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4436 lines
140 KiB
4436 lines
140 KiB
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combining to form microclots, that's all I'm totally down with that. But to then
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jump to the stage where that explanation now covers all of the problems with
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vaccines, it's another problem with vaccines. And I think that's the that's
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the that's the nuance that everybody needs to constantly be vigilant of
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because all all of the people that are trying to trip us up for sure are
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gonna give us easy explanations which replace other explanations. And that is
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a temptation that you cannot jump to because it's just like the DNA
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contamination of the RNA shot is now tempting to jump to that as the
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explanation where in reality we have this whole toolbox of of attributes of
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transfection which are bad and then the quality control and then this and then
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they all add together and the trick is to not let any one of us any one of
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these these explanations start to dominate to the point where all of the
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other impacts which we know are real are diluted or lost and that's basically
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what they're trying to do with the with the protocols right they're trying to
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tell stories and stories and stories so that the protocols go farther and farther
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into the past so that the rising number of opioid deaths from 2020 to 2021 to
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2022 go farther and farther in the past that's what they want and so that's why
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13:36.100 --> 13:41.700
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we have to be very vigilant and and work constantly to to update this list and
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13:41.700 --> 13:47.060
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not let the list be changed but rather just added to and that that was
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13:47.060 --> 13:51.820
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|
especially true with regard to what Kevin McCurn and I believe has been
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13:51.860 --> 13:58.940
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basically up to is he's populating this list but then he's he's not reciting it
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13:58.940 --> 14:03.300
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anymore and so if he if he has all this publicity has all this chance to tell
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people how bad transfection is he's definitely not taking advantage of it
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14:07.660 --> 14:12.100
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and instead he's focused on the latest greatest thing which is this CD and A
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14:12.100 --> 14:16.340
|
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contamination which of course is a very different objection than what he was
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14:16.340 --> 14:22.820
|
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making in 2020 in 2021 in 2022 and it's really important that we pay
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14:22.820 --> 14:28.980
|
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attention to these people because it's over time it's it's very hard to lie
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14:28.980 --> 14:34.540
|
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consistently and you can be like Mark and you can have made mistakes you can be
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14:34.540 --> 14:39.380
|
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like Mark and have sort of followed false leads or chased things that didn't
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14:39.460 --> 14:47.100
|
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need to be chased anymore but if he's correcting himself and he's he's if he's
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14:47.100 --> 14:52.180
|
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reevaluating where he stands like I try to do and like others try to do then
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14:52.180 --> 14:56.180
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then there's nothing wrong with playing a few notes as long as you're playing
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14:56.180 --> 15:03.820
|
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with passion and with the idea that that you want to get better and so you know
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15:03.820 --> 15:07.620
|
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it feels really good but I'm gonna try and take a little easy on my throat just
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15:07.620 --> 15:12.060
|
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to make sure I don't go nuts because I'm really excited and and I want to just
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15:12.060 --> 15:19.620
|
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talk all day but we're gonna go a little slower here so the show must go on and
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15:19.620 --> 15:29.220
|
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we did a number of shows recently about about companies related to Canadian
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15:29.220 --> 15:37.620
|
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biosciences and it's become really increasingly curious to me how so much
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15:37.620 --> 15:41.100
|
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of this story is just crossed that border and how much of that story
|
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15:41.100 --> 15:44.940
|
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actually was already across the border at the very early parts of the pandemic
|
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15:44.940 --> 15:51.580
|
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with this with this researcher who a Chinese researcher who was working on Z
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15:51.580 --> 15:56.100
|
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map and had this antibody cocktail that was really good and was on the front of
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15:56.140 --> 16:03.660
|
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time and and then accused of being a spy and stealing and disappearing and it
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16:03.660 --> 16:08.580
|
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wasn't really clear what it was about this lady that was weird but Mark was
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16:08.580 --> 16:13.260
|
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one of the first people to really point out that this Z map was this antibody
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16:13.260 --> 16:19.420
|
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cocktail that might have been useful for this or or at least wasn't
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16:19.420 --> 16:23.780
|
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antibody cocktail that had been previously compared to remdesivir and so
|
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16:23.780 --> 16:29.980
|
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there was reason to believe that that this Z map would would somehow muddy the
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16:29.980 --> 16:35.540
|
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waters around remdesivir and maybe it needed to disappear anyway we have more
|
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16:35.540 --> 16:41.780
|
|
recently crossed the border into Canada with regards to Peter colas and Peter
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16:41.780 --> 16:47.180
|
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colas brought us to Canada because number one he's the guy who apparently is
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16:47.180 --> 16:50.600
|
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responsible for the intellectual property of the lipid nanoparticles
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16:50.600 --> 16:55.760
|
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that are now used for all of these gene therapies and vaccines I shouldn't
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16:55.760 --> 17:02.200
|
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call them vaccines and transfections but more importantly Robert Malone was the
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17:02.200 --> 17:08.600
|
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one who actually pointed us to him in one of his sub-stacks which was being
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17:08.600 --> 17:14.000
|
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quite critical of the awarding of the Nobel Prize and said that you know if
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17:14.000 --> 17:20.800
|
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anybody had and he used the patent law language enabling technology it would
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17:20.800 --> 17:28.080
|
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be Peter colas and so in my offline discussions with my friend regular guy
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17:28.080 --> 17:34.120
|
|
it became clear to him in his eyes that the language that Robert Malone had
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17:34.120 --> 17:39.120
|
|
been using in that article was really intellectual property law type language
|
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17:39.120 --> 17:43.320
|
|
when you say enabling technology in regards to a patent you really talking
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17:43.320 --> 17:51.520
|
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about patent law and in that sense it seemed almost as if the the idea of the
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17:51.520 --> 17:56.040
|
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intellectual property that was being you know acknowledged with the MR of the
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17:56.040 --> 18:01.800
|
|
mRNA with the Nobel Prize that intellectual property may not be as solid
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18:01.800 --> 18:09.200
|
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as the award might make it seem and the reason why is because the enabling
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18:09.200 --> 18:14.240
|
|
technology in Robert Malone's mind wasn't the chemical alterations of the
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18:14.240 --> 18:18.760
|
|
mRNA but it was the lipid nanoparticles that allowed it so it's an interesting
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18:18.760 --> 18:24.600
|
|
assertion because remember and I'm just breaking this down with this on screen
|
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18:24.600 --> 18:28.560
|
|
I don't really know why maybe you can you can copy this video that we're gonna
|
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18:28.560 --> 18:37.640
|
|
watch here but it's interesting because up until that statement it should be
|
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18:37.640 --> 18:45.720
|
|
very clear to you that it was his it was his idea of using RNA as a vaccine
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18:45.720 --> 18:53.840
|
|
and all of the he had like eight patents around this so as he first came out in
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18:53.840 --> 19:01.840
|
|
2021 remember part of the reason why he came out was to claim in mentorship but
|
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19:02.200 --> 19:08.320
|
|
now after the Nobel Prize is awarded it's almost a change in position if you
|
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19:08.320 --> 19:14.800
|
|
think that well in 2021 I was the one who came up with all the relevant ideas for
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19:14.800 --> 19:20.320
|
|
using RNA as a vaccine and then when the Nobel Prize is awarded you say well
|
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19:20.320 --> 19:24.480
|
|
actually what they did isn't that impressive because the enabling
|
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19:24.480 --> 19:31.680
|
|
technology is is Peter Kullis's technology so it's a very very
|
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|
19:31.680 --> 19:36.240
|
|
interesting pivot that actually is not consistent with his his earlier three
|
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19:36.240 --> 19:44.120
|
|
years of behavior and so you can only see this as a continuing evolving op or
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19:44.120 --> 19:49.560
|
|
continuing evolving construct it's not just somebody struggling to tell the
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19:49.560 --> 19:54.080
|
|
truth this is a person who is adjusting the narrative and adjusting what he
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19:54.120 --> 19:59.600
|
|
says in order to keep aiming at whatever goal they're aimed at and I think that
|
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19:59.600 --> 20:05.960
|
|
that's how you should start to see most of the people's changing behavior is if
|
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20:05.960 --> 20:10.120
|
|
you think about what their goal was for the entire three years that I've been
|
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20:10.120 --> 20:15.360
|
|
online my goal has been to free my children from this illusion into free our
|
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|
20:15.360 --> 20:20.720
|
|
society from this illusion and that's not really the goal of a lot of other
|
|
|
|
20:20.760 --> 20:29.080
|
|
people that let's say compete for this this kind of airtime I mean Kevin McCarran
|
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|
|
20:29.080 --> 20:36.000
|
|
has never been about stopping the thing Kevin McCarran has never been about
|
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|
20:36.000 --> 20:41.560
|
|
breaking any illusions that are around it's been about maximum fear and
|
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|
|
20:41.560 --> 20:47.160
|
|
confusion and really Kevin McCarran has never been about stopping anything he's
|
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20:47.200 --> 20:53.720
|
|
never said that transfection and kids would be crazy and the list really goes
|
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|
20:53.720 --> 21:00.280
|
|
on quite long how many people haven't said really anything useful about what
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21:00.280 --> 21:05.880
|
|
about what should be done with regard to this technology and they certainly
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|
21:05.880 --> 21:10.920
|
|
didn't say it with any in any useful length of time and so here we are this
|
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|
|
21:10.920 --> 21:18.200
|
|
is the epivax presentation from January 26th 2021 so put that into your time
|
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|
21:18.200 --> 21:24.400
|
|
frame we are about to roll out the we had already rolled out the vaccines in the
|
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|
21:24.400 --> 21:31.400
|
|
UK so the the the J&J and the AstraZeneca are already out and we're about to roll
|
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|
21:31.400 --> 21:37.640
|
|
out the mRNA and epivax is also trying to put together a vaccine candidate and
|
|
|
|
21:38.120 --> 21:43.840
|
|
and they were actually working with crazy enough the University of Seattle I
|
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21:43.840 --> 21:49.320
|
|
believe or University why I don't know which one it is Mark would know where a
|
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|
21:49.320 --> 21:55.560
|
|
guy by the name of Biesler was working and Biesler also surprisingly had a
|
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|
|
21:55.560 --> 22:03.160
|
|
three-dimensional model of the spike like in in February or January of 2020 he had
|
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|
|
22:03.160 --> 22:10.120
|
|
a candidate vaccine ready to go based on the spike in a nanoparticle and that's
|
|
|
|
22:10.120 --> 22:17.240
|
|
also where Sohomish County man just happened to be so epivax is a company
|
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|
|
22:17.240 --> 22:23.440
|
|
who for whom Robert Malone was a consultant for a very long time from
|
|
|
|
22:23.440 --> 22:30.640
|
|
2005 to 2018 or something like this and epivax is also a a company that has
|
|
|
|
22:30.640 --> 22:40.320
|
|
worked with Abcellular which is this this
|
|
|
|
22:40.480 --> 22:45.760
|
|
which is this company in Canada that is developing antibodies or finding them
|
|
|
|
22:45.760 --> 22:50.680
|
|
with this new technology that we watched yesterday so I want to watch this
|
|
|
|
22:50.680 --> 22:56.720
|
|
video because in this video they're going to discuss the methodological
|
|
|
|
22:56.800 --> 23:04.480
|
|
technology that is epivax and I think it's really Mark sent me a video this
|
|
|
|
23:04.480 --> 23:09.120
|
|
morning from was it eight years ago or something like that where this lady is
|
|
|
|
23:09.120 --> 23:15.000
|
|
also talking about this technology on a news program and I thought to watch that
|
|
|
|
23:15.000 --> 23:18.200
|
|
one now but actually I'm gonna watch that one with Mark sometime and invite him
|
|
|
|
23:18.200 --> 23:22.040
|
|
to watch it because it's an older one and she makes some crazy references this
|
|
|
|
23:22.040 --> 23:24.920
|
|
one has a lot more biology and it's I thought it'd be more appropriate for a
|
|
|
|
23:24.920 --> 23:27.880
|
|
study hall and I can take some notes and then give my voice a little bit of
|
|
|
|
23:27.880 --> 23:32.520
|
|
rest in between but not that it really needs rest the only reason why sometimes
|
|
|
|
23:32.520 --> 23:37.400
|
|
sound doesn't come out I think is because there's that flap of skin or
|
|
|
|
23:37.400 --> 23:42.880
|
|
tissue or whatever it was that was full of blood and then it emptied so it's
|
|
|
|
23:42.880 --> 23:50.480
|
|
kind of still there but I mean I don't I don't hear it sometimes but it's not
|
|
|
|
23:50.480 --> 23:55.960
|
|
like it was I could never do that yesterday I mean it's it's crazy how
|
|
|
|
23:55.960 --> 24:04.960
|
|
happy I am to have my voice back so let's see if it's here yes it is great
|
|
|
|
24:10.640 --> 24:16.160
|
|
thank you guys for joining me tonight I know that I am the CEO and CSO heavy
|
|
|
|
24:16.240 --> 24:20.360
|
|
acts incorporated and I'll be talking to you today about prediction and
|
|
|
|
24:20.360 --> 24:25.040
|
|
validation of immunogenicity and tolerance to generic peptides and
|
|
|
|
24:25.040 --> 24:35.600
|
|
impurities clearly this refers to the FDA draft guidance in which the FDA
|
|
|
|
24:35.600 --> 24:42.920
|
|
requested sponsors to identify impurities in their generic drug products
|
|
|
|
24:43.000 --> 24:49.200
|
|
that were above a certain percentage of the final drug product and and their
|
|
|
|
24:49.200 --> 24:57.440
|
|
request and validation sorry I missed the title too
|
|
|
|
24:57.440 --> 25:02.800
|
|
hey everyone this is Annie DeGroote I am the CEO and CSO heavy-vax
|
|
|
|
25:02.800 --> 25:07.640
|
|
incorporated and I'll be talking to you today about prediction and validation of
|
|
|
|
25:07.640 --> 25:17.560
|
|
immunogenicity and tolerance to generic peptides and impurities clearly this
|
|
|
|
25:17.560 --> 25:25.640
|
|
refers to the FDA draft guidance in which the FDA requested sponsors to identify
|
|
|
|
25:25.640 --> 25:31.920
|
|
impurities in their generic drug products that were above a certain
|
|
|
|
25:32.000 --> 25:37.360
|
|
percentage of the final drug product and and their request related to the
|
|
|
|
25:37.360 --> 25:42.600
|
|
identification of T cell epitopes shown in this slide that could be present in
|
|
|
|
25:42.600 --> 25:48.640
|
|
the impurities in the drug product it turns out that we've been working in the
|
|
|
|
25:48.640 --> 25:54.960
|
|
field of immunogenicity risk assessment focusing on peptides and
|
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|
|
25:54.960 --> 26:01.080
|
|
proteins and their T cell epitopes for the last 20 years so we developed a
|
|
|
|
26:01.080 --> 26:06.000
|
|
comprehensive program for assessing the immunogenicity risk of peptide
|
|
|
|
26:06.000 --> 26:11.120
|
|
impurities building on decades of experience with biologics this program
|
|
|
|
26:11.120 --> 26:17.760
|
|
is called the panda program for peptide accelerated new drug application no and
|
|
|
|
26:17.760 --> 26:23.280
|
|
one of the things that I want to point out here is that this T cell epitope thing
|
|
|
|
26:23.280 --> 26:28.280
|
|
that she's speaking about is actually very serious the reason why I think it's
|
|
|
|
26:28.320 --> 26:33.960
|
|
serious is because in 2020 late 2020 when people were still screaming about the
|
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|
|
26:33.960 --> 26:42.920
|
|
spike protein being a designed protein and I was still playing along it really
|
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|
|
26:42.920 --> 26:51.680
|
|
felt like to me that one possibility was that they lied about the virus but they
|
|
|
|
26:51.680 --> 26:57.000
|
|
they lied to the extent to which they actually lied about the spike and so
|
|
|
|
26:57.000 --> 27:02.440
|
|
the spike was a designed spike on purpose with the idea that okay we're
|
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|
27:02.440 --> 27:06.840
|
|
gonna lie about this virus but then we're gonna say that it has this spike and
|
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|
|
27:06.840 --> 27:12.080
|
|
this spike protein we're gonna use it for the vaccine and why because we've
|
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|
|
27:12.080 --> 27:18.560
|
|
already altered it we've already added a couple let's say universal T cell
|
|
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|
27:18.560 --> 27:23.840
|
|
epitopes so that we know that this spike protein will generate antibodies and
|
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|
|
27:23.880 --> 27:29.240
|
|
more importantly we can predict with a reasonably high accuracy what antibodies
|
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|
27:29.240 --> 27:34.120
|
|
they will produce or at least what epitopes they will target and so then
|
|
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|
27:34.120 --> 27:39.520
|
|
all you really need to know is how that epitope will be evaluated and
|
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|
27:39.520 --> 27:44.800
|
|
represented given the different HLA subtypes of a particular person and
|
|
|
|
27:44.800 --> 27:50.840
|
|
that's what she's talking about for 20 years they've been working on finding the
|
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|
27:50.840 --> 27:58.520
|
|
T cell epitopes that are chosen by your immune system when exposed to
|
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|
27:58.520 --> 28:06.600
|
|
proteins and trying to see if there's some pattern based on the HLA receptors
|
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|
28:06.600 --> 28:14.960
|
|
of the animal or the human what is the pattern of T cell epitope selection and
|
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|
|
28:14.960 --> 28:19.560
|
|
is that pattern predictable and she's been working on it for a very long time
|
|
|
|
28:19.560 --> 28:26.580
|
|
now the reason why I find it enticing is because before I got to clones and
|
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|
28:26.580 --> 28:31.080
|
|
swarm and all this other stuff and I was still really playing along with the idea
|
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|
28:31.080 --> 28:34.280
|
|
that it was a lab leak and something is spreading around which again is still a
|
|
|
|
28:34.280 --> 28:41.520
|
|
possibility that the idea would be to lie about the sequence so that you could
|
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|
|
28:41.520 --> 28:51.720
|
|
get your guaranteed shoe in immunogen into the vaccine and so you could imagine
|
|
|
|
28:51.720 --> 28:56.400
|
|
this story where you everybody insists that this spike bro spike bro spike
|
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|
28:56.400 --> 29:01.960
|
|
protein all the time and all these people are laughing because while the spike
|
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|
|
29:01.960 --> 29:09.400
|
|
protein is being portrayed as this evil evil protein it's really not it's a
|
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|
29:09.400 --> 29:14.760
|
|
design protein guaranteed to produce seroprevalence and even more importantly
|
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|
|
29:14.760 --> 29:22.960
|
|
it could be guaranteed to produce seroprevalence on many serial exposures
|
|
|
|
29:22.960 --> 29:28.200
|
|
because it's a T cell epitope that in theory the immune system would have a
|
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|
29:28.200 --> 29:35.440
|
|
harder time ignoring it and that's the product that's the that's the product
|
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|
|
29:35.440 --> 29:39.840
|
|
design from a vaccine designer's perspective that's the product design
|
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|
|
29:39.840 --> 29:46.560
|
|
you want because the NIH says that antibodies are the indication of immunity
|
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|
|
29:46.560 --> 29:49.880
|
|
and the antibodies are how they're going to measure the effectiveness of your
|
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|
29:49.880 --> 29:56.280
|
|
product and so if you have a product where you can you can administer it
|
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|
29:56.280 --> 30:01.120
|
|
multiple times and every time you get a good robust antibody response it's the
|
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|
|
30:01.200 --> 30:08.600
|
|
ideal vaccine and so what she has been working on with this company basically
|
|
|
|
30:08.600 --> 30:15.640
|
|
for 20 years is that this ability to hijack what the T cells are doing and
|
|
|
|
30:15.640 --> 30:22.640
|
|
force them to react and it's doing it by selecting these epitopes out of the
|
|
|
|
30:22.640 --> 30:26.520
|
|
natural proteins and looking at the responses and screening them and using
|
|
|
|
30:26.520 --> 30:33.120
|
|
computational approaches to narrow down see it's still there to the proteins
|
|
|
|
30:33.120 --> 30:38.760
|
|
that will that will produce this I'm sure it's just scar tissue that's got to
|
|
|
|
30:38.760 --> 30:44.480
|
|
work his way out now I mean maybe my voice will get even lower peptide
|
|
|
|
30:44.480 --> 30:51.000
|
|
accelerated new drug application and the methods that I'm going to describe
|
|
|
|
30:51.000 --> 30:56.440
|
|
today are published in this recent compendium of methods in immunogenicity
|
|
|
|
30:56.440 --> 31:03.600
|
|
risk assessment that was written by a group of members of the APS therapeutic
|
|
|
|
31:03.600 --> 31:10.000
|
|
protein immunogenicity group so please refer to this article for additional
|
|
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details on the assays and in silico tools that I'll be talking about today
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members of the team that work with me include Brian Roberts who's the associate
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scientific director and manager of the protein therapeutics program at Epivax
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31:26.240 --> 31:30.880
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Francis Terry who is the director of analysis and immuno informatics at
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31:30.880 --> 31:35.200
|
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epivax and Bill Martin who is co-founder of epivax and the architect of our
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31:35.200 --> 31:41.240
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in silico tools of course I would be remiss not to mention the epivax panda
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team members who work in the laboratory to do the validation of the in silico
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predictions that we make and they are listed here on this slide my talk will be
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divided in four parts first why do immunogenicity screening peptides what
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31:56.760 --> 32:01.080
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what is it about these impurities that could generate a T cell response how to
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do it in silico and in vitro and I'll be describing the special tools that we
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have that evaluate tolerance and help find T reg epitopes I will also be
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describing some case studies that we recent T regulatory epitopes boy oh boy
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they're really they're doing it all like this is exactly what before I knew
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that's company existed I would have said that you need to be working on and so now
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you just imagine just imagine remember Robert Malone has been consulting with
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all of these companies that are in a position like absolera to make
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antibodies with mRNA she is in a position to make small peptides with
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mRNA so it's all kind of the same next generation game and now I might be going
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out on a limb here when I say this but it almost seems like that's the whole game
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that was the whole game all they have to do is preserve the national security
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priority of vaccinating against covid and then all they got to do is make the
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first generation of covid vaccines kind of lame and now guess what we need new
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vaccines for covid and those new vaccines will be much better because we
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won't use this silly spike protein we'll just use a few T cell epitopes or we'll
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we'll just make the antibodies and so after four years of brainwashing
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|
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everybody or 40 years of brainwashing everybody the antibodies are important
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|
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they've finally gotten around to saying well we'll just find the antibody and
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make the RNA and code for it that's not gonna work there's lots of reasons why
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that's not gonna work and we'll talk about that over the next weeks but I'm
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just trying to let you know that this sounds like reasonable immunology it
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sounds like really smack on point immunology that you we should have we
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should have been hearing so now the question I'm just burping from drinking
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|
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too much if the question is how deceptive is she gonna be about antibodies and
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34:21.440 --> 34:27.800
|
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T cells how deceptive is she gonna be about the order in which those memories
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are made I think she's gonna have to do some hand waving here because she can't
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be too aggressive and say that actually the whole immune system is T cells and
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|
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antibodies are dumb she can't say that but I'm sure that when they're in their
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|
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own offices that's what they're always thinking they're always thinking that
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well yeah but anybody's come from T cells I mean they they require T cell
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|
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help and all this other stuff and T regulatory cells to down like it I mean
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34:54.040 --> 34:58.120
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she obviously knows that so it's gonna be a good talk it's only 30 minutes long
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|
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I'll try not to interrupt it anymore we completed under an FDA contract on
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|
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calcitonin and terraperitide impurities and we'll show you some of the
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35:07.440 --> 35:14.200
|
|
interesting findings that we uncovered while doing those projects now I'm gonna
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35:14.200 --> 35:19.920
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be primarily focusing on in silico so I do want to go over how a peptide drug
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|
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impurity can potentially be presented to a T cell so that's illustrated in this
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|
|
slide here you can see a peptide drug which could be up to 50 amino acids in
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35:29.320 --> 35:34.720
|
|
length and a peptide impurity which contains a modification to the amino acid
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35:34.720 --> 35:40.840
|
|
sequence notice that this impurity is shorter mainly because in the antigen
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35:40.840 --> 35:45.640
|
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presenting cell it will be processed down to the length that will be presented on
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35:45.640 --> 35:50.720
|
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the surface of the HLA binding molecule on the surface of the antigen presenting
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35:50.720 --> 35:56.220
|
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cell the these so I'm I gotta say I'm actually confused because they're talking
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35:56.220 --> 36:00.300
|
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about impurities so that's I guess you produce proteins and there's a certain
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|
|
amount of impurities and so what she's trying to figure out how these impurities
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|
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cause T cell activation this is like bait and switch and what she's trying to
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36:11.260 --> 36:17.660
|
|
explain and what she's trying to talk around I'm sure of it is that T cell
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36:17.660 --> 36:22.220
|
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epitopes are only about nine amino acids long and so these very short
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36:22.300 --> 36:27.260
|
|
proteins are actually extremely dangerous because they have a propensity to
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36:27.260 --> 36:34.140
|
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easily be presented as antigens unlike the larger proteins which need to be
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36:34.140 --> 36:38.820
|
|
brought in and then process down to smaller fragments and then that process
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36:38.820 --> 36:46.140
|
|
and this is the trick that process is the responsibility of this mature antigen
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36:46.140 --> 36:52.140
|
|
presenting cell it's a process that we don't understand and so the larger
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36:52.140 --> 37:00.300
|
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protein goes in that's this one and it gets it gets processed by the antigen
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37:00.300 --> 37:05.220
|
|
presenting cell and it's something we don't understand what she has noticed
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37:05.220 --> 37:10.740
|
|
and pharmacological producers of biologics have noticed is that the
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37:11.100 --> 37:16.860
|
|
impurities the small peptides are the ones that tend to generate the immune
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37:16.860 --> 37:21.180
|
|
response and that's because of this and the way that the processing in a in a
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37:21.180 --> 37:28.180
|
|
mature antigen presenting cell works if you don't give it anything to break down
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37:28.180 --> 37:34.540
|
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then there's nothing really to do but present and I'm not speaking from knowledge
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37:34.860 --> 37:41.500
|
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here I'm I'm imagining based on what I understand of antigen presentation and
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37:41.500 --> 37:48.580
|
|
the the sorting of an antigen to the epitope that you present to the T cells
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37:48.580 --> 37:54.140
|
|
and that selection process is extremely important in what she and her epivax
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37:54.140 --> 37:58.940
|
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company have been doing over the last decades is trying to figure that process
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37:58.940 --> 38:06.460
|
|
out what parts of peptides are regularly chosen as T cell epitopes and how does
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|
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that interplay connect with HLA diversity HLA being the MHC receptor that is used
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38:13.580 --> 38:22.100
|
|
by them and by T cells to to compare notes so to speak if you just join me I
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38:22.100 --> 38:29.180
|
|
hear a look a bunch of people there just join me yes a polyp or a blister or
|
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38:29.180 --> 38:35.980
|
|
some kind of growth in my throat exploded today on a cough it filled my mouth
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38:35.980 --> 38:41.900
|
|
with blood I spit it out on the garage floor I looked at my son and I said the
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38:41.900 --> 38:48.140
|
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words I might need some help and it came out like I might need some help and my
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38:48.180 --> 38:54.100
|
|
voice was back and so I actually haven't had this voice this exact voice I don't
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38:54.100 --> 39:00.820
|
|
think in maybe six years it started to go away when I was on my bike and it's
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39:00.820 --> 39:06.700
|
|
just slowly gone worse in the last couple years it really went awful and I think
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39:06.700 --> 39:11.420
|
|
it was this thing this I don't know what it was I haven't been to the doctor I
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39:11.420 --> 39:18.460
|
|
don't know all I know is I'm not feeling any real pain if I cough it's a little
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39:18.460 --> 39:23.500
|
|
painful but if I'm talking it feels fine and I don't need the best thing is I
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39:23.500 --> 39:27.420
|
|
don't need to force any air through my voice box anymore I'm not running out of
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39:27.420 --> 39:31.900
|
|
breath you can hear me right now I still when I breathe there's this little thing
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39:31.900 --> 39:38.380
|
|
in there I don't know if it's loose skin or what it is that you hear it but it
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39:38.860 --> 39:43.780
|
|
doesn't it doesn't stop me that thing was waking me up at night it was blocking
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39:43.780 --> 39:48.700
|
|
my breathing at night and and I was actually having sleep dapnea for the
|
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39:48.700 --> 39:54.740
|
|
last two and a half months or something so that's all the reason why my my my
|
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39:54.740 --> 39:58.900
|
|
health has been going downstream or downhill very rapidly and I think this
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39:58.900 --> 40:02.660
|
|
is gonna be a huge turnaround because of anything I'm gonna get sleep now sorry
|
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40:02.660 --> 40:09.620
|
|
back to T cell activation peptides can be anywhere between 8 or 9 to 15 to 20
|
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|
40:09.620 --> 40:12.540
|
|
amino acids in the length when they're presented on the surface of the cell
|
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|
40:12.540 --> 40:19.020
|
|
but the key sequence that binds into the HLA molecule binding groove is about
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40:19.020 --> 40:24.020
|
|
9 amino acids in length the side chains of the peptide will bind into the
|
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|
40:24.020 --> 40:27.580
|
|
binding pockets and you can well imagine that a peptide drug that has a
|
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|
40:27.580 --> 40:32.020
|
|
modification of one of its residues may not bind with the same affinity or may
|
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|
40:32.020 --> 40:37.780
|
|
bind with a different affinity than the active pharmaceutical ingredient or the
|
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|
40:37.780 --> 40:43.180
|
|
API in this picture on the right-hand side I've illustrated for you in in an
|
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|
40:43.180 --> 40:50.820
|
|
EM electron microscope a picture the interaction with T cell it's receptor
|
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|
40:50.820 --> 40:55.340
|
|
which you can't even see on this slide and the antigen presenting cell that's
|
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|
|
40:55.340 --> 40:59.260
|
|
presenting HLA you can see that there's probably a very close fit between those
|
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40:59.260 --> 41:04.300
|
|
two cells and what the T cell is coming down to see is the peptide lying in a
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|
|
41:04.300 --> 41:10.780
|
|
linear fashion in the HLA molecule and there is a face that faces down and binds
|
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|
41:10.780 --> 41:15.820
|
|
to the HLA that's called the epitope and there's sorry the agritope and there's a
|
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|
41:15.820 --> 41:19.860
|
|
face that faces up to the T cell receptor and that's called the epitope the
|
|
|
|
41:19.860 --> 41:23.860
|
|
epitope is what drives the T cell response and that can be good or bad
|
|
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|
41:23.860 --> 41:30.700
|
|
depending on which T cell is responding so why do impurities affect the T cell
|
|
|
|
41:30.700 --> 41:35.380
|
|
response to peptide drug well let's take our API and now let's make some
|
|
|
|
41:35.380 --> 41:41.020
|
|
modification and to it the way that they would occur in a synth in a synthetic
|
|
|
|
41:41.020 --> 41:47.820
|
|
process you could have truncations that could remove peptide T cell epitopes you
|
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|
41:47.820 --> 41:52.780
|
|
could have amino acid deletions that change the sequence so that the frame of
|
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|
|
41:52.780 --> 41:57.260
|
|
the nimer is disturbed and if there is a T cell epitope there it's no longer
|
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|
41:57.260 --> 42:02.500
|
|
gonna bind in the HLA molecule you could have an amino acid insertion which
|
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|
42:02.500 --> 42:06.940
|
|
could change the side chain that's binding into the HLA molecule or it
|
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|
42:06.940 --> 42:10.900
|
|
could actually shift everything over and I'll show show you that disturbing the
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|
42:10.900 --> 42:16.500
|
|
binding frame you could have amino acid duplications which again shift the
|
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|
42:16.500 --> 42:21.460
|
|
binding frame of T cell epitopes and you could also have incorporation of
|
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|
42:21.460 --> 42:27.700
|
|
unusual amino acids such as stereoisomers or side chain modifications which also
|
|
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|
42:27.700 --> 42:32.340
|
|
interfere with the binding of the peptide to the HLA molecule and that's
|
|
|
|
42:32.340 --> 42:36.580
|
|
what's illustrated in greater detail on this slide I've already mentioned that
|
|
|
|
42:36.580 --> 42:41.380
|
|
there's a an agritope side of the T cell epitope that might be in your peptide
|
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|
42:41.380 --> 42:48.860
|
|
drug and there is an epitope side which faces up to the T cell receptor there
|
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|
|
42:48.860 --> 42:52.780
|
|
are specific amino acids that bind to the HLA and there so this is interesting
|
|
|
|
42:52.780 --> 42:57.860
|
|
I've never seen this biology before apparently the HLA receptor interacts
|
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|
42:57.860 --> 43:05.380
|
|
with certain amino acids of the epitope and the the T cell react so I don't know
|
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|
43:05.380 --> 43:08.940
|
|
if this would be like their functional groups that would stick out this way or
|
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|
43:08.940 --> 43:14.420
|
|
their charged groups that would stick out this way it's a very interesting way of
|
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43:14.820 --> 43:21.500
|
|
and she's portraying that in every picture which I guess I got to read because I
|
|
|
|
43:21.500 --> 43:26.820
|
|
didn't know that they knew this much about how antibodies were interesting
|
|
|
|
43:26.820 --> 43:32.060
|
|
we're here in this slide and other ones that bind up that face the T cell
|
|
|
|
43:32.060 --> 43:37.100
|
|
receptor that is recognized by the T cell let's now introduce a duplication of
|
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|
43:37.100 --> 43:42.740
|
|
an amino acid of position two and you can imagine that a peptide that once
|
|
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|
43:42.820 --> 43:48.780
|
|
found to HLA now that you've shifted the frame over by one position no longer
|
|
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|
43:48.780 --> 43:53.620
|
|
presents side chains that bind down into the HLA binding group so that peptide
|
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|
43:53.620 --> 43:59.220
|
|
will no longer bind to the HLA molecule that may be good if there was a T cell
|
|
|
|
43:59.220 --> 44:02.700
|
|
response there you would obviously potentially lose it because the peptide
|
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|
44:02.700 --> 44:06.900
|
|
will no longer bind if there was however a T cell response that could
|
|
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|
44:06.900 --> 44:11.580
|
|
induce a suppressor immune response a regulatory T cell then you might not
|
|
|
|
44:11.620 --> 44:16.820
|
|
want to lose that signal in your peptide drug so let's look at the
|
|
|
|
44:16.820 --> 44:22.140
|
|
converse maybe you have a sequence that doesn't bind so did you hear what she
|
|
|
|
44:22.140 --> 44:28.660
|
|
said and this is really key she said that if you have a a mutation in or a
|
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|
|
44:28.660 --> 44:32.660
|
|
deletion that gets rid of your T regulatory response you might not want
|
|
|
|
44:32.660 --> 44:37.940
|
|
that and why not because we've talked about this before the basics of the T
|
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|
|
44:37.980 --> 44:43.540
|
|
cell response are such that the T cell response ramps up the inflammation
|
|
|
|
44:43.540 --> 44:49.100
|
|
ramps up the immune response and a corresponding T regulatory cell
|
|
|
|
44:49.100 --> 44:54.260
|
|
response that recognizes many of the same epitopes is responsible for the
|
|
|
|
44:54.260 --> 45:00.220
|
|
day crescendo and so if you only have T cell epitopes which stimulate T cells
|
|
|
|
45:00.220 --> 45:05.060
|
|
but not T regulatory cells then you'll have this imbalance induced by your
|
|
|
|
45:05.060 --> 45:08.820
|
|
biologic I think that's what she's talking about here and it's really
|
|
|
|
45:08.820 --> 45:15.740
|
|
curious to hear someone talk so focused on T cells and not realize that that
|
|
|
|
45:15.740 --> 45:20.980
|
|
all of these vaccines that are being sold distributed whatever I just don't
|
|
|
|
45:20.980 --> 45:25.660
|
|
don't even look at this it's not even on their radar I guess that's what makes
|
|
|
|
45:25.660 --> 45:30.140
|
|
their that's what makes this company so good to see you can hear my voice is
|
|
|
|
45:30.140 --> 45:34.420
|
|
not the other thing I have to tell you is that because that ball was in the back
|
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|
|
45:34.460 --> 45:37.420
|
|
of my throat I haven't been able to get all the mucus out of my lungs like I
|
|
|
|
45:37.420 --> 45:41.060
|
|
should have so I'm probably going to need to cough a lot of stuff out over the
|
|
|
|
45:41.060 --> 45:45.180
|
|
next few days and maybe that'll give me more wind too I don't know but I can
|
|
|
|
45:45.180 --> 45:51.540
|
|
tell you that my voice is rattling around in my voice box and in my jaw in a way
|
|
|
|
45:51.540 --> 45:56.740
|
|
that it hasn't done in at least five years
|
|
|
|
45:56.860 --> 46:03.140
|
|
not want to lose that signal in your peptide drug so let's look at the
|
|
|
|
46:03.140 --> 46:09.020
|
|
converse maybe you have a sequence that doesn't bind it's a particular peptide
|
|
|
|
46:09.020 --> 46:13.620
|
|
that doesn't seem to have any T-cell epitopes in it now you introduce a
|
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|
|
46:13.620 --> 46:18.620
|
|
duplication of the amino acid in position two you've just shifted the side chains
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46:18.620 --> 46:24.380
|
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over and now you have an agritope which will bind to HLA and present an epitope
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46:24.380 --> 46:28.620
|
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to the T cell receptor that could be a new immunogenic impurity and that's
|
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46:28.620 --> 46:32.300
|
|
exactly what we're talking about when we're concerned about impurities and
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46:32.380 --> 46:37.140
|
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their potential to trigger a T-cell response so how do we look for these
|
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46:37.140 --> 46:43.700
|
|
T-cell epitopes we have basically a three-step process which also involves a
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46:43.700 --> 46:50.060
|
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four-step integrating everything into one overall perspective and we start always
|
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46:50.060 --> 46:54.420
|
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with epitope prediction because we want to look and see if the T-cell epitope is
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46:54.420 --> 47:01.500
|
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present in the API and how far from that binding kind of threshold will the
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47:01.540 --> 47:05.220
|
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impurities travel maybe you have something that has a lot of T-cell epitopes in it
|
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47:05.220 --> 47:10.300
|
|
impurities will therefore induce a lot of new epitopes if you have something
|
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47:10.300 --> 47:14.220
|
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that doesn't have any T-cell epitopes in it it's hard to imagine how immunogenic
|
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47:14.220 --> 47:18.020
|
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that could be with the substitution of a single amino acid because that won't
|
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47:18.020 --> 47:22.620
|
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really change a lot about the binding capability of that T-cell of that sorry
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47:22.620 --> 47:28.460
|
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peptide sequence so we start with epitope prediction and then we validate we like
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47:28.460 --> 47:33.100
|
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to check at least HLA binding maybe the peptide is not predicted to bind will
|
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47:33.100 --> 47:39.020
|
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validate that in HLA binding assay just to confirm our suspicion but we also like
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47:39.020 --> 47:43.340
|
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to do T-cell assays and we can do that with naive blood because naive donors
|
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47:43.340 --> 47:47.740
|
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have never seen the drug or its impurities so it's similar to testing it
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47:47.740 --> 47:52.500
|
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in a patient so the the epitope prediction is the first step and then
|
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47:52.500 --> 47:57.540
|
|
we'll start with the API sequence and then compare it to the impurities that
|
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47:57.580 --> 48:04.060
|
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we can look at also in silico we use the epimatrix tool it is an algorithm that
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48:04.060 --> 48:10.820
|
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has been developed over 20 plus years developed epivax it predicts both class
|
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48:10.820 --> 48:14.380
|
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one and class two binding potential and here we're going to be focusing focusing
|
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48:14.380 --> 48:21.860
|
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on class two which facilitates cytokine release as well as antibody response so
|
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48:21.860 --> 48:25.060
|
|
that might be the the two things that you're going to be concerned about in
|
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48:25.100 --> 48:32.660
|
|
terms of a safety signal for peptide drugs it's an algorithm that focuses on
|
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48:32.660 --> 48:38.060
|
|
nine HLADR supertypes for the purpose of measuring immunogenicity risk why
|
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48:38.060 --> 48:42.780
|
|
do we do that because when we look at all of the different human HLAs we can
|
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48:42.780 --> 48:47.460
|
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actually find that they fall into families these families share pocket
|
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48:47.460 --> 48:53.300
|
|
preferences which side chains bind into the HLA molecule so now that we know
|
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48:53.300 --> 48:56.700
|
|
that there are supertypes comprising families we can kind of narrow down the
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48:56.700 --> 49:00.980
|
|
search space to a manageable level and find patterns that actually give help us
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49:00.980 --> 49:05.500
|
|
figure out if something's going to be immunogenic or not so those are the nine
|
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49:05.500 --> 49:09.860
|
|
supertype families that we usually work with there are certain alleles that are
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49:09.860 --> 49:14.940
|
|
more common in certain populations but such as DR9 which is an Asian a couple
|
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49:14.940 --> 49:19.100
|
|
papers there I gotta read I guess however we find that if we include all of these
|
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49:19.180 --> 49:24.740
|
|
HLADR molecules in our search space we can get results that are representative
|
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49:24.740 --> 49:31.740
|
|
of 95% of the human populations worldwide that's the in silico approach of course
|
|
|
|
49:31.740 --> 49:36.380
|
|
how short these sequences are here that selection and try to get a lot and so
|
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49:36.380 --> 49:39.620
|
|
now what I want you to think about is the idea that if they wanted to make it
|
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49:39.620 --> 49:44.140
|
|
sure thing that they would say oh there's a coronavirus out there and it's got
|
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49:44.140 --> 49:48.820
|
|
this spike routine and they only needed to put in a couple of those just a
|
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49:48.820 --> 49:53.500
|
|
couple and then they would be guaranteed almost guaranteed to get the right
|
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49:53.500 --> 50:01.260
|
|
antibody response think about that think about how easy that that that trick
|
|
|
|
50:01.260 --> 50:05.940
|
|
would be to pull off given what we now know about the sequences and rule on the
|
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|
50:05.940 --> 50:14.340
|
|
sequence in Washington it would be a joke and so that's actually the kind of
|
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50:14.420 --> 50:19.860
|
|
deception that I was thinking had occurred in 2020 and then of course had
|
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|
50:19.860 --> 50:23.500
|
|
all kinds of different changes in terms of how I think about it now but it's
|
|
|
|
50:23.500 --> 50:27.980
|
|
still something to consider we don't know what happened this is a crime and we
|
|
|
|
50:27.980 --> 50:31.860
|
|
still don't know how far clones would spread if you made enough of them we
|
|
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|
50:31.860 --> 50:35.140
|
|
don't know how many people they would jump through I don't know would they
|
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|
50:35.140 --> 50:42.660
|
|
really stop with the first person that inhaled them I don't know so it's it's
|
|
|
|
50:42.700 --> 50:49.620
|
|
some really interesting immunology being sold here very carefully sold here
|
|
|
|
50:49.620 --> 50:55.820
|
|
mind you but you know it's exactly what you need to start thinking about as you
|
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|
50:55.820 --> 51:06.220
|
|
as you consider how the immune system works that somehow the way that she's
|
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|
51:06.300 --> 51:13.780
|
|
screening for immunogenic peptides seems to not jive with the idea that we can
|
|
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|
51:13.780 --> 51:18.740
|
|
just throw a a transfection in somebody and they'll express a protein in your
|
|
|
|
51:18.740 --> 51:24.020
|
|
immune system will be fine it doesn't really make sense from the perspective
|
|
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|
51:24.020 --> 51:30.900
|
|
of what she's saying because small contaminants or point mutations in a
|
|
|
|
51:30.900 --> 51:36.780
|
|
biologic can be a problem so when we know all the things we know now we have
|
|
|
|
51:36.780 --> 51:41.860
|
|
to really who the hell oh my goodness he doesn't even know I'm online Matthew
|
|
|
|
51:41.860 --> 51:47.300
|
|
Crawford is calling me on signal that is interesting I'm not gonna take that
|
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|
|
51:47.300 --> 51:53.140
|
|
call though thank you very much I'm gonna keep this going actually well I
|
|
|
|
51:53.140 --> 51:55.780
|
|
don't know I'm gonna speed it up because I don't know how much she's really gonna
|
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|
|
51:55.780 --> 52:00.780
|
|
do and I wanted to watch this other two-minute video of her where she's
|
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|
|
52:00.780 --> 52:03.820
|
|
talking a little more silly because she's on the nightly news and it's only a
|
|
|
|
52:03.820 --> 52:08.620
|
|
two-minute video so anyway I'll leave it like this I think it would go a little
|
|
|
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52:08.620 --> 52:11.060
|
|
faster.
|
|
|
|
52:11.060 --> 52:14.460
|
|
Located coverage of each HLA allele so probably 30 to 50 patients is really the
|
|
|
|
52:14.460 --> 52:19.140
|
|
ideal number of patients to be testing in an in vitro assay. Now screening peptide
|
|
|
|
52:19.140 --> 52:21.820
|
|
in silica we do look at it this way we basically parse it into nine we're
|
|
|
|
52:21.820 --> 52:24.660
|
|
overlapping frames and then we're gonna look at each overlapping frame for its
|
|
|
|
52:24.660 --> 52:28.020
|
|
predicted affinity to bind to specific HLA alleles here the nine super types
|
|
|
|
52:28.020 --> 52:31.180
|
|
that we've described. Notice in this picture that we see several nine
|
|
|
|
52:31.180 --> 52:35.220
|
|
reframes that bind promiscuously across HLA alleles and those are highlighted in
|
|
|
|
52:35.220 --> 52:37.660
|
|
yellow those are what we call epibars they're promiscuous T cell epitopes
|
|
|
|
52:37.660 --> 52:40.680
|
|
they're the primary drivers of an immune response and if we're making a
|
|
|
|
52:40.680 --> 52:43.260
|
|
vaccine those are great if they're in our peptide drug and they're foreign that's
|
|
|
|
52:43.260 --> 52:47.220
|
|
bad or or our impurity. They also give you the sense that the more T cell epitopes
|
|
|
|
52:47.220 --> 52:50.020
|
|
you pack into a single sequence whether they're for the same allele or other
|
|
|
|
52:50.020 --> 52:53.340
|
|
alleles in general higher epitope content is gonna drive a higher T cell
|
|
|
|
52:53.340 --> 52:55.820
|
|
response and that's what's we've observed in the literature as well as in
|
|
|
|
52:55.820 --> 52:58.820
|
|
our experience over the 20 years that we've been doing this. So we developed a
|
|
|
|
52:58.820 --> 53:01.140
|
|
ranking scale the ranking scale basically looks for the number of T cell
|
|
|
|
53:01.140 --> 53:05.220
|
|
epitopes per unit protein or peptide and we can look at how immunogenic a peptide
|
|
|
|
53:05.220 --> 53:10.020
|
|
might be for a population compared to others or for an individual. And as Mark
|
|
|
|
53:10.020 --> 53:14.540
|
|
said in the chat over ten years ago she came up with the idea of using
|
|
|
|
53:14.540 --> 53:21.220
|
|
Microsoft Word to look for these small epitopes in genetic sequences and the
|
|
|
|
53:21.220 --> 53:25.260
|
|
crazy thing is is that he found a video where she was talking to a
|
|
|
|
53:25.260 --> 53:29.980
|
|
newscaster and said well you know people started to contact us and asked us to
|
|
|
|
53:29.980 --> 53:33.820
|
|
analyze their protein sequence and at first we started with well how about a
|
|
|
|
53:33.820 --> 53:37.060
|
|
thousand dollars and they said fine so then we said how about five thousand
|
|
|
|
53:37.060 --> 53:39.580
|
|
dollars and then we were up to twenty thousand dollars and then we knew we
|
|
|
|
53:39.580 --> 53:46.940
|
|
really had a company for using Microsoft Word to search through their their
|
|
|
|
53:46.980 --> 53:53.020
|
|
genetic sequences to find T cell epitopes they had previously identified that's
|
|
|
|
53:53.020 --> 53:57.300
|
|
what we're dealing with here ladies and gentlemen this woman and people like
|
|
|
|
53:57.300 --> 54:02.100
|
|
her and that are looking to make products and looking to start companies
|
|
|
|
54:02.100 --> 54:07.300
|
|
and looking for things to from a business perspective catch on are very
|
|
|
|
54:07.300 --> 54:12.500
|
|
different than people are trying to save the world change the world or free
|
|
|
|
54:12.540 --> 54:18.740
|
|
humanity and so you have to see this for what it is you have to see Robert
|
|
|
|
54:18.740 --> 54:22.940
|
|
Malone for who he is you have to see Kevin McCurnan for who he is you have to
|
|
|
|
54:22.940 --> 54:29.300
|
|
see that these people have been swimming in this space for decades and they've
|
|
|
|
54:29.300 --> 54:34.820
|
|
been playing this game for decades the idea is to get a house on the harbor a
|
|
|
|
54:34.820 --> 54:40.340
|
|
seven thousand square foot house on the harbor the idea is to get really rich
|
|
|
|
54:40.340 --> 54:47.460
|
|
and to become famous the idea is to get the Bloomberg businessman award that's
|
|
|
|
54:47.460 --> 54:54.220
|
|
what they want that's the that's the kind of of prestige and fame and and
|
|
|
|
54:54.220 --> 55:00.420
|
|
and recognition that they want they aren't interested in giving they're not
|
|
|
|
55:00.420 --> 55:05.820
|
|
interested in teaching they're interested in making stuff that's worth stuff worth
|
|
|
|
55:05.900 --> 55:11.420
|
|
money and it is unfortunately a lot about money they measure it and their
|
|
|
|
55:11.420 --> 55:15.140
|
|
success based on money and that's what was so insightful about that interview
|
|
|
|
55:15.140 --> 55:21.300
|
|
from eight years ago with Annie is that it's she said it in such a way that it
|
|
|
|
55:21.300 --> 55:26.580
|
|
was almost like wow you're really an asshole like I went to this school and
|
|
|
|
55:26.580 --> 55:30.420
|
|
the school needed my help and so I said sure I can help you for a thousand
|
|
|
|
55:30.420 --> 55:33.780
|
|
dollars this week and they said great and so I was happy with that thousand
|
|
|
|
55:33.780 --> 55:39.460
|
|
dollars because a thousand dollars gets me through the week but then another
|
|
|
|
55:39.460 --> 55:44.820
|
|
school called me and I decided to say two thousand and they said fine and so I
|
|
|
|
55:44.820 --> 55:49.260
|
|
just did the job for two thousand and then when the next person called me I
|
|
|
|
55:49.260 --> 55:52.860
|
|
just scratched my eye wonder if they'll do it for five how about five thousand
|
|
|
|
55:52.860 --> 55:58.860
|
|
dollars and they said yes and suddenly I talked to my friend and I realized wow
|
|
|
|
55:58.860 --> 56:02.700
|
|
you know people will pay twenty thousand dollars for us to use Microsoft Word to
|
|
|
|
56:02.700 --> 56:07.980
|
|
search for nine letters in their protein sequence and we can charge five
|
|
|
|
56:07.980 --> 56:15.540
|
|
grand I wonder if we can charge twenty that's literally how this worked that's
|
|
|
|
56:15.540 --> 56:24.060
|
|
literally where epivacs came from it's no more complicated than that and yes it
|
|
|
|
56:24.060 --> 56:27.140
|
|
became more complicated of course because people threw millions of
|
|
|
|
56:27.140 --> 56:32.380
|
|
dollars at them the Bill Gates Foundation threw almost a million dollars at them
|
|
|
|
56:32.380 --> 56:39.300
|
|
many years ago already it's a really really interesting thing look now they
|
|
|
|
56:39.300 --> 56:45.260
|
|
have a pandemic sorry a peptide immunogenic scale it's kind of like the
|
|
|
|
56:45.260 --> 56:51.300
|
|
scoval rating of peppers I guess and here you go a 20 mer that's 20 amino
|
|
|
|
56:51.300 --> 56:58.860
|
|
acids theoretically minimum right and then all these guys have many many many
|
|
|
|
56:59.300 --> 57:06.580
|
|
potential T cell activating or HLA binding short sequences and so they're
|
|
|
|
57:06.580 --> 57:12.180
|
|
more immunogenic now if they if they have this idea already in their head for 10
|
|
|
|
57:12.180 --> 57:17.580
|
|
years then it's very easy to put the let's say where where where is where does
|
|
|
|
57:17.580 --> 57:24.620
|
|
the coronavirus spike protein fit in here not this one but the other ones it's
|
|
|
|
57:24.660 --> 57:29.660
|
|
not on here is it pretty convenient you see why we're this is exactly the story
|
|
|
|
57:29.660 --> 57:36.220
|
|
this is exactly where immunology should be where I expected it to be and now
|
|
|
|
57:36.220 --> 57:41.460
|
|
that we find it we have to understand why it's here what were these people doing
|
|
|
|
57:41.460 --> 57:47.100
|
|
before and after the pandemic and what does it mean going forward knowing that
|
|
|
|
57:47.100 --> 57:53.380
|
|
all of these Canadian companies were connected to American companies and
|
|
|
|
57:53.420 --> 58:00.300
|
|
connected to DARPA and a lot of these companies had a red thread of Robert
|
|
|
|
58:00.300 --> 58:07.940
|
|
Malone as an advisor it's just not possible for this to be random we have
|
|
|
|
58:07.940 --> 58:14.540
|
|
finally stumbled upon the joke the first generation of mRNA vaccines and the
|
|
|
|
58:14.540 --> 58:20.180
|
|
second generation of mRNA vaccines and that's probably been their long game
|
|
|
|
58:20.180 --> 58:24.900
|
|
plan all along whether or not Robert Malone was supposed to come out and
|
|
|
|
58:24.900 --> 58:29.180
|
|
and play shell games with everybody I don't really know but that's what that's
|
|
|
|
58:29.180 --> 58:35.460
|
|
where it had to go and to what extent we forced it to go there I don't know but
|
|
|
|
58:35.460 --> 58:41.380
|
|
we are definitely pushing the apple cart now we are definitely pushing the
|
|
|
|
58:41.380 --> 58:45.340
|
|
apple cart now we know genicity can be ranked here I'm analyzing the overall
|
|
|
|
58:45.340 --> 58:48.660
|
|
immunogenicity of generic peptide drugs compared to some well-known immunogenic
|
|
|
|
58:48.660 --> 58:51.260
|
|
peptides which are on the left-hand side of my scale from tennis talks and
|
|
|
|
58:51.260 --> 58:54.780
|
|
influenza EVV and you can see that the generic peptides which are generally
|
|
|
|
58:54.780 --> 58:58.300
|
|
derived from self peptides tend to be lower on that scale the scale is set to
|
|
|
|
58:58.300 --> 59:01.940
|
|
be zero for the average or median of a set of more than a hundred thousand
|
|
|
|
59:01.940 --> 59:04.860
|
|
random peptide sequences so you can see that there's a distribution things that
|
|
|
|
59:04.860 --> 59:08.180
|
|
are high on this scale could be expected to be more immunogenic than a random
|
|
|
|
59:08.180 --> 59:10.980
|
|
peptide by random chance and things that are lower on the scale are predicted to
|
|
|
|
59:10.980 --> 59:14.420
|
|
be less immunogenic than a random peptide found by random chance so okay
|
|
|
|
59:14.420 --> 59:18.180
|
|
maybe I'm just gonna stop this and I'm gonna look for the other video because I
|
|
|
|
59:18.460 --> 59:25.100
|
|
hold on let me just I'm gonna copy this because I think I watched it right
|
|
|
|
59:25.100 --> 59:34.420
|
|
before this video and so I should be able to go back here as efforts are
|
|
|
|
59:34.420 --> 59:37.260
|
|
underway worldwide trying find a way to stop this virus a local company is
|
|
|
|
59:37.260 --> 59:40.620
|
|
helping in the efforts working to create a vaccine okay hold on Logan
|
|
|
|
59:40.620 --> 59:45.740
|
|
Wilbur joins us now from Providence tonight with the story this is great so
|
|
|
|
59:45.740 --> 59:51.740
|
|
this is a an interview with her right at the start of the pandemic and now
|
|
|
|
59:51.740 --> 59:55.100
|
|
there's too much that goes on in this two minutes so I'm gonna have to stop it
|
|
|
|
59:55.100 --> 01:00:01.460
|
|
a lot but you're just not gonna believe it now you try your best and bring your
|
|
|
|
01:00:01.460 --> 01:00:09.140
|
|
most trained critical ears to this interview and bang on your own table
|
|
|
|
01:00:09.140 --> 01:00:15.180
|
|
every time you hear something you you simply can't believe she says from the
|
|
|
|
01:00:15.180 --> 01:00:19.020
|
|
outside this brick building in Onlyville may not look like much but people
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01:00:19.020 --> 01:00:24.100
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inside are working to find a possible solution to the coronavirus
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01:00:24.100 --> 01:00:29.540
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Providence based epivacs is working on two coronavirus vaccines with one focus
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01:00:29.540 --> 01:00:33.420
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on protecting health care workers they're the first line of defense against the
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01:00:33.420 --> 01:00:37.540
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virus and we want to give them something that will actually generate what we
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01:00:37.540 --> 01:00:41.660
|
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would call immune system body armor will give them a protection we asked Dr.
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01:00:41.660 --> 01:00:46.100
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Andy Groot to explain how vaccines work using a virus most people are
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01:00:46.100 --> 01:00:50.900
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familiar with the flu you have pre-existing immunity that allows your
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01:00:50.900 --> 01:00:55.980
|
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immune systems to go oh I see flu here I see a word that says flu I'm gonna help
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01:00:55.980 --> 01:01:00.020
|
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my immune system respond and make a lot of antibody which is exactly what the
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01:01:00.020 --> 01:01:05.100
|
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epivacs vaccine does it generates that immune memory you need that immune
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01:01:05.100 --> 01:01:08.620
|
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memory in order to generate an effective immune response currently without a
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01:01:08.620 --> 01:01:13.540
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vaccine Dr. DeGroot calls the coronavirus very dangerous this virus is
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01:01:13.540 --> 01:01:23.140
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killing somewhere between two to four people per 100 two to four people per
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01:01:23.140 --> 01:01:32.540
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100 three to four percent are dying of this virus is that not exactly the worst
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01:01:32.540 --> 01:01:38.540
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case scenario is that not exactly the bullshit that we're trying to fight
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01:01:38.540 --> 01:01:44.540
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right now it's not it was the protocols it was then do not resuscitate orders
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01:01:44.540 --> 01:01:50.020
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and she's a hundred percent on narrative it's killing between three and four
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01:01:50.020 --> 01:01:55.140
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people out of every 100 and no everyone is vulnerable listen that's very
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01:01:55.140 --> 01:02:01.620
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different from influenza where it's it's 10 to 50 fold higher so while there is a
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01:02:01.620 --> 01:02:05.860
|
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comparison to the flu as to why vaccines are important to solving this pandemic
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01:02:05.860 --> 01:02:10.300
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as the mortality rate shows the two are not alike I think there's a tendency to
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01:02:10.300 --> 01:02:15.380
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kind of not take this seriously and that's because people have said it's like
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01:02:15.380 --> 01:02:19.420
|
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the flu so we you know maybe we're somewhat immune to the flu but in
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01:02:19.420 --> 01:02:24.020
|
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actuality it's not like flu in that way we need to build the immunity through
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01:02:24.020 --> 01:02:33.060
|
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vaccines and vaccines are extremely important Wow I mean wow that's just
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01:02:33.060 --> 01:02:39.780
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complete hogwash it is nonsense it's ridiculous but she's saying it and it's
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01:02:39.780 --> 01:02:45.300
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not it's not unusual you just have to understand that as we look backwards and
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01:02:45.300 --> 01:02:51.620
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we actually take stock of what was happening at this time in 2020 it's
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01:02:51.620 --> 01:02:57.060
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going to become more and more painfully obvious that some of these people she's
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01:02:57.060 --> 01:03:01.460
|
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smiling in this damn interview the whole time because she's excited about the
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01:03:01.540 --> 01:03:06.380
|
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possibility that she's about to make a billion dollars there's a possibility
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01:03:06.380 --> 01:03:11.980
|
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that she still will make a billion dollars with the next one they're all
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01:03:11.980 --> 01:03:16.300
|
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excited about the possibility that they're going to go from zero to a billion in
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01:03:16.300 --> 01:03:25.020
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a year it's exactly what the video of the absolera CEO was titled you don't
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01:03:25.020 --> 01:03:30.140
|
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think all these people start dreaming about that the moment that it becomes
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01:03:30.140 --> 01:03:34.780
|
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possible the moment that somebody whispers in their ear this might be an
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01:03:34.780 --> 01:03:44.140
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IPO you don't think that happens I'm sure it does and I'm sure that this woman
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01:03:44.140 --> 01:03:49.060
|
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has been trying to get a hold of one of those hot air balloons for some time
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01:03:49.060 --> 01:03:54.340
|
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venture capital hot air balloon I mean I'd be happy to have someone invest a
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01:03:54.340 --> 01:04:00.460
|
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million dollars in gigo and biological to make sure that all of this you know
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01:04:00.460 --> 01:04:09.140
|
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live up-to-date coverage of pandemic mythology continues and I'm sure I would
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01:04:09.140 --> 01:04:15.940
|
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accept it greatly but it's not the reason why I'm doing it it's not the
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01:04:15.940 --> 01:04:21.460
|
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actual goal which is the actual goal of a company like this and was the actual
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01:04:21.500 --> 01:04:25.580
|
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goal of her spin-out company and the exact goal of all of these companies is
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01:04:25.580 --> 01:04:31.780
|
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to eventually go public and become worth five billion dollars that's the dream
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01:04:31.780 --> 01:04:41.100
|
|
of every biologist at their bench or at least the ones that think like her
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01:04:41.100 --> 01:04:45.340
|
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you're not thinking about saving the world you're not thinking about making a
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01:04:45.340 --> 01:04:50.980
|
|
therapeutic that everybody can afford you're thinking about making yourself
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01:04:50.980 --> 01:04:57.580
|
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rich and famous and Dr. DeGroote tells me we could see a vaccine and as
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01:04:57.580 --> 01:05:02.100
|
|
little as five to six months but that all depends on funding she says she's
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01:05:02.100 --> 01:05:05.580
|
|
going to ask the federal government to help with that more than three hundred
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01:05:05.580 --> 01:05:10.340
|
|
million dollars needed to ensure both the safety and efficiency of the vaccine
|
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01:05:10.340 --> 01:05:15.660
|
|
in Providence Logan Wilbur Eyewitness News she's gonna ask for three million
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01:05:15.660 --> 01:05:24.380
|
|
dollars holy shit three hundred million dollars holy cow excuse me they do have
|
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01:05:24.380 --> 01:05:30.020
|
|
the identical T-cell receptor-facing residues and bind to the same HLA the
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01:05:30.020 --> 01:05:34.140
|
|
T-cell probably wouldn't be able to differentiate between that human GPI
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01:05:34.140 --> 01:05:37.140
|
|
I'm gonna go back here and speed it up they can actually they can go up so if
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01:05:37.140 --> 01:05:40.460
|
|
they're in the red zone we would be concerned if they're in the green zone
|
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01:05:40.460 --> 01:05:44.100
|
|
we probably wouldn't even do a T-cell assay or an in vitro binding assay because
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01:05:44.100 --> 01:05:48.260
|
|
we would imagine that peptide would be very low risk so furthermore we have
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01:05:48.260 --> 01:05:51.020
|
|
other tools that allow us to screen for those happy bars of customers one such
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01:05:51.020 --> 01:05:55.140
|
|
tool that finds regions of high epitope density in a protein or peptide sequence
|
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01:05:55.140 --> 01:05:57.940
|
|
it's very important to find these okay now make sure that you understand what
|
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|
|
01:05:57.940 --> 01:06:03.540
|
|
we're watching here she is assembling a software stack so there was a software
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01:06:03.540 --> 01:06:07.860
|
|
that she was using earlier and now that was called panda or something like that
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|
01:06:07.860 --> 01:06:13.980
|
|
now there's customer and you cannot underestimate how this is the business
|
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01:06:13.980 --> 01:06:19.820
|
|
model it is very very similar to abcellular which is basically a stack of
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01:06:19.820 --> 01:06:27.900
|
|
IA machine learning programs which can use the data that's gathered in their
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01:06:27.900 --> 01:06:32.500
|
|
single-cell machines to do what it is they say they're doing which is
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01:06:32.500 --> 01:06:35.980
|
|
identifying antibodies that are important and finding the B cells that
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01:06:35.980 --> 01:06:42.140
|
|
are producing in them this is this is the same kind of screening it's screening
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01:06:42.140 --> 01:06:46.540
|
|
the genetic sequence and they're they they're doing the same thing with
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01:06:46.540 --> 01:06:55.340
|
|
antibodies it's a sequence and and they're using software to do it and so they
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01:06:55.340 --> 01:07:02.860
|
|
make this patented software stack through which your biologic gets washed and
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|
|
01:07:02.860 --> 01:07:09.460
|
|
what comes out is a patentable biologic because you washed it through this
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|
01:07:09.460 --> 01:07:17.180
|
|
software stack and I think that that there are people who are right when they
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|
01:07:17.180 --> 01:07:20.500
|
|
say that they hope that the mRNA would go better I think there are people that
|
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|
|
01:07:20.500 --> 01:07:25.180
|
|
there were probably people that didn't think that it would go as bad as it has
|
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|
01:07:25.180 --> 01:07:31.820
|
|
both from the perspective of coverage and the side effects I actually think
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|
01:07:31.820 --> 01:07:36.500
|
|
they thought it would go better and I think Mark is also on this page at this
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|
01:07:36.500 --> 01:07:40.380
|
|
stage where he thinks that sort of the cancers and all this other stuff it
|
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|
|
01:07:40.380 --> 01:07:45.260
|
|
doesn't seem like very many people were anticipating this one of the ways that
|
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|
01:07:45.260 --> 01:07:51.020
|
|
Mark has shown me of looking at this is going to the stock prices of cancer
|
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|
|
01:07:51.020 --> 01:07:56.300
|
|
companies and you can see that they didn't rise ahead of this they certainly
|
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|
|
01:07:56.300 --> 01:08:01.540
|
|
didn't rise before the pandemic like some other companies did and so it's
|
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|
|
01:08:01.620 --> 01:08:08.260
|
|
possible that we are so off-script right now that we have a chance to actually
|
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|
|
01:08:08.260 --> 01:08:13.620
|
|
change the direction of the cruise ship it's possible and I think that if you
|
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|
|
01:08:13.620 --> 01:08:18.780
|
|
listen to this session where she talks so confidently about this technology and
|
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|
|
01:08:18.780 --> 01:08:23.100
|
|
then we realize that this technology didn't even make it it didn't even make
|
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|
|
01:08:23.100 --> 01:08:29.020
|
|
it to production what does that mean does that mean it's still waiting does
|
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|
|
01:08:29.060 --> 01:08:33.500
|
|
that mean this is gonna be the next generation and if we think about the
|
|
|
|
01:08:33.500 --> 01:08:36.620
|
|
fact that a lot of these companies are all united by an interaction with
|
|
|
|
01:08:36.620 --> 01:08:42.220
|
|
Robert Malone and Robert Malone came out and controlled the narrative about how
|
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|
|
01:08:42.220 --> 01:08:48.580
|
|
the mRNA vaccine was successful or not or who was successful for you can start
|
|
|
|
01:08:48.580 --> 01:08:53.780
|
|
to see a scenario here I think you can start to see a scenario here where you
|
|
|
|
01:08:53.780 --> 01:09:00.980
|
|
can understand what these people are clowning about now there are a couple
|
|
|
|
01:09:00.980 --> 01:09:05.100
|
|
other pieces to this puzzle one is that I've heard Robert Malone state several
|
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|
|
01:09:05.100 --> 01:09:10.700
|
|
times that him and his wife have a patent on mucosal and inhaled vaccine
|
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|
|
01:09:10.700 --> 01:09:17.220
|
|
vaccines and all technologies that do that if that's a possibility then I
|
|
|
|
01:09:17.220 --> 01:09:23.140
|
|
assure you this company having its long ties with Robert Malone will
|
|
|
|
01:09:23.140 --> 01:09:30.580
|
|
certainly be on this shortlist as we'll probably absolera and maybe a cutis or
|
|
|
|
01:09:30.580 --> 01:09:35.980
|
|
whoever else is that that he has ongoing relationships with but it's it's really
|
|
|
|
01:09:35.980 --> 01:09:45.740
|
|
hard not to see a scenario where the wrong question has been asked for several
|
|
|
|
01:09:45.740 --> 01:09:52.100
|
|
years now wrong question that has been propelled by George Webb and Veritas and
|
|
|
|
01:09:52.100 --> 01:09:59.020
|
|
Robert Malone it is a it is a wrong question about who is Boston
|
|
|
|
01:09:59.020 --> 01:10:04.620
|
|
consulting and what happened in this video and the fact that Robert Malone
|
|
|
|
01:10:04.620 --> 01:10:12.020
|
|
promoted that video and the fancy org chart of George Webb is exactly that
|
|
|
|
01:10:12.020 --> 01:10:19.820
|
|
video with exactly Jordan Walker and so we're all distracted by Boston
|
|
|
|
01:10:19.820 --> 01:10:26.700
|
|
consulting group and Pfizer and we really have never seen any of the
|
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|
|
01:10:26.700 --> 01:10:31.660
|
|
companies that Robert Malone is actually working for and consulting with except
|
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|
|
01:10:31.660 --> 01:10:38.060
|
|
for on Mark Street and we've never known really how they're connected until we
|
|
|
|
01:10:38.060 --> 01:10:43.500
|
|
watch this video with Colis and he revealed all the things that he revealed
|
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|
|
01:10:43.820 --> 01:10:51.540
|
|
and that Mark kind of got pushed in just the right direction where he where he
|
|
|
|
01:10:51.540 --> 01:10:57.340
|
|
found what he we needed to find to really see that absolera is the the trick
|
|
|
|
01:10:57.340 --> 01:11:06.660
|
|
Peter Teal is there the antibody paradox anybody patent paradox is there and so
|
|
|
|
01:11:06.660 --> 01:11:10.260
|
|
now we need to really understand what the real immunology is going forward and I
|
|
|
|
01:11:10.300 --> 01:11:14.820
|
|
believe that although this company has been in the background for a long time
|
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|
|
01:11:14.820 --> 01:11:20.380
|
|
and not really doesn't seem taken very seriously I actually have always believed
|
|
|
|
01:11:20.380 --> 01:11:24.500
|
|
you hear a lot of people talk about this the T cells are the cells that we
|
|
|
|
01:11:24.500 --> 01:11:32.220
|
|
should be targeting and we who were trying to actually augment and so at least in
|
|
|
|
01:11:32.220 --> 01:11:36.820
|
|
principle this company is thinking the right way and so I think has potential
|
|
|
|
01:11:36.820 --> 01:11:42.740
|
|
to be the part of the next generation of mRNA therapeutics which I assure you
|
|
|
|
01:11:42.740 --> 01:11:48.100
|
|
are coming they have no I have no doubt in my mind that that's the plan that
|
|
|
|
01:11:48.100 --> 01:11:53.980
|
|
that even if it becomes common knowledge that some of the batches of of the
|
|
|
|
01:11:53.980 --> 01:12:00.260
|
|
mRNA were contaminated it's not going to be enough to penetrate the the psyche of
|
|
|
|
01:12:00.260 --> 01:12:04.300
|
|
the average skilled TV watcher for them to understand that newer
|
|
|
|
01:12:04.380 --> 01:12:10.700
|
|
transfections or newer versions of this kind of of therapeutic are going to be
|
|
|
|
01:12:10.700 --> 01:12:14.620
|
|
just as dangerous they're going to think that the next generation is better just
|
|
|
|
01:12:14.620 --> 01:12:18.820
|
|
like Robert Malone says that he took the mRNA shot because he assumed they
|
|
|
|
01:12:18.820 --> 01:12:24.940
|
|
solved the trafficking problem or the targeting problem and of course yesterday
|
|
|
|
01:12:24.940 --> 01:12:29.140
|
|
we heard from or day before we heard from Peter Cullis that they haven't they
|
|
|
|
01:12:29.140 --> 01:12:32.500
|
|
tried for 40 years to solve the trafficking problem and they've never done
|
|
|
|
01:12:32.500 --> 01:12:39.780
|
|
it he burnt five postdocs on it we have been lied to thoroughly and now we're
|
|
|
|
01:12:39.780 --> 01:12:44.180
|
|
just getting to the point where we can start to see why I think and it's again
|
|
|
|
01:12:44.180 --> 01:12:50.820
|
|
it is exactly as Mark has said it the best the job of these people is only to
|
|
|
|
01:12:50.820 --> 01:12:55.180
|
|
make sure that you're asking the wrong question it doesn't even matter what
|
|
|
|
01:12:55.180 --> 01:13:01.700
|
|
question it is ask a question about bioweapons fine you're lost ask a question
|
|
|
|
01:13:01.700 --> 01:13:06.380
|
|
about amyloidosis and prion disease okay you're not on the story ask a
|
|
|
|
01:13:06.380 --> 01:13:13.020
|
|
question about hydroxychloroquine or Ivermectin and their effectiveness okay
|
|
|
|
01:13:13.020 --> 01:13:19.580
|
|
you're not on the story and so as long as you keep fighting about all these
|
|
|
|
01:13:19.580 --> 01:13:26.180
|
|
nonsense things and you keep chasing down all this nonsense biology he won't
|
|
|
|
01:13:26.180 --> 01:13:30.740
|
|
ever actually see the breadth and the depth of which you can you can see
|
|
|
|
01:13:30.740 --> 01:13:34.220
|
|
right through them they're just right here they tell you the truth over and
|
|
|
|
01:13:34.220 --> 01:13:40.540
|
|
over again they believe in things that don't work they believe in technology
|
|
|
|
01:13:40.540 --> 01:13:46.300
|
|
with a little bit of hand waving they believe in the future of the technologies
|
|
|
|
01:13:46.300 --> 01:13:51.860
|
|
that they're working on now and they believe lies are justified because they're
|
|
|
|
01:13:51.860 --> 01:13:55.740
|
|
getting rich because you can lie in business there's nothing wrong with
|
|
|
|
01:13:55.740 --> 01:14:00.300
|
|
lying in business to get rich it's all spare in love and war and business I
|
|
|
|
01:14:00.300 --> 01:14:07.340
|
|
guess so they have to sell this as the best technology it's their technology
|
|
|
|
01:14:07.340 --> 01:14:15.860
|
|
but they're revealing in my mind how again shallow their understanding of the
|
|
|
|
01:14:15.860 --> 01:14:20.700
|
|
immune response is in shallow in terms of their outlook on how to augment it
|
|
|
|
01:14:20.700 --> 01:14:24.300
|
|
they're really still just looking for antibody responses again those are the
|
|
|
|
01:14:24.300 --> 01:14:28.580
|
|
immunodominant signals in outbred populations here's an example this is a
|
|
|
|
01:14:28.580 --> 01:14:31.900
|
|
peptide that is found in GAD 65 it has an epi bar and it's a well-known
|
|
|
|
01:14:31.900 --> 01:14:36.140
|
|
autoimmune disease epitope found in patients who have type 1 diabetes now
|
|
|
|
01:14:36.140 --> 01:14:39.180
|
|
what happens when we have an impurity that contains a natural or artificial
|
|
|
|
01:14:39.180 --> 01:14:43.020
|
|
amino acid and what we do there is we basically use a best proxy approach we
|
|
|
|
01:14:43.020 --> 01:14:45.700
|
|
take three steps we replace with a neutral placeholder just to kind of see
|
|
|
|
01:14:45.700 --> 01:14:48.940
|
|
what the potential for immunogenicity is in that peptide on its own without the
|
|
|
|
01:14:48.940 --> 01:14:52.020
|
|
unnatural amino acid then we do a replacement analysis with all 20
|
|
|
|
01:14:52.020 --> 01:14:55.980
|
|
natural amino acids and look at the best case sorry the best case low immunogenicity
|
|
|
|
01:14:55.980 --> 01:15:00.220
|
|
or worst case high immunogenicity amino acid replacement that gives us a
|
|
|
|
01:15:00.220 --> 01:15:03.540
|
|
range and that tells us how immunogenic could this peptide be in the worst case
|
|
|
|
01:15:03.540 --> 01:15:07.300
|
|
scenario if that third position was replaced by a peptide that found
|
|
|
|
01:15:07.300 --> 01:15:10.100
|
|
promiscuously across all each allele so that tells you the worst case scenario
|
|
|
|
01:15:10.100 --> 01:15:13.620
|
|
since you don't or can't predict in silica what the unnatural would actually
|
|
|
|
01:15:13.620 --> 01:15:16.540
|
|
do the third thing we do is we pick a proxy and in this case for this peptide
|
|
|
|
01:15:16.540 --> 01:15:20.140
|
|
we actually picked the tryptophan proxy which allowed us to make an
|
|
|
|
01:15:20.140 --> 01:15:23.740
|
|
insilico prediction for an unnatural that was not a tryptophan so that's what we
|
|
|
|
01:15:23.780 --> 01:15:27.020
|
|
do in silico for un-naturals now once we've identified the potential immunogenicity
|
|
|
|
01:15:27.020 --> 01:15:31.140
|
|
of our API and our impurities we also want to evaluate if those APIs or
|
|
|
|
01:15:31.140 --> 01:15:35.020
|
|
impurities have the potential to induce tolerance in in vitro and in vivo how
|
|
|
|
01:15:35.020 --> 01:15:38.260
|
|
do peptides induce tolerance they engage t-reg cells that suppress immune
|
|
|
|
01:15:38.260 --> 01:15:41.940
|
|
response it turns out that the peptides that trigger t-regs bind to HLA
|
|
|
|
01:15:41.940 --> 01:15:45.380
|
|
molecules similarly to peptides that trigger a t-effector immune response so
|
|
|
|
01:15:45.380 --> 01:15:49.060
|
|
you can't differentiate them by their HLA binding group files you can as we
|
|
|
|
01:15:49.060 --> 01:15:52.460
|
|
discovered however determine if a peptide might be a t-reg epitope by
|
|
|
|
01:15:52.500 --> 01:15:55.700
|
|
looking at its T cell receptor facing surface and so we actually use a tool
|
|
|
|
01:15:55.700 --> 01:15:58.820
|
|
called Janus matrix to do that let me explain further here what I'm showing
|
|
|
|
01:15:58.820 --> 01:16:02.580
|
|
is the peptide from your another software to purity binding the binding
|
|
|
|
01:16:02.580 --> 01:16:05.540
|
|
group the agritobus facing down the abitopus facing up to the T cell
|
|
|
|
01:16:05.540 --> 01:16:08.780
|
|
receptor and what we're doing with this Janus matrix tool is basically dividing
|
|
|
|
01:16:08.780 --> 01:16:11.540
|
|
the peptide into two different components the amino acids that bind to
|
|
|
|
01:16:11.540 --> 01:16:15.180
|
|
the HLA and the amino acids that bond that face up to the T cell receptor you
|
|
|
|
01:16:15.180 --> 01:16:18.020
|
|
can imagine when the T cell receptor comes down on top of that peptide that is
|
|
|
|
01:16:18.020 --> 01:16:20.900
|
|
really only seeing the amino acid side chains that face up it can't see the
|
|
|
|
01:16:20.940 --> 01:16:24.740
|
|
ones that are bound down into the HLA binding group so we could actually take
|
|
|
|
01:16:24.740 --> 01:16:28.660
|
|
those amino acids and look in the human genome for other peptides it may not be
|
|
|
|
01:16:28.660 --> 01:16:32.260
|
|
identical in sequence that do have the identical T cell receptor facing
|
|
|
|
01:16:32.260 --> 01:16:35.460
|
|
residues and bind to the same HLA the T cell probably wouldn't be able to
|
|
|
|
01:16:35.460 --> 01:16:38.780
|
|
differentiate between that human genome peptide and say the impurity peptide
|
|
|
|
01:16:38.780 --> 01:16:41.460
|
|
that we're showing it in an HLA molecule as long as the HLA molecule is
|
|
|
|
01:16:41.460 --> 01:16:44.700
|
|
the same and the T cell receptor facing residues are the same that's the
|
|
|
|
01:16:44.700 --> 01:16:47.940
|
|
hypothesis turns out that when we do have extensive cross conservation at the TCR
|
|
|
|
01:16:47.940 --> 01:16:51.340
|
|
phase that we're able to show that those peptides which have say this peptide
|
|
|
|
01:16:51.340 --> 01:16:55.540
|
|
which is an IMER has six different peptides to which it can be related in
|
|
|
|
01:16:55.540 --> 01:16:58.300
|
|
the human genome by conservation of the TCR phase and restriction by the same
|
|
|
|
01:16:58.300 --> 01:17:01.780
|
|
HLA allele that peptide is going to either be tolerated because we've been
|
|
|
|
01:17:01.780 --> 01:17:05.340
|
|
trained to tolerate it we've seen that peptide before in our own genome or it
|
|
|
|
01:17:05.340 --> 01:17:08.140
|
|
will be actively regulatory and that's what's really interesting about some of
|
|
|
|
01:17:08.140 --> 01:17:12.860
|
|
the peptides that we're dealing with as generic peptides today so what she
|
|
|
|
01:17:12.860 --> 01:17:17.900
|
|
seems to imply here is that if it if a peptide sequence has a high homology
|
|
|
|
01:17:17.900 --> 01:17:23.540
|
|
with self proteins it will tend to be a T regulatory epitope and if it has an
|
|
|
|
01:17:23.540 --> 01:17:29.060
|
|
a foreign one then it will tend to be a a immunogenic epitope which is
|
|
|
|
01:17:29.060 --> 01:17:35.460
|
|
interesting because in another talk of hers you can hear her say very plainly
|
|
|
|
01:17:35.460 --> 01:17:41.660
|
|
that coronaviruses and RNA viruses have adopted a tremendous amount of
|
|
|
|
01:17:41.660 --> 01:17:51.340
|
|
homology between human proteins to avoid detection to cause tolerance which is
|
|
|
|
01:17:51.340 --> 01:17:55.980
|
|
exactly what I've said from the very beginning is essentially the response to
|
|
|
|
01:17:55.980 --> 01:18:02.020
|
|
a coronavirus RNA if they exist as they are portrayed in cartoons our bodies
|
|
|
|
01:18:02.020 --> 01:18:09.380
|
|
have learned to respond to these over millennia with a lack of immune response
|
|
|
|
01:18:09.460 --> 01:18:17.300
|
|
and a lack of inflammation and so one of the reasons why the common cold is in
|
|
|
|
01:18:17.300 --> 01:18:20.380
|
|
particularly dangerous except for in people who are already dying is that
|
|
|
|
01:18:20.380 --> 01:18:26.700
|
|
reason because our immune system isn't really triggered by them and one of the
|
|
|
|
01:18:26.700 --> 01:18:30.980
|
|
reasons may be what she has explained in one of her many lectures is that a lot
|
|
|
|
01:18:30.980 --> 01:18:36.700
|
|
of the coronavirus proteins are homologous through large stretches with
|
|
|
|
01:18:36.700 --> 01:18:42.220
|
|
human proteins which could be mimicry or it could be a sign that they're just
|
|
|
|
01:18:42.220 --> 01:18:46.940
|
|
exosomes right I mean this is part of what's so frustrating about this this
|
|
|
|
01:18:46.940 --> 01:18:54.620
|
|
idea is that all of these people when they talk they are discussing their ideas in
|
|
|
|
01:18:54.620 --> 01:18:58.700
|
|
the context of this bad biology and this bad understanding of of the immune
|
|
|
|
01:18:58.700 --> 01:19:03.820
|
|
system and so it's hard to talk around them in some ways because they're limited
|
|
|
|
01:19:03.820 --> 01:19:08.420
|
|
by this this huge assumption that you know there's just a few knobs in the
|
|
|
|
01:19:08.420 --> 01:19:14.340
|
|
immune system to tweak and one goes up and one goes down and it's it's like
|
|
|
|
01:19:14.340 --> 01:19:20.220
|
|
that but it's not it's not as simple as you know symbols in the band and symbols
|
|
|
|
01:19:20.220 --> 01:19:23.740
|
|
not in the band it's not like that other aspects of that peptide might bind
|
|
|
|
01:19:23.740 --> 01:19:26.920
|
|
similarly to an MHC molecule or HLA molecule but would have no cross
|
|
|
|
01:19:26.920 --> 01:19:29.660
|
|
conservation in the human genome and those could potentially be immunogenic
|
|
|
|
01:19:29.660 --> 01:19:32.980
|
|
now let's just pretend this API is now has a modification and it is an
|
|
|
|
01:19:32.980 --> 01:19:36.180
|
|
impurity this part of the impurity that binds to a specific HLA allele could
|
|
|
|
01:19:36.180 --> 01:19:40.140
|
|
actually be tolerogenic this part of the impurity could actually bind to a MHC or
|
|
|
|
01:19:40.140 --> 01:19:44.020
|
|
HLA alleles and drive an unexpected and unwanted immune response so that's why we
|
|
|
|
01:19:44.020 --> 01:19:47.260
|
|
do this analysis with the Janus matrix tool the method is published it's in the
|
|
|
|
01:19:47.260 --> 01:19:49.940
|
|
literature and there are actually quite a few papers which I'm showing you here
|
|
|
|
01:19:49.940 --> 01:19:53.100
|
|
and I invite you to look at later what's an example of a T-reg epitope that is
|
|
|
|
01:19:53.100 --> 01:19:56.100
|
|
confirmed with Janus matrix one is found in immunoglobulin actually there are
|
|
|
|
01:19:56.100 --> 01:19:59.820
|
|
six to eight to ten that are found in immunoglobulin G and these are promiscuous
|
|
|
|
01:19:59.820 --> 01:20:02.580
|
|
T cell epitopes that are highly cross conserved not only in immunoglobulin G
|
|
|
|
01:20:02.580 --> 01:20:06.820
|
|
but across a whole set of other human genome peptides they are tolerogenic they
|
|
|
|
01:20:06.820 --> 01:20:11.420
|
|
do induce T-regs in vitro and they induce adaptive tolerance to other parts of
|
|
|
|
01:20:11.420 --> 01:20:14.900
|
|
proteins that contain them so T-regitopes are an interesting discovery that we can
|
|
|
|
01:20:14.900 --> 01:20:18.260
|
|
make with the Janus matrix tool and when we're looking at contain them so T-regics
|
|
|
|
01:20:18.260 --> 01:20:21.940
|
|
in vitro and they induce adaptive talk I'm not really sure how this works she's
|
|
|
|
01:20:21.940 --> 01:20:29.260
|
|
saying IgG this is a antibody year and I'm not really sure how this arrow works
|
|
|
|
01:20:29.260 --> 01:20:35.660
|
|
with regard to now that antigen presenting cell is gonna present a
|
|
|
|
01:20:35.660 --> 01:20:38.580
|
|
portion of the antibody this is something that I have never heard of
|
|
|
|
01:20:38.580 --> 01:20:43.140
|
|
before so I guess I'm gonna have to read some of those papers I might need to
|
|
|
|
01:20:43.140 --> 01:20:48.660
|
|
catch up on this this is a this is a new thing for me but it's interesting to
|
|
|
|
01:20:48.660 --> 01:20:55.780
|
|
think that the T-regulatory cell epitope might be on IgG antibodies I don't know
|
|
|
|
01:20:55.780 --> 01:20:59.540
|
|
what I have to draw pictures I'm not gonna be able to follow this anymore I
|
|
|
|
01:20:59.540 --> 01:21:03.340
|
|
don't think but I'm gonna listen to it but I'm gonna get lost to other parts
|
|
|
|
01:21:03.340 --> 01:21:06.540
|
|
of proteins that contain them so T-regitopes are an interesting discovery
|
|
|
|
01:21:06.540 --> 01:21:09.420
|
|
that we can make with the Janus matrix tool now when we're looking at peptides
|
|
|
|
01:21:09.420 --> 01:21:12.380
|
|
and their impurities we're gonna try to assess their risk by looking at these
|
|
|
|
01:21:12.380 --> 01:21:16.300
|
|
two aspects of the peptide itself let's look at for example on the y-axis how
|
|
|
|
01:21:16.300 --> 01:21:19.660
|
|
many T-cell epitopes per unit length that peptide or impurity might have you
|
|
|
|
01:21:19.660 --> 01:21:22.820
|
|
could have epitode dense peptides or epitopes sparse peptides and then let's
|
|
|
|
01:21:22.820 --> 01:21:26.020
|
|
look at the humanists of that peptide you could have peptides that are more
|
|
|
|
01:21:26.020 --> 01:21:29.220
|
|
that are have TCR faces that are more common in human proteins and peptides
|
|
|
|
01:21:29.220 --> 01:21:32.780
|
|
that have that look less human and so you can obviously divide peptides and
|
|
|
|
01:21:32.780 --> 01:21:35.300
|
|
their impurities into four different quadrants with the least immunogenic
|
|
|
|
01:21:35.300 --> 01:21:37.580
|
|
potential down here and the most immunogenic potential up there where
|
|
|
|
01:21:37.580 --> 01:21:41.060
|
|
there are more T-cell epitopes less human so what do our generic peptides look
|
|
|
|
01:21:41.060 --> 01:21:43.780
|
|
like and what do their impurities look like well let's just take the two peptides
|
|
|
|
01:21:43.780 --> 01:21:47.060
|
|
that we worked on with the FDA in the context of our contract here you can see
|
|
|
|
01:21:47.060 --> 01:21:53.020
|
|
on this quadrant analysis all of that so she's working on FDA approved
|
|
|
|
01:21:53.020 --> 01:21:59.020
|
|
biologics which have known impurities in them and she's trying to explain whether
|
|
|
|
01:21:59.020 --> 01:22:05.060
|
|
the impurities are generating the unwanted immune responses or the peptide
|
|
|
|
01:22:05.060 --> 01:22:13.660
|
|
itself and so she's analyzed peptides for the FDA this is like right years
|
|
|
|
01:22:13.660 --> 01:22:17.820
|
|
years later after she had that interview which I described where she
|
|
|
|
01:22:17.820 --> 01:22:21.380
|
|
said well we charged him a thousand and they paid it and the next people had
|
|
|
|
01:22:21.380 --> 01:22:25.180
|
|
called we said five and they paid it and the next people called we said 20 and
|
|
|
|
01:22:25.180 --> 01:22:31.860
|
|
they paid it so we knew we had a company and so what you see here is epi matrix
|
|
|
|
01:22:31.860 --> 01:22:38.540
|
|
and Janice matrix supposedly probably just two software programs that are
|
|
|
|
01:22:38.620 --> 01:22:46.860
|
|
going to be patented and that makes the results of this patentable or trade
|
|
|
|
01:22:46.860 --> 01:22:50.340
|
|
markable or something I'm sure
|
|
|
|
01:22:51.300 --> 01:22:55.580
|
|
generic peptides that are of interest in the market right now and you can see
|
|
|
|
01:22:55.580 --> 01:22:59.020
|
|
that a lot of them fall in this low epitope density but not necessarily very
|
|
|
|
01:22:59.020 --> 01:23:02.740
|
|
human quadrant which suggests that there is potential for some immunogenicity but
|
|
|
|
01:23:02.740 --> 01:23:05.260
|
|
there are two that fall in other quadrants tear peritide falls in the
|
|
|
|
01:23:05.260 --> 01:23:07.320
|
|
epitope dense but highly human so potentially taller
|
|
|
|
01:23:07.320 --> 01:23:11.160
|
|
genetic quadrant and the serotide is epitope sparse and highly human so
|
|
|
|
01:23:11.160 --> 01:23:14.000
|
|
probably not a problem as an API and what about their impurities you can
|
|
|
|
01:23:14.000 --> 01:23:16.800
|
|
actually see on this quadrant graph that the tear peritide impurities that we
|
|
|
|
01:23:16.800 --> 01:23:20.280
|
|
worked on with FDA really travel around the parent drug small modifications
|
|
|
|
01:23:20.280 --> 01:23:23.400
|
|
really don't expect you don't can't expect deviation to be too great from
|
|
|
|
01:23:23.400 --> 01:23:26.000
|
|
the parent drug but there are examples and we actually designed the peptide
|
|
|
|
01:23:26.000 --> 01:23:29.840
|
|
shown here to be to erase the human like a face of tear peritide and I'll get to
|
|
|
|
01:23:29.840 --> 01:23:33.200
|
|
that later so we actually found using an algorithm the peptides that were
|
|
|
|
01:23:33.200 --> 01:23:36.520
|
|
furthest from the parent molecule and could potentially be immunogenic obviously
|
|
|
|
01:23:36.520 --> 01:23:39.440
|
|
those are impurities that you want to watch out for here's salmon calcitonin
|
|
|
|
01:23:39.440 --> 01:23:42.880
|
|
again most of the impurities kind of traveled around the salmon calcitonin
|
|
|
|
01:23:42.880 --> 01:23:46.600
|
|
API itself and didn't get up into the very high risk but there were they were
|
|
|
|
01:23:46.600 --> 01:23:49.600
|
|
in the kind of moderate risk category here you can see in gray some well-known
|
|
|
|
01:23:49.600 --> 01:23:53.080
|
|
peptides that are immunogenic generally derived from tetanus toxin and others
|
|
|
|
01:23:53.080 --> 01:23:55.840
|
|
those are used as controls in our assays and here the T regitope showing
|
|
|
|
01:23:55.840 --> 01:23:59.120
|
|
that they are epitope dense but highly human and or as I've mentioned have been
|
|
|
|
01:23:59.120 --> 01:24:03.400
|
|
found to be taller genetic now how do we validate the in silico I'm just going
|
|
|
|
01:24:03.400 --> 01:24:06.400
|
|
to point to a couple of assays that we use we use HLA binding assays to see if
|
|
|
|
01:24:06.400 --> 01:24:09.840
|
|
the agritope binds to the HLA DR molecules as predicted then we use T cell
|
|
|
|
01:24:09.840 --> 01:24:12.720
|
|
assays with naive donors looking to see if we can generate a T cell response in
|
|
|
|
01:24:12.720 --> 01:24:16.360
|
|
vitro not the most accurate assay but it's a good way of validating something
|
|
|
|
01:24:16.360 --> 01:24:20.800
|
|
that you've looked at in silico to see if the two two expectations align so it's
|
|
|
|
01:24:20.800 --> 01:24:24.240
|
|
a way of doing orthogonal analysis of your impurity looking at it from two
|
|
|
|
01:24:24.240 --> 01:24:27.320
|
|
different directions and seeing if you get sort of the same signal the binding
|
|
|
|
01:24:27.320 --> 01:24:31.600
|
|
assay that we use is actually an assay that uses a fluorescent tracer peptide
|
|
|
|
01:24:31.640 --> 01:24:36.200
|
|
that's a known binder I'm still I'm still confused about how you can use a blood
|
|
|
|
01:24:36.200 --> 01:24:43.400
|
|
sample from a person to take T cells out and then try to find T cells my
|
|
|
|
01:24:43.400 --> 01:24:49.200
|
|
problem with that is that it is inevitably an incredibly small portion of
|
|
|
|
01:24:49.200 --> 01:24:53.200
|
|
the T cells of that person because most of the naive T cells are hanging out in
|
|
|
|
01:24:53.680 --> 01:25:02.480
|
|
not in circulation but they're in the lymph nodes pre activation so I'm having
|
|
|
|
01:25:02.480 --> 01:25:09.720
|
|
a hard time understanding what kind of sample one gets from circulation my
|
|
|
|
01:25:09.720 --> 01:25:12.960
|
|
assumption would be that that sample would be composed of T cells that have
|
|
|
|
01:25:12.960 --> 01:25:16.240
|
|
already been educated T cells that are already on patrol T cells that are
|
|
|
|
01:25:16.240 --> 01:25:21.360
|
|
already working including cytotoxic T cells as well T regulatory cells and
|
|
|
|
01:25:21.360 --> 01:25:27.160
|
|
T helper cells I don't so she said it was not a very reliable essay or not a
|
|
|
|
01:25:27.160 --> 01:25:32.840
|
|
perfect assay but I think it's it's worse than that it's it's not even she
|
|
|
|
01:25:32.840 --> 01:25:36.320
|
|
should really say that it's like a biological shot in the dark and if we
|
|
|
|
01:25:36.320 --> 01:25:39.120
|
|
get something from it we're lucky but most of the time we don't know for sure
|
|
|
|
01:25:39.120 --> 01:25:46.480
|
|
because the vast majority of the catalog of T cell memory is encased in a place
|
|
|
|
01:25:46.480 --> 01:25:51.760
|
|
that you can't just get to with a small blood sample that really bothers me a
|
|
|
|
01:25:51.760 --> 01:25:56.480
|
|
lot I don't I don't know I don't tie it off with the test peptide which is our
|
|
|
|
01:25:56.480 --> 01:26:01.920
|
|
API or in our impurity we do a seven concentration range of binding assay
|
|
|
|
01:26:01.920 --> 01:26:05.640
|
|
so that we can get a nice dose ranging curve and that gives us the ability to
|
|
|
|
01:26:05.640 --> 01:26:09.840
|
|
calculate the I C 50 of the binding affinity here are some examples strong
|
|
|
|
01:26:09.840 --> 01:26:13.400
|
|
binder competes off the tracer peptide moderate binder only at high
|
|
|
|
01:26:13.400 --> 01:26:16.960
|
|
concentrations non binder doesn't compete at all T cell assay we use is is
|
|
|
|
01:26:16.960 --> 01:26:20.120
|
|
adopted from walnut at all it basically expands up T cells in vitro with the
|
|
|
|
01:26:20.120 --> 01:26:22.880
|
|
test peptide and then you do a measurement of the immune response either in a
|
|
|
|
01:26:22.880 --> 01:26:26.480
|
|
fluorescent at least by assay measuring T cell responses or you can do a flow
|
|
|
|
01:26:26.480 --> 01:26:30.640
|
|
assay the last assay I want to mention is the tetanus toxin bystander assay I'm
|
|
|
|
01:26:30.640 --> 01:26:34.480
|
|
not an expert on those assays I'm gonna try to read a few of her papers and see
|
|
|
|
01:26:34.480 --> 01:26:37.600
|
|
if we can't do some journal clubs on them till we can understand this because I
|
|
|
|
01:26:37.600 --> 01:26:42.800
|
|
am interested in T cells and understanding what is supposedly known so it
|
|
|
|
01:26:42.800 --> 01:26:47.200
|
|
looks like this is gonna be a a lot of work for me but it's good okay or we we
|
|
|
|
01:26:47.200 --> 01:26:50.120
|
|
actually measure for T-reg response but since you can't it's or it's difficult
|
|
|
|
01:26:50.120 --> 01:26:52.680
|
|
to measure directly the T-reg response we usually try to measure it by looking
|
|
|
|
01:26:52.680 --> 01:26:55.920
|
|
at how much a T-reg epitope will suppress another response here we use
|
|
|
|
01:26:55.920 --> 01:26:59.960
|
|
tetanus toxin and we try to suppress that response in vitro we publish that assay
|
|
|
|
01:26:59.960 --> 01:27:04.040
|
|
it's in a new paper looking at a new T-regital tube called factor 5 6 21 please
|
|
|
|
01:27:04.040 --> 01:27:07.760
|
|
take a look at the light Jack paper looking at a new T-regital tube called
|
|
|
|
01:27:07.760 --> 01:27:11.400
|
|
factor 5 6 21 please take a look at the light Jack you're just gonna have to
|
|
|
|
01:27:11.400 --> 01:27:15.880
|
|
wait a few minutes so to the case studies really interesting peptides
|
|
|
|
01:27:15.880 --> 01:27:19.160
|
|
salmon calcitonin and teraparitide salmon calcitonin because it is immunogenic
|
|
|
|
01:27:19.160 --> 01:27:23.080
|
|
it is a foreign peptide only 50% conserved with human calcitonin teraparitide a
|
|
|
|
01:27:23.080 --> 01:27:25.800
|
|
fully human peptide and as it turns out it looks tolerogenic in our in
|
|
|
|
01:27:25.800 --> 01:27:29.640
|
|
silico assays here is salmon calcitonin interestingly enough it has one of those
|
|
|
|
01:27:29.640 --> 01:27:33.600
|
|
every day talked about and that epibar is in the book I can't tell whether if
|
|
|
|
01:27:33.600 --> 01:27:38.120
|
|
tolerogenic is good in her mind or what it is I can't tell we foreign immunogenic
|
|
|
|
01:27:38.120 --> 01:27:40.680
|
|
region others have looked at this region and found it to be immunogenic so that's
|
|
|
|
01:27:40.680 --> 01:27:43.980
|
|
confirmed in our in silico assays and we also looked at impurities you can see
|
|
|
|
01:27:43.980 --> 01:27:46.520
|
|
as I've mentioned before that all of the salmon calcitonin impurities were in
|
|
|
|
01:27:46.520 --> 01:27:50.320
|
|
the left lower quadrant not traveling too far from the a salmon calcitonin
|
|
|
|
01:27:50.320 --> 01:27:53.480
|
|
API and we test all of these in finding assays all these in T-cell assays it's
|
|
|
|
01:27:53.480 --> 01:27:56.520
|
|
one of their controls the tetanus toxin is there so just to give you kind of a
|
|
|
|
01:27:56.520 --> 01:28:01.120
|
|
high-level view of salmon calcitonin is immunogenic in a 16 donor set of assays
|
|
|
|
01:28:01.120 --> 01:28:04.560
|
|
we found that 44% of donors responded again see there you go now they're
|
|
|
|
01:28:04.560 --> 01:28:09.120
|
|
using 16 different donors to find out if there's a T-cell response that
|
|
|
|
01:28:09.120 --> 01:28:14.920
|
|
recognizes one of these epitopes or recognizes their responses to calcitonin
|
|
|
|
01:28:14.920 --> 01:28:20.640
|
|
so I'm still not completely clear what they're doing but I do think it is that
|
|
|
|
01:28:20.640 --> 01:28:25.800
|
|
from this test they can take those T-cells and then find out a little bit
|
|
|
|
01:28:25.800 --> 01:28:30.760
|
|
about what they memorized in this I don't know what an API is I think that
|
|
|
|
01:28:30.760 --> 01:28:37.160
|
|
this is some abbreviation for a protein artificially protein something you know
|
|
|
|
01:28:37.160 --> 01:28:39.760
|
|
like I don't know what that means I could you could google it and find it
|
|
|
|
01:28:39.760 --> 01:28:43.080
|
|
out but it's she's used it a couple times in the talk as if everybody in the
|
|
|
|
01:28:43.080 --> 01:28:46.240
|
|
audience understood it so I didn't that matrix a score is above that random
|
|
|
|
01:28:46.240 --> 01:28:50.680
|
|
zero that's the median of what we would expect from random chance so higher
|
|
|
|
01:28:50.680 --> 01:28:55.560
|
|
than I would say expected immunogenicity for a peptide or expected in silico and
|
|
|
|
01:28:55.560 --> 01:28:59.840
|
|
validated in vitro we also found that the impurities listed here some of which
|
|
|
|
01:28:59.840 --> 01:29:04.200
|
|
had higher scores a higher it means a small number of donors who put you in
|
|
|
|
01:29:05.200 --> 01:29:09.800
|
|
salt and but you can see that yes although salmone calcitonin is immunogenic
|
|
|
|
01:29:09.800 --> 01:29:13.440
|
|
the impurities do look like they're slightly more immunogenic as predicted
|
|
|
|
01:29:13.440 --> 01:29:17.040
|
|
in silico so the findings in our salmone calcitonin studies were that the
|
|
|
|
01:29:17.040 --> 01:29:19.440
|
|
salmone calcitonin impurities had similar epimatrix scores that were
|
|
|
|
01:29:19.440 --> 01:29:22.520
|
|
moderate and Janus matrix scores which were non-human and they had
|
|
|
|
01:29:22.520 --> 01:29:27.360
|
|
application program to the API so they were immunogenic as predicted but not
|
|
|
|
01:29:27.360 --> 01:29:30.440
|
|
more so than the API itself so that was a nice finding now what about terra
|
|
|
|
01:29:30.440 --> 01:29:34.600
|
|
peritide terra peritide is fully human it is a sub sequence of the parathyroid
|
|
|
|
01:29:34.600 --> 01:29:37.920
|
|
hormone it's a drug called fordio it's generally not immunogenic in the
|
|
|
|
01:29:37.920 --> 01:29:41.480
|
|
clinic but it does have an epibar so if you look at this this peptide sequence
|
|
|
|
01:29:41.480 --> 01:29:43.960
|
|
you see that epibar and you go to yourself that's got to be immunogenic
|
|
|
|
01:29:43.960 --> 01:29:47.440
|
|
however when we look at it with Janus matrix I do not know what an epibar is
|
|
|
|
01:29:47.440 --> 01:29:50.960
|
|
apparently everybody else in the audience does but I don't know what an
|
|
|
|
01:29:50.960 --> 01:29:54.720
|
|
epibar is I could also google that but I'm not gonna do it right now it has a
|
|
|
|
01:29:54.720 --> 01:29:58.080
|
|
very high Janus matrix human homology score meaning that it has a
|
|
|
|
01:29:58.080 --> 01:30:00.600
|
|
conservation with the TCR facing residues of peptides found in the
|
|
|
|
01:30:00.600 --> 01:30:04.200
|
|
human genome and actually it's related to the human protein tubulin which is
|
|
|
|
01:30:04.200 --> 01:30:08.680
|
|
found in most cells all cells it's the protein that basically gives each cell
|
|
|
|
01:30:08.680 --> 01:30:11.440
|
|
its structure so this is very similar promiscuous T cell epitope is found in
|
|
|
|
01:30:11.440 --> 01:30:14.920
|
|
tubulin here's the cytoscape diagram showing that relationship again as I've
|
|
|
|
01:30:14.920 --> 01:30:18.800
|
|
mentioned terra peritide actually has a high epimatrix score higher epitope
|
|
|
|
01:30:18.800 --> 01:30:21.320
|
|
density than what we would expect from random chance lots of T cell epitopes
|
|
|
|
01:30:21.320 --> 01:30:24.640
|
|
epibar and it's highly human as we've mentioned in terms of its Janus matrix
|
|
|
|
01:30:24.640 --> 01:30:28.320
|
|
score and so are most of the impurities and we actually had to generate an
|
|
|
|
01:30:28.320 --> 01:30:31.760
|
|
impurity that erased that TCR face and we did do that with what we call the
|
|
|
|
01:30:31.760 --> 01:30:35.320
|
|
WIM machine which generates all the impurities at every single amino acid
|
|
|
|
01:30:35.320 --> 01:30:39.040
|
|
position for every generic peptide that we want to look at and that actually gave
|
|
|
|
01:30:39.040 --> 01:30:43.600
|
|
us a couple of solutions that we could test in vitro and in vivo here again are
|
|
|
|
01:30:43.600 --> 01:30:47.120
|
|
the impurities again this publication is in preparation we promise that you'll
|
|
|
|
01:30:47.120 --> 01:30:50.080
|
|
get a look at the detailed results for these impurities when we finish now I'm
|
|
|
|
01:30:50.080 --> 01:30:52.560
|
|
just gonna cut to the chase because I thought this was really interesting we
|
|
|
|
01:30:52.560 --> 01:30:55.280
|
|
actually did that tetanus toxin bystander assay with the API so here I'm
|
|
|
|
01:30:55.280 --> 01:30:58.880
|
|
just using the API to see if it was tolerogenic in vitro so we added
|
|
|
|
01:30:58.880 --> 01:31:01.880
|
|
tetanus to this the wells and in this example donor what we're looking for
|
|
|
|
01:31:01.880 --> 01:31:05.160
|
|
is proliferation of the cells the cells travel left in the flow when they
|
|
|
|
01:31:05.160 --> 01:31:09.520
|
|
start proliferating and when we actually see a T-reg have an effect on that
|
|
|
|
01:31:09.520 --> 01:31:13.040
|
|
proliferation you can see less proliferation here and less activation
|
|
|
|
01:31:13.040 --> 01:31:16.960
|
|
and presentation of activation cell surface markers on the T cells so two
|
|
|
|
01:31:16.960 --> 01:31:19.920
|
|
different tests of the same thing and what you see here is two standard T
|
|
|
|
01:31:19.920 --> 01:31:24.000
|
|
regitope controls and terra peritide all three are suppressing the
|
|
|
|
01:31:24.000 --> 01:31:26.640
|
|
proliferation response to tetanus toxin and our tetanus toxin bystander
|
|
|
|
01:31:26.640 --> 01:31:29.360
|
|
assay and they also reduce activation this was repeated with I think five
|
|
|
|
01:31:29.360 --> 01:31:33.320
|
|
total donors which demonstrated that that terra peritide does actually have a
|
|
|
|
01:31:33.320 --> 01:31:36.800
|
|
tolerogenic effect in vitro could be what we would call a T regitope and we're
|
|
|
|
01:31:36.800 --> 01:31:40.120
|
|
going to be exploring that further do the impurities induce an immune response and
|
|
|
|
01:31:40.120 --> 01:31:43.840
|
|
the answer is yes if you remove the TCR cross-conserved residues the terra
|
|
|
|
01:31:43.840 --> 01:31:46.880
|
|
peritide impurities still bind but they are more immunogenic and we look forward
|
|
|
|
01:31:46.880 --> 01:31:50.960
|
|
to publishing that data so you can review it in detail so in brief we had
|
|
|
|
01:31:50.960 --> 01:31:54.320
|
|
an opportunity to look at these two case studies and then the most recent
|
|
|
|
01:31:54.320 --> 01:31:57.680
|
|
project is to prospectively predict and rank all peptide impurities well at
|
|
|
|
01:31:57.680 --> 01:32:02.200
|
|
least for the generic peptides using a machine called whim what is whim is whim
|
|
|
|
01:32:02.200 --> 01:32:06.240
|
|
stands for the what if machine and basically since we don't know all drug
|
|
|
|
01:32:06.240 --> 01:32:09.360
|
|
impurities but there are certainly many that could occur we basically just made
|
|
|
|
01:32:09.360 --> 01:32:12.120
|
|
an in silico tool that performs all possible changes to the natural amino
|
|
|
|
01:32:12.120 --> 01:32:15.080
|
|
acid sequence of the drug substance and measures their impact on the epitome
|
|
|
|
01:32:15.080 --> 01:32:19.800
|
|
content not only epitope density but also their humanness the what if machine
|
|
|
|
01:32:19.800 --> 01:32:24.480
|
|
sounds a lot like the domain server or like what Robert Malone did at the
|
|
|
|
01:32:24.480 --> 01:32:29.920
|
|
beginning of the pandemic where he tested all possible drugs all known drugs and
|
|
|
|
01:32:29.920 --> 01:32:40.680
|
|
pharmaceuticals against the the virtual 3D crystallization model of the of the
|
|
|
|
01:32:40.720 --> 01:32:46.240
|
|
enzyme that he made in like three weeks he made the model of the enzyme of the
|
|
|
|
01:32:46.240 --> 01:32:52.320
|
|
protein that he wanted to bind to which was the 3 CL enzyme or protease 3 CL
|
|
|
|
01:32:52.320 --> 01:32:58.520
|
|
protease of the of the virus he made a crystal a virtual crystal model of that
|
|
|
|
01:32:58.520 --> 01:33:05.080
|
|
which again is a simulation and then he took that simulation he interfaced it
|
|
|
|
01:33:05.080 --> 01:33:12.600
|
|
with all known drugs and pharmaceuticals in the domain server or in the domain
|
|
|
|
01:33:12.600 --> 01:33:21.160
|
|
program or something and the crazy thing is is that program kicked out remdesivir
|
|
|
|
01:33:21.160 --> 01:33:28.360
|
|
femotidine and a few other things apparently it didn't kick out a hydroxy
|
|
|
|
01:33:28.360 --> 01:33:33.280
|
|
chloroquine or ivermectin and that could be because they don't interact with the
|
|
|
|
01:33:33.280 --> 01:33:39.400
|
|
virtual 3D crystallography model that Robert Malone made of the 3 CL protease
|
|
|
|
01:33:39.400 --> 01:33:45.640
|
|
in January of 2020 after being told by Michael Callahan to spin his team up
|
|
|
|
01:33:45.640 --> 01:33:53.080
|
|
largely volunteers this sounds like a very similar you know magic box where you
|
|
|
|
01:33:53.080 --> 01:33:59.280
|
|
just kind of crank it out and it gives you answers all possible changes but this
|
|
|
|
01:33:59.280 --> 01:34:04.360
|
|
is easier because it's only nine only nine amino acids in their in their
|
|
|
|
01:34:04.360 --> 01:34:09.000
|
|
epitopes and so they only need to change those nine amino acids in relation to
|
|
|
|
01:34:09.000 --> 01:34:13.880
|
|
the other chemical amino acids that are related to them so 20 amino acids you
|
|
|
|
01:34:13.880 --> 01:34:19.160
|
|
know it's maximum it's not that many so it it's a little less than all the drugs
|
|
|
|
01:34:19.160 --> 01:34:23.880
|
|
and pharmaceuticals known to man were tested against my my thing like then
|
|
|
|
01:34:23.880 --> 01:34:27.720
|
|
calculate a predicted immunodulus score that combines those two things and we
|
|
|
|
01:34:27.720 --> 01:34:30.320
|
|
basically identify whether certain impurities with modifications at a
|
|
|
|
01:34:30.320 --> 01:34:34.160
|
|
certain location are more risky than others this generates a list list that
|
|
|
|
01:34:34.160 --> 01:34:37.360
|
|
could be used to identify impurities that could be removed from generic drugs
|
|
|
|
01:34:37.360 --> 01:34:42.600
|
|
prior to approval so this just shows you an example of past pogutide which is a
|
|
|
|
01:34:42.600 --> 01:34:45.800
|
|
glip one that was taken off the market because it had a lot of impurities a lot
|
|
|
|
01:34:45.800 --> 01:34:49.200
|
|
of those impurities were immunogenic there wasn't HLA association none of
|
|
|
|
01:34:49.200 --> 01:34:52.960
|
|
that ever got published but we have seen the data and what is shown here is just
|
|
|
|
01:34:52.960 --> 01:34:57.280
|
|
a duplication modification that we generated with whim you can see that some
|
|
|
|
01:34:57.280 --> 01:35:01.420
|
|
of those some here's the RLD or the API and here are the scores of the
|
|
|
|
01:35:01.420 --> 01:35:05.480
|
|
modified impurities generated in the wind machine you can also see the Janus
|
|
|
|
01:35:05.480 --> 01:35:08.400
|
|
major comology score obviously a high homology score would be less immunogenic
|
|
|
|
01:35:08.400 --> 01:35:11.800
|
|
and what's really interesting that is that the HLA that restricted were
|
|
|
|
01:35:11.800 --> 01:35:15.440
|
|
present in the patients that had the adverse events with TASPO correlated
|
|
|
|
01:35:15.440 --> 01:35:19.280
|
|
with the highest risk immunogenicity in this table so maybe we identified the
|
|
|
|
01:35:19.280 --> 01:35:22.880
|
|
impurities that were a problem in that TASPO clinical trial so this is just to
|
|
|
|
01:35:22.880 --> 01:35:26.760
|
|
tell you what's coming up we so in a way it's very interesting because what she
|
|
|
|
01:35:26.760 --> 01:35:34.860
|
|
is doing is not dissimilar to what San Sashalatopova was doing back in the
|
|
|
|
01:35:34.860 --> 01:35:40.600
|
|
90s where she was giving them and giving pharmaceutical companies another way to
|
|
|
|
01:35:40.600 --> 01:35:48.640
|
|
read the P wave of cardiac of cardiac signals so one of the things that they
|
|
|
|
01:35:48.640 --> 01:35:54.240
|
|
look for in all drug trials is the the signature of the heart of the patient
|
|
|
|
01:35:54.240 --> 01:35:58.080
|
|
and you know that the signature of the heart of a patient has this you know
|
|
|
|
01:35:58.080 --> 01:36:02.880
|
|
thing that they call I don't know what it is electrocardiogram and it has this
|
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01:36:02.880 --> 01:36:06.960
|
|
little shape and they show it on the ER show and all other stuff and it's got a
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01:36:06.960 --> 01:36:12.600
|
|
P wave and a Q something and whatever and cardiologists that are really good at
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01:36:12.600 --> 01:36:15.800
|
|
looking at these things can tell what's wrong with you by just looking at the
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01:36:15.800 --> 01:36:20.800
|
|
distances and the sizes between these these characteristic electrical signals
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01:36:20.800 --> 01:36:30.080
|
|
that come from the heart and so Sandra a lot of Sashalatopova was the CEO of a
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01:36:30.080 --> 01:36:36.480
|
|
company which sold software which essentially analyzed the the cardiac
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01:36:36.480 --> 01:36:44.800
|
|
data of in clinical trials and so in a way it was a what-if machine about the
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01:36:44.800 --> 01:36:52.000
|
|
cardiac data in a in a way that could as Sashal that be more sensitive so that
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|
01:36:52.000 --> 01:36:58.120
|
|
let's say bad signals cut bad cardiac signals would not prematurely end a
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01:36:58.120 --> 01:37:04.720
|
|
trial or not allow a drug to come to market because their software allowed a
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01:37:04.720 --> 01:37:10.240
|
|
more subtle analysis which you could just construe as the software allowed them
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|
|
01:37:10.240 --> 01:37:15.640
|
|
to get away with more signal change then they should have been able to and I
|
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|
|
01:37:15.640 --> 01:37:19.600
|
|
would I would argue that this might be something very similar to that where
|
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|
01:37:19.600 --> 01:37:29.280
|
|
we're looking at a a kind of a screen of a biologic where you can actually look
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01:37:29.280 --> 01:37:33.560
|
|
at the the results of a clinical trial and then come up with a model where the
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|
01:37:33.560 --> 01:37:39.440
|
|
where the impurities that you found are responsible for the for the adverse
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|
|
01:37:39.480 --> 01:37:44.000
|
|
events rather than for the the product as a whole and so you can blame it on this
|
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|
|
01:37:44.000 --> 01:37:53.200
|
|
what how well with using software three layers of software can identify where the
|
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|
|
01:37:53.200 --> 01:38:00.440
|
|
potential immunogenic epitopes are in your designer drug and its impurities and so
|
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|
|
01:38:00.440 --> 01:38:04.120
|
|
unless you're able to go into this code and find it yourself which you can't
|
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|
|
01:38:04.120 --> 01:38:08.000
|
|
unless you're part of this company you're never going to be able to verify
|
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|
|
01:38:08.000 --> 01:38:13.600
|
|
whether or not this score is actually proving that the intended protein is
|
|
|
|
01:38:13.600 --> 01:38:19.520
|
|
fine but the purity impurities are wrong it's a really wonderful wonderful tool
|
|
|
|
01:38:19.520 --> 01:38:26.080
|
|
if it's honest but it's also a hugely potential source of fraud because just
|
|
|
|
01:38:26.080 --> 01:38:31.240
|
|
because you use a computer program doesn't make it correct and if you can
|
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|
|
01:38:31.240 --> 01:38:34.280
|
|
launder anything you want through through the domain program and get
|
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|
|
01:38:34.280 --> 01:38:40.520
|
|
everybody to take remdesivir and that's kind of the same trick which I think
|
|
|
|
01:38:40.520 --> 01:38:47.840
|
|
was done with remdesivir and potentially could be done with a software suite like
|
|
|
|
01:38:47.840 --> 01:38:52.800
|
|
this one. We identified the impurities that were a problem in that TASPO clinical
|
|
|
|
01:38:52.800 --> 01:38:56.480
|
|
trial so this is just to tell you what's coming up we are really delighted to be
|
|
|
|
01:38:56.480 --> 01:38:59.920
|
|
working with our OGD colleagues on these projects of the last one being
|
|
|
|
01:38:59.920 --> 01:39:03.040
|
|
Selen Calcitonin and Terra Peritite and the current one being Wim I have
|
|
|
|
01:39:03.040 --> 01:39:06.560
|
|
included publications in my presentation and I want to thank my team for doing
|
|
|
|
01:39:06.560 --> 01:39:09.280
|
|
the actual work that I get to present and I'll take any questions that you may
|
|
|
|
01:39:09.280 --> 01:39:15.600
|
|
have thank you for your attention. So we're going to leave it at that right yes
|
|
|
|
01:39:15.600 --> 01:39:24.360
|
|
we are it whoops that was a mistake. Hello and welcome to our webinar the
|
|
|
|
01:39:24.360 --> 01:39:27.160
|
|
webinar is entitled does nature always know best the role of regulatory
|
|
|
|
01:39:27.160 --> 01:39:30.360
|
|
T cell epitopes in biologics and vaccines my name is Annie DeGroote I'm
|
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|
|
01:39:31.320 --> 01:39:35.400
|
|
guess we have to I'll have to watch that one sometime because that's really
|
|
|
|
01:39:35.400 --> 01:39:38.880
|
|
cool too I want to know what they're thinking I want to know what's going on
|
|
|
|
01:39:38.880 --> 01:39:44.680
|
|
here. So if you don't mind I'm just gonna take this chance to present the
|
|
|
|
01:39:44.680 --> 01:39:51.920
|
|
last part of my running slide set right now in a different voice. Ladies and
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|
|
01:39:51.920 --> 01:39:56.840
|
|
gentlemen we have been misled about the potential for pandemics in bad caves
|
|
|
|
01:39:57.040 --> 01:40:02.080
|
|
and we've also been misled about the potential of this pandemic potential
|
|
|
|
01:40:02.080 --> 01:40:07.960
|
|
that can be accessed via cell culture and via animal passage over several
|
|
|
|
01:40:07.960 --> 01:40:12.920
|
|
decades we have been led to believe that this pandemic potential could be
|
|
|
|
01:40:12.920 --> 01:40:18.240
|
|
accessed in a laboratory and even worse you could stitch pieces of potential
|
|
|
|
01:40:18.240 --> 01:40:21.920
|
|
pandemic viruses together and create something that mother nature herself
|
|
|
|
01:40:21.920 --> 01:40:28.440
|
|
never would have and it is this illusion of consensus about the potential for
|
|
|
|
01:40:28.440 --> 01:40:34.400
|
|
pandemics in bad caves and in laboratories that is the new mythology
|
|
|
|
01:40:34.400 --> 01:40:41.000
|
|
with which they intend to govern you and more importantly your children because
|
|
|
|
01:40:41.000 --> 01:40:45.680
|
|
it's different than terrorism it's different than patriotism it's different
|
|
|
|
01:40:45.680 --> 01:40:51.280
|
|
than communism it's different than aliens it affects everyone and it's
|
|
|
|
01:40:51.320 --> 01:40:58.360
|
|
invisible and it's under and you can't investigate it there's nothing that the
|
|
|
|
01:40:58.360 --> 01:41:04.000
|
|
average person can do to disprove this without learning years of molecular
|
|
|
|
01:41:04.000 --> 01:41:11.800
|
|
biology to the extent to which you can see through this but there is a way to
|
|
|
|
01:41:11.800 --> 01:41:15.280
|
|
see through it if you don't bother with the biology you can just bother with the
|
|
|
|
01:41:15.280 --> 01:41:22.240
|
|
numbers and the way to think about it is in 2020 they told you that there was a
|
|
|
|
01:41:22.240 --> 01:41:31.640
|
|
new cause of death a new way of dying for which everyone was vulnerable and that
|
|
|
|
01:41:31.640 --> 01:41:39.600
|
|
new way of dying should have shown up as a spreading respiratory virus and so
|
|
|
|
01:41:39.600 --> 01:41:45.640
|
|
when you say this out loud there's a novel cause of death that's spreading that is
|
|
|
|
01:41:45.640 --> 01:41:53.680
|
|
a certain level of expectation in the data and Denny Rancor has shown us that
|
|
|
|
01:41:53.680 --> 01:42:00.320
|
|
those expectations are never met so the excess deaths are not correlated with
|
|
|
|
01:42:00.320 --> 01:42:08.600
|
|
the spread they are correlated with poverty excess deaths are not correlated
|
|
|
|
01:42:08.600 --> 01:42:17.440
|
|
with spread they are correlated with poverty in America and that's because
|
|
|
|
01:42:17.440 --> 01:42:26.480
|
|
hospital protocols were destroyed the autonomy of a doctor to treat the
|
|
|
|
01:42:26.480 --> 01:42:33.360
|
|
symptoms in front of him or her was destroyed and with a high financial
|
|
|
|
01:42:33.360 --> 01:42:41.360
|
|
incentive and top-down control in hospitals they were able to use a
|
|
|
|
01:42:41.360 --> 01:42:49.760
|
|
nonspecific PCR test to rope an ever larger portion of all cause mortality
|
|
|
|
01:42:49.760 --> 01:42:57.040
|
|
into a new national security priority that they called COVID when in reality
|
|
|
|
01:42:57.040 --> 01:43:02.040
|
|
all they really needed to do was kill a bunch of people with pneumonia and call
|
|
|
|
01:43:02.040 --> 01:43:08.360
|
|
it that that's all they need to do if you need antibiotics for secondary
|
|
|
|
01:43:08.360 --> 01:43:13.440
|
|
pneumonia and you don't get it and instead they test you with PCR and then
|
|
|
|
01:43:13.440 --> 01:43:20.240
|
|
put you on a ventilator and gave you remdesivir you were added to the list and
|
|
|
|
01:43:20.240 --> 01:43:25.320
|
|
in fact with a lot of these people early on there was no remdesivir there was
|
|
|
|
01:43:25.320 --> 01:43:32.160
|
|
just a lack of treatment from not do not resuscitate orders in New York City
|
|
|
|
01:43:32.160 --> 01:43:38.160
|
|
all the way to ventilating people they could talk and these protocols were
|
|
|
|
01:43:38.160 --> 01:43:44.600
|
|
enacted wherever the government or the CDC had sufficient push and we're gonna
|
|
|
|
01:43:44.600 --> 01:43:48.680
|
|
find more and more that the places where these protocols didn't occur there's
|
|
|
|
01:43:48.680 --> 01:43:54.000
|
|
gonna be some administrative reason why one doctor got in the way or several
|
|
|
|
01:43:54.000 --> 01:44:00.080
|
|
nurses got in the way and so the death toll never happened there that's the
|
|
|
|
01:44:00.080 --> 01:44:05.080
|
|
reason why the death toll doesn't cross borders ladies and gentlemen that's the
|
|
|
|
01:44:05.080 --> 01:44:11.280
|
|
reason why why Germany had almost no deaths until the vaccine was rolled out
|
|
|
|
01:44:11.280 --> 01:44:17.960
|
|
no excess deaths ladies and gentlemen they intend a total surrender of
|
|
|
|
01:44:17.960 --> 01:44:21.480
|
|
individual sovereignty and enforcement of a fundamental inversion from basic
|
|
|
|
01:44:21.480 --> 01:44:26.600
|
|
human rights to basic granted permissions and this illusion of consensus is how
|
|
|
|
01:44:26.600 --> 01:44:30.160
|
|
they've done it they have convinced us that there was a novel virus that
|
|
|
|
01:44:30.160 --> 01:44:33.960
|
|
everybody had to act on that the Army RNA saved a lot of people but it could
|
|
|
|
01:44:33.960 --> 01:44:37.080
|
|
have been better and because this was likely again a function virus this will
|
|
|
|
01:44:37.080 --> 01:44:42.480
|
|
definitely happen again and that illusion of consensus I'm calling a scooby-doo
|
|
|
|
01:44:42.480 --> 01:44:46.840
|
|
which is a bunch of teenagers being fooled into solving a mystery that ends
|
|
|
|
01:44:46.840 --> 01:44:53.560
|
|
up to be bad guys with monster masks and so while the entire population is
|
|
|
|
01:44:53.560 --> 01:44:58.640
|
|
afraid of a monster called COVID-19 we are now being tricked into taking the
|
|
|
|
01:44:58.640 --> 01:45:04.040
|
|
masks off of the people who are responsible for that monster instead of
|
|
|
|
01:45:04.040 --> 01:45:09.040
|
|
being told the truth which is the monster could only exist in the context
|
|
|
|
01:45:09.040 --> 01:45:16.000
|
|
of lies lies about your immune system lies about mother nature lies about the
|
|
|
|
01:45:16.000 --> 01:45:22.600
|
|
fidelity of RNA lies about the immune response lies about vaccination lies
|
|
|
|
01:45:22.600 --> 01:45:30.400
|
|
about intramuscular injection lies about everything and in 2020 in 2021 the
|
|
|
|
01:45:30.400 --> 01:45:38.520
|
|
lies were so succinct and so synchronized and so perfect the doctors
|
|
|
|
01:45:38.520 --> 01:45:42.880
|
|
around the world were ventilating people to prevent spread doctors around
|
|
|
|
01:45:42.880 --> 01:45:49.520
|
|
America were using remdesivir with no no bother to read where it had been used
|
|
|
|
01:45:49.520 --> 01:45:56.040
|
|
before no bother to look into how it worked no bother at all just following
|
|
|
|
01:45:56.040 --> 01:46:02.720
|
|
the CDC protocol don't use antibiotics anymore don't use antibiotics anymore on
|
|
|
|
01:46:02.720 --> 01:46:11.680
|
|
a viral disease was something that people on twiv are still saying then they shut
|
|
|
|
01:46:11.680 --> 01:46:16.840
|
|
down schools they masked our little babies and they terrified everybody who
|
|
|
|
01:46:16.840 --> 01:46:23.400
|
|
wasn't sophisticated enough to know they terrified every skilled TV watcher
|
|
|
|
01:46:23.400 --> 01:46:28.320
|
|
with this illusion of consensus and those skilled TV watchers are just now
|
|
|
|
01:46:28.320 --> 01:46:32.840
|
|
thinking that they finally figured out what happened which is that we covered
|
|
|
|
01:46:32.840 --> 01:46:37.960
|
|
up our role in the production of this virus in China and then it got out in
|
|
|
|
01:46:37.960 --> 01:46:44.800
|
|
China tried to cover it up and so did we and the reason why this is so enticing
|
|
|
|
01:46:44.800 --> 01:46:48.840
|
|
this illusion of consensus of a laboratory batcave zoonosis is that that
|
|
|
|
01:46:48.840 --> 01:46:53.880
|
|
means that this potential is there forever that means that we need the who
|
|
|
|
01:46:53.880 --> 01:47:02.640
|
|
and vaccines and viral surveillance and all of this stuff forever and that's what
|
|
|
|
01:47:02.640 --> 01:47:07.120
|
|
I mean by trying to govern your children on this mythology this mythology
|
|
|
|
01:47:07.120 --> 01:47:12.280
|
|
that we defeat viruses with vaccination all the time like Annie DeGroote said in
|
|
|
|
01:47:12.280 --> 01:47:19.040
|
|
that brief piece on the TV channel she said that we have to develop immunity
|
|
|
|
01:47:19.040 --> 01:47:26.840
|
|
with vaccines for this one and novel viruses can jump from species and
|
|
|
|
01:47:26.840 --> 01:47:32.640
|
|
can pandemic be false PCR false positives are rare asymptomatic spread
|
|
|
|
01:47:32.640 --> 01:47:38.360
|
|
was real and they still believe it is real my neighbors still believe it's
|
|
|
|
01:47:38.360 --> 01:47:45.760
|
|
real she tested positive for covid and her husband made her isolate in her
|
|
|
|
01:47:45.760 --> 01:47:52.640
|
|
bedroom for five days and she didn't come out I mean it's people are that they
|
|
|
|
01:47:52.640 --> 01:47:58.040
|
|
believe it and they live right next door to me they were just here for the party
|
|
|
|
01:47:58.040 --> 01:48:06.320
|
|
and they know how we think but they can't snap it they can't turn it off they
|
|
|
|
01:48:06.320 --> 01:48:11.880
|
|
can't stop because they took the test and the test said positive you know it's
|
|
|
|
01:48:11.880 --> 01:48:16.160
|
|
like if your husband took a pregnancy test and it said positive would you
|
|
|
|
01:48:16.160 --> 01:48:20.800
|
|
believe it was right I mean the conflated background signal is the thing you have
|
|
|
|
01:48:20.800 --> 01:48:24.680
|
|
to understand because we don't know what that conflated background signal is is
|
|
|
|
01:48:24.680 --> 01:48:31.760
|
|
it really coronaviruses is it really human RNA is it human RNA sequences see
|
|
|
|
01:48:31.760 --> 01:48:36.760
|
|
the problem with it is is that up until 2020 we knew that coronaviruses had a
|
|
|
|
01:48:36.760 --> 01:48:42.240
|
|
lot of homology with our own proteins and in fact that's what everybody was
|
|
|
|
01:48:42.240 --> 01:48:45.600
|
|
complaining about in the very beginning when we decided to use the spike as the
|
|
|
|
01:48:45.600 --> 01:48:49.400
|
|
transfection because using the spike is the transfection it's got a lot of
|
|
|
|
01:48:49.400 --> 01:48:54.480
|
|
epitopes in it that aren't so not human and so we risk mimicry we risking this
|
|
|
|
01:48:54.480 --> 01:48:58.680
|
|
potential auto immunity there's lots of things in there that we might not want
|
|
|
|
01:48:59.160 --> 01:49:04.720
|
|
platelet factor for a mile in this kind of thing and that's what makes
|
|
|
|
01:49:04.720 --> 01:49:07.800
|
|
epi-backs so interesting is they knew that already they knew that that was
|
|
|
|
01:49:07.800 --> 01:49:15.120
|
|
screenable and so it's not like all this stuff wasn't known Robert Malone was
|
|
|
|
01:49:15.120 --> 01:49:22.280
|
|
working with that company for 15 years no eight years he definitely knew just
|
|
|
|
01:49:22.280 --> 01:49:29.040
|
|
like he knew Peter Colis knew that you can't target an mRNA encased in a lipid
|
|
|
|
01:49:29.040 --> 01:49:34.680
|
|
nanoparticle to a particular part of your body by intramuscular injection so when
|
|
|
|
01:49:34.680 --> 01:49:41.360
|
|
Robert Malone went on Brett Weinstein's podcast in 2021 and said that he thought
|
|
|
|
01:49:41.360 --> 01:49:47.240
|
|
that they probably fixed that problem that's absolute bullshit and there's no
|
|
|
|
01:49:47.240 --> 01:49:53.240
|
|
other word for it that was a bald face lie he knew that Peter Colis had never
|
|
|
|
01:49:53.240 --> 01:49:57.120
|
|
solved that problem and that's Peter Colis knew he never solved that problem
|
|
|
|
01:49:57.120 --> 01:50:07.880
|
|
he had burnt five postdocs on it five postdocs were burnt on trying to get the
|
|
|
|
01:50:07.880 --> 01:50:15.720
|
|
LNP's of Peter Colis to target somewhere and they couldn't even get the real easy
|
|
|
|
01:50:15.880 --> 01:50:22.840
|
|
target like the liver to work very well that's where we're at lies upon lies
|
|
|
|
01:50:22.840 --> 01:50:28.000
|
|
upon lies and some of them are assumptions some of them are dumb when you hear
|
|
|
|
01:50:28.000 --> 01:50:33.000
|
|
Peter Colis say that when that when that Pfizer report came out and they said
|
|
|
|
01:50:33.000 --> 01:50:38.720
|
|
that the vaccine was 95% effective what did Peter Colis do he went and got a
|
|
|
|
01:50:38.720 --> 01:50:45.240
|
|
glass of scotch and started drinking that's exactly what he said I'm not really
|
|
|
|
01:50:45.240 --> 01:50:50.040
|
|
sure what to what to think about this I'm not really sure how to push it I do
|
|
|
|
01:50:50.040 --> 01:50:52.800
|
|
know that my voice needs a little bit of a break though I can feel it a little
|
|
|
|
01:50:52.800 --> 01:50:55.680
|
|
bit in the back so I'm gonna give it a little rest because I did rupture
|
|
|
|
01:50:55.680 --> 01:50:59.800
|
|
something back there so something needs healing I'm sure but there was
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01:50:59.800 --> 01:51:04.680
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definitely endemic background of something that they misconstrued as the
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01:51:04.680 --> 01:51:09.720
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novel spread of something else and they use the protocols to fill it to fool us
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01:51:10.120 --> 01:51:13.200
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and protocols were actually murder not COVID and
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01:51:13.200 --> 01:51:18.040
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transfection is not medicine now it could have been an infectious clone
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01:51:18.040 --> 01:51:22.800
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release that's my favorite explanation the only question is how far does the
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01:51:22.800 --> 01:51:26.320
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clone spread how much did they spread was it really only three people and three
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01:51:26.320 --> 01:51:31.800
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sequences and and and three seeded narratives or was it really a whole
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01:51:31.800 --> 01:51:37.200
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hospital of in northern Italy and a whole bunch of people in Wuhan and in Iran I
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01:51:37.280 --> 01:51:42.280
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don't know but if we actually considered it a crime and actually started to think
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01:51:42.280 --> 01:51:46.280
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about the plausible biology that's available to these people that's what
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01:51:46.280 --> 01:51:50.520
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we would be considering an infectious clone release could have been a
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01:51:50.520 --> 01:51:54.680
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transfection agent as well what's the difference between a transfection agent
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01:51:54.680 --> 01:52:01.120
|
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and an infectious clone an infectious clone release is is the mRNA or sorry
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01:52:01.120 --> 01:52:08.840
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the RNA of a coronavirus which is presumed to be self-replicating so it
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01:52:08.840 --> 01:52:14.000
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has a RNA dependent RNA polymerase and 30 other accessory proteins which allow
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01:52:14.000 --> 01:52:21.080
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the assembly of coronavirus particles whereas a transfection agent release
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01:52:21.080 --> 01:52:26.280
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might have just been mRNA which expresses a spike or expresses an
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01:52:26.320 --> 01:52:32.520
|
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immunogen which would produce the the false positives that they needed or
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01:52:32.520 --> 01:52:38.040
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produce the I can only be really the false positives that they needed so the
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01:52:38.040 --> 01:52:41.840
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transfection agent might work if you transfected the spike protein and an
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01:52:41.840 --> 01:52:45.920
|
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end protein or something like that and then you knew that your PCR was going to
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01:52:45.920 --> 01:52:50.040
|
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test for those then a a transfection agent of just the end protein would work
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01:52:50.040 --> 01:52:55.080
|
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if your PCR is only going to test for the end protein but I think it depended on
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01:52:55.080 --> 01:52:57.880
|
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what country you're in some countries were testing for this bike some were
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01:52:57.880 --> 01:53:01.440
|
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doing RNA dependent RNA polymerase some were doing RNA dependent polymerase and
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01:53:01.440 --> 01:53:06.680
|
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and I think America now is doing three different ends or something like that so
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01:53:06.680 --> 01:53:11.280
|
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it's changed over time but the protocols have always been murder and
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01:53:11.280 --> 01:53:16.360
|
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transfection has always not been medicine and the same thing goes for this
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01:53:16.360 --> 01:53:20.400
|
|
trap we've been working on this one for a long time but I'm pretty sure that the
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01:53:20.400 --> 01:53:26.320
|
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no-virus people are gonna vanish into sort of insignificance at some point as
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01:53:26.320 --> 01:53:33.000
|
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the the ridiculousness of their stance becomes more and more obvious and the
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01:53:33.000 --> 01:53:38.760
|
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way that they will continue to sort of push for is instead of protocols and
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01:53:38.760 --> 01:53:47.920
|
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push you know unrelated cursory issues to make you ask the wrong question is the
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01:53:47.920 --> 01:53:53.200
|
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best the absolute best way to put it because if your question is are there
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01:53:53.200 --> 01:53:58.040
|
|
viruses or not you're asking the wrong question because we know that they can
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01:53:58.040 --> 01:54:03.560
|
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aerosolize lipid nanoparticles we know that they can aerosolize RNA and DNA we
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01:54:03.560 --> 01:54:08.320
|
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know that they can make infectious clones by the leader we know that they can make
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01:54:08.320 --> 01:54:16.800
|
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recombinant DNA and recombinant RNA in the laboratory in quantity and so are
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01:54:16.800 --> 01:54:21.880
|
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there real viruses in nature is secondary to the fact that so much of the
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01:54:21.880 --> 01:54:25.920
|
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technology necessary to make it appear as though there was a pandemic was
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01:54:25.920 --> 01:54:31.880
|
|
already rare to go and I think the best way to look at the no-virus people is
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01:54:31.880 --> 01:54:39.600
|
|
just go back to 2020 go back to 2020 and watch a few Andy Kaufman Andrew
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01:54:39.600 --> 01:54:45.480
|
|
Kaufman lectures and you'll see that I'm totally right because in those
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01:54:45.520 --> 01:54:50.360
|
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lectures he doesn't talk about there being no virus he talks about them being
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01:54:50.360 --> 01:54:55.880
|
|
unable to isolate it he talks about them lying about it and he talks about them
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01:54:55.880 --> 01:55:01.560
|
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probably being exosomes and the PCR is just detecting that that the that the
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01:55:01.560 --> 01:55:06.200
|
|
sequencing reaction is really amplifying amplicons it could easily be parts of
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01:55:06.200 --> 01:55:12.480
|
|
the human the human genome or the human proteome and if you do that and then
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01:55:12.480 --> 01:55:17.120
|
|
use a computer program to assemble them into a coronavirus it's not the same
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01:55:17.120 --> 01:55:23.320
|
|
thing as finding a coronavirus and all of those arguments from 2020 of the no
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01:55:23.320 --> 01:55:32.000
|
|
virus people are totally 100% right and then they stopped and then they started
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01:55:32.000 --> 01:55:39.440
|
|
talking about foyas and they started talking exclusively about isolation
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01:55:39.440 --> 01:55:45.320
|
|
and purification and they made it seem like that was because this is the
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01:55:45.320 --> 01:55:52.160
|
|
argument this is how you win but it's not that's not how you win that's how you
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01:55:52.160 --> 01:55:57.440
|
|
stall people out and that's how you get people asked the wrong question I'm
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01:55:57.440 --> 01:56:00.800
|
|
convinced of it otherwise they would have been saying a long time ago that the
|
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01:56:00.800 --> 01:56:04.720
|
|
protocols are murder and transfection is a medicine and we don't think there are
|
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01:56:04.720 --> 01:56:09.000
|
|
real viruses but instead they just say we don't think there are real viruses we
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01:56:09.000 --> 01:56:14.360
|
|
don't want to talk to anybody who doesn't think the same it's ridiculous and so
|
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|
|
01:56:14.360 --> 01:56:19.360
|
|
in this conflated background signal the PCR test used in 2020 in 2021 were not
|
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|
01:56:19.360 --> 01:56:23.960
|
|
specific for a particular coronavirus the PCR tests have many sources of false
|
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|
01:56:23.960 --> 01:56:30.680
|
|
positives besides high cycle count including human transcripts the respiratory
|
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|
01:56:30.680 --> 01:56:34.120
|
|
disease that leads to a secondary ammonia is a regular cause of death that we
|
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|
01:56:34.120 --> 01:56:40.720
|
|
stopped treating appropriately in 2020 say it again respiratory disease that
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|
01:56:40.720 --> 01:56:44.080
|
|
leads to secondary pneumonia is a regular cause of death that we stopped
|
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01:56:44.080 --> 01:56:52.080
|
|
treating appropriately in 2020 in 2021 and I have been saying this for years
|
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|
01:56:52.080 --> 01:56:58.200
|
|
years changing the standard protocols for treatment of a general respiratory
|
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|
01:56:58.200 --> 01:57:01.240
|
|
disease that was the primary cause of excess death during the pandemic
|
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|
|
01:57:01.240 --> 01:57:04.800
|
|
additional harms were also caused by the response that included lockdowns
|
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|
01:57:04.800 --> 01:57:09.400
|
|
etc. Additional arms can also be matched to the use of specific agents
|
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|
01:57:09.400 --> 01:57:13.360
|
|
including Madazlam and Rendezivir. Her early treatment must be considered
|
|
|
|
01:57:13.360 --> 01:57:18.520
|
|
protocol by protocol because no single agent is likely to have been the silver
|
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|
|
01:57:18.520 --> 01:57:22.760
|
|
bullet for whatever they sprayed distributed or lied about and it certainly
|
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|
|
01:57:22.760 --> 01:57:26.040
|
|
wasn't going to cure anybody that was being improperly ventilated or treated
|
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|
|
01:57:26.040 --> 01:57:30.960
|
|
with Remdesivir. We spend money to make sure the danger of zoonotic pandemics
|
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|
|
01:57:30.960 --> 01:57:36.200
|
|
is taken very seriously that's really the bottom line if we spend money to get
|
|
|
|
01:57:36.200 --> 01:57:42.240
|
|
papers published that that claim pandemic potential and we we fund
|
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|
|
01:57:42.240 --> 01:57:46.680
|
|
organizations like the Equal Health Alliance to make sure that people think
|
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|
|
01:57:46.680 --> 01:57:52.280
|
|
that there's pandemic potential and and Nathan Wolf's organization metal
|
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|
|
01:57:52.280 --> 01:58:01.200
|
|
biota same thing it is the governing forces trying to set up this mythology
|
|
|
|
01:58:01.200 --> 01:58:08.320
|
|
this mythology of a natural pandemic and a man-made one and unavoidable because
|
|
|
|
01:58:08.320 --> 01:58:14.560
|
|
with climate change and our population and deforestation and guess who's one of
|
|
|
|
01:58:14.560 --> 01:58:24.000
|
|
the biggest donors of Equal Health Alliance palm oil companies palm oil
|
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|
|
01:58:24.000 --> 01:58:33.680
|
|
companies deforestation donating to to organizations that are helping with
|
|
|
|
01:58:33.680 --> 01:58:42.040
|
|
climate change is a great way to launder money for palm oil companies
|
|
|
|
01:58:42.200 --> 01:58:46.240
|
|
ladies and gentlemen you can tell the liars because they're not talking about
|
|
|
|
01:58:46.240 --> 01:58:49.600
|
|
the PCR anymore they're not talking about variants and sequencing fraud
|
|
|
|
01:58:49.600 --> 01:58:52.160
|
|
they're not talking about death certificate fraud that happened from
|
|
|
|
01:58:52.160 --> 01:58:58.760
|
|
California to New York and not talking about purity fraud protein folding
|
|
|
|
01:58:58.760 --> 01:59:03.240
|
|
transfection in general and they forgot completely about natural immunity that
|
|
|
|
01:59:03.240 --> 01:59:08.000
|
|
I was talking about in 2020 so that's how you tell they're doing this for a
|
|
|
|
01:59:08.000 --> 01:59:11.760
|
|
reason because they've got only this chance to get this many people on board
|
|
|
|
01:59:11.760 --> 01:59:15.680
|
|
to brainwash this many people to collect this much data that's really all
|
|
|
|
01:59:15.680 --> 01:59:20.600
|
|
this is about they don't need all of us they need our kids time they've got 30
|
|
|
|
01:59:20.600 --> 01:59:24.720
|
|
years they've got 40 years and in 40 years I might be dead so it's only my
|
|
|
|
01:59:24.720 --> 01:59:29.720
|
|
sons that'll be here and those are the ones they're trying to get not us
|
|
|
|
01:59:29.720 --> 01:59:33.120
|
|
ladies and gentlemen intramuscular injection of any combination of
|
|
|
|
01:59:33.120 --> 01:59:36.600
|
|
substances with the intent of augmenting the immune system is dumb and
|
|
|
|
01:59:36.600 --> 01:59:42.440
|
|
transfection is not immunization please stop all transfections in humans
|
|
|
|
01:59:42.440 --> 01:59:49.880
|
|
full stop full stop please just really stop it stop it all don't do it any more
|
|
|
|
01:59:49.880 --> 01:59:55.840
|
|
please get in there right there yes Mike Vandenberg mixed-day no that's not
|
|
|
|
01:59:55.840 --> 02:00:01.640
|
|
what I did I did this one oh I see
|
|
|
|
02:00:01.640 --> 02:00:09.080
|
|
I don't know what to say ladies and gentlemen I hope that the surprise was
|
|
|
|
02:00:09.080 --> 02:00:14.040
|
|
worth it I hope that you weren't let down we have 137 viewers which is a new
|
|
|
|
02:00:14.040 --> 02:00:19.040
|
|
record for giga-home biological so maybe my voice did something for us ladies and
|
|
|
|
02:00:19.040 --> 02:00:21.800
|
|
gentlemen stop all transfections and humans because they're trying to eliminate
|
|
|
|
02:00:21.800 --> 02:00:26.160
|
|
the control group by any means necessary this has been giga-home biological a
|
|
|
|
02:00:26.160 --> 02:00:29.840
|
|
high-resistance low noise information brief brought to you by a biologist it's
|
|
|
|
02:00:29.880 --> 02:00:38.320
|
|
21st of October 2023 this is day 46 in a run of several hundred so grab your
|
|
|
|
02:00:38.320 --> 02:00:44.720
|
|
popcorn and your hot tea and I will see you again tomorrow ladies and gentlemen
|
|
|
|
02:00:44.720 --> 02:00:51.480
|
|
hopefully the voice will be the same or even deeper yeah I still have a little
|
|
|
|
02:00:51.480 --> 02:00:54.000
|
|
you know I gotta
|
|
|
|
02:01:00.120 --> 02:01:15.480
|
|
thanks a lot Pamela thanks everybody for all your support it's really been
|
|
|
|
02:01:15.480 --> 02:01:21.280
|
|
unbelievable and I don't know what to say other than I'm when I coughed that
|
|
|
|
02:01:21.280 --> 02:01:25.160
|
|
thing up this morning and I spoke to my sons I started crying pretty fast
|
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|
|
02:01:25.240 --> 02:01:30.440
|
|
afterward because it I've been saying it for a long time if you give me my
|
|
|
|
02:01:30.440 --> 02:01:36.920
|
|
voice back I'm gonna definitely use it and here we are so it's not a matter of
|
|
|
|
02:01:36.920 --> 02:01:40.280
|
|
what is true the counts but a matter of what is perceived to be true ladies and
|
|
|
|
02:01:40.280 --> 02:01:45.880
|
|
gentlemen so let's start teaching biology share this stream please ladies and
|
|
|
|
02:01:45.880 --> 02:01:49.680
|
|
gentlemen share my work that's the best way to support it I love you guys see
|
|
|
|
02:01:49.680 --> 02:01:51.960
|
|
tomorrow
|
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|
|
02:01:55.160 --> 02:01:57.220
|
|
you
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|