{How Pfizer carried out the biggest pharma trial heist ever & the regulators swallowed it—hook, line, & sinker}
• Evidence Blog By: Arkmedic 10.12.25
• Remember this? (@Jikkyleaks)
“Pfizer’s vaccine is more than 90% effective”
2) • Headlines repeated around the world & more importantly by the regulators FDA, TGA, EMA & MHRA
• The “real” statistic was actually 95%
• Yep, Pfizer & the FDA concluded - after one of the quickest & largest randomized controlled trials in pharma history - that receiving a Pfizer COVID vaccine would give you only 5% of the risk of “catching COVID” than someone who didn’t receive their product
• Just to reiterate - this was about COVID infection
• No claims on severity, hospitalisation or death were made by Pfizer
• The FDA agreed that Pfizer’s trial showed that for every 100 people who were not vaccinated & “got COVID” only 5 vaccinated people would “get COVID”
• & remember this is COVID infection (testing positive), not anything else
• FDA’s analysis of the available efficacy data from 36,523 participants 12 years of age & older without evidence of SARS-CoV-2 infection prior to 7 days after dose 2 confirmed the vaccine was 95% effective (95% credible interval 90.3, 97.6) in preventing COVID-19 occurring at least 7 days after the second dose (with 8 COVID-19 cases in the vaccine group compared to 162 COVID-19 cases in the placebo group)
• Putting this another way, for every vaccinated person you met who had COVID you should have met at least 24 vaccinated people that didn’t ever have COVID
• Given that most of the vaccinated population actually “got COVID” - many of them multiple times, that sounds impossible, right?
• That’s because it was
• Yet the trial nejm.org/doi/full/10.10…
itself showed 95% reduction in the risk of infection & was published in the infamous New England Journal of Medicine (the same journal that published the fraudulent Surgisphere study) on the 10th December 2020 science.org/content/articl…
3) ~ Dates Matter ~
• As a background to the first red flag concerning this trial & subsequent “emergency approval” of the Pfizer COVID-19 vaccine it is worth noting some dates:
• The first patient recruited to the study was July 27th 2020
• By 31st August 2020 half of the participants had been recruited, meaning that less than half the participants had follow-up of at least 75 days from the first injection
• Given that you were supposed to need two weeks after the second injection (35 days) for it to “work” this means that half the participants had follow up of less than 47 days for the “effective dose”
• The original submission from Pfizer to the FDA happened on November 20th 2020
• The “data cut-off” for the trial - the last day that COVID infections could be registered - was November 14th 2020
• The VRBPAC meeting (Vaccines & Related Biological Products Advisory Committee) at the FDA met on the 10th December 2020, the same day the trial was published
• The VRBPAC assessment document for the Pfizer submission was written on the 7th December 2020, just two weeks after the submission was made - & having had to assess a trial with 44,000 participants
• This median of 47 days was the basis on which the approval was given, but it gets worse - much worse
• In fact we are going to show that the whole study was a sham & that there never was a benefit - at all, never mind “95% reduction in infection”
• Here is the chart provided by Pfizer that they used to show that there was a 95% reduction in infection
• It’s impressive
• The red line is the “placebo” group & the blue line is the “vaccinated” group
• And although they initially start off getting infected at the same rate - after about 10 days after the first jab, the vaccinated pretty much stop getting infected at all
• A true miracle vaccine
4) • Note that his chart is by “day after dose 1” & not “day of the year” or “day of the trial”
• The point of mentioning the dates is not only to show that the approval was made on the basis of 47 days of follow-up for most patients but was also made in 1 day, because the VRBPAC meeting was the 10th December 2020 & the EUA approval was declared on the Dec 11, 2020 archive.md/BP7bC
• It is of course not possible that such a decision could have been made overnight & so the implication is that this was a pre-agreed approval & all that needed to happen was that Pfizer provide data that shows that, in the group that were followed up for more than 35 days, there were less infections in the vaccination group
• & we are going to see that this was all planned to happen by around the 20th of October, around 4 weeks before the data cut-off date
5) ~ What’s COVID According To Pfizer? ~
• Here comes the next important part of the hustle
• For most of us, “COVID” is a clinical syndrome signified by a viral infection that causes symptoms
• Those symptoms invariably involve a fever & lethargy
• For some people it involves a cough or runny nose
• And when “severe COVID” happens, if it does, that almost always involves a post-viral pneumonia - just like the 1918 “Spanish flu” & basically every other respiratory virus ever - as I wrote about extensively here arkmedic.info/p/there-was-no…
6) • If you don’t have any symptoms you can’t really have “COVID” or any similar illness of any significance
• Testing positive on a PCR test is irrelevant if you don’t have symptoms (why are you even testing?) but if you do have symptoms it’s highly predictive of a viral infection with SARS-Cov-2
• So you would think that the definition of “COVID” in the Pfizer trial was something like “symptoms of respiratory viral infection with fever cough & a positive PCR or lateral flow test conducted at the local health authority” wouldn’t you?
• Oh no
• This is the case definition in the Pfizer protocol
• Efficacy will be assessed:
• If, at any time, a participant develops acute respiratory illness (see Section 8.13), for the purposes of the study he or she will be considered to potentially have COVID-19 illness
• the participant should contact the site, an in-person or telehealth visit should occur, & assessments should be conducted
• will include a nasal (midturbinate) swab, which will be tested at a central laboratory using a reverse transcription–polymerase chain reaction (RT-PCR) test
• The central laboratory NAAT result will be used for the case definition
• There is one phrase hidden in there that not many people noticed but prompted this tweet over 3 years ago
7) • And the phrase of interest is “The central laboratory NAAT result will be used for the case definition”
• The tweet is basically asking why - when a large proportion of the trial participants were recruited in Argentina - you would send your “suspected COVID” swab all the way to New York
• Well the answer becomes obvious when you realise what the “central laboratory” is - it’s Pfizer’s lab in Pearl River, New York
• How do we know that?
• Because it’s in the documents that Pfizer & the FDA tried to withhold for 75 years - until Aaron Siri took the FDA to court to provide those very same documents phmpt.org/pfizer-16-plus…
8) [It’s worth noting at this point that those documents in total work out at over 2 million pages, so I hope readers will forgive me for taking a long time (arguably 3 years) to produce this article which is based on analysing & verifying the data in them}
• It’s a lot of work, & anybody who’s looked at these files will know that it’s not possible to review them properly in 2 weeks
• And here is the confirmation that the “central laboratory” was at Pfizer’s vaccine HQ
• Which means that the people that decided whether a swab would be marked as PCR positive or negative - which was the only test that mattered - were Pfizer
• Nothing to see there, obviously, But it gets better
9) ~ VRBPAC SHMERPAC ~
• The FDA’s VRBPAC meeting was held on the 10th December 2020 & comprised a bunch of people who appeared completely incompetent - & in some cases didn’t appear to know what time of day it was, or how to use zoom
• Except Doran Fink,
(linkedin.com/in/doran-fink-…) who gave a polished presentation, that almost looks like it was written for him, explaining how the FDA had been investigating this trial data “for months”
• That was despite (supposedly) having no clinical data in that time - so that was not possible
• To clarify, unblinding in the trial was not allowed to have happened until after Nov 14th, 2020, so it seems that Doran is throwing Pfizer under the bus by telling us that there was some way that Pfizer knew who was in which arm before the 14th November
• Neither was it possible for Doran Fink himself to have analysed such a quantity of data because he had no experience in handling large clinical data sets, so it certainly wasn’t him that did that analysis pubmed.ncbi.nlm.nih.gov/?term=fink%2C%…
• Doran was rewarded with a plum job at Moderna sharylattkisson.com/2023/11/bmj-in… for his efforts to put lipstick on the Pfizer trial data…
• & if that wasn’t good enough he’s now rocking it at the home of the pharma vaccine cartel - GSK
11) • Which was all a bit naughty because, if the data cut off was the 14th Nov. Pfizer couldn’t have known before that date that they had achieved anything at all, unless the “unblinded team” that they conveniently had as part of their protocol had told them arkmedic.info/publish/post/1…
• And although they had an “unblinded team” who knew which patients were in which groups they didn’t need that information, because they had another way of finding out, which we’ll come back to soon
12) ~ What Did Doran Do? ~
• Well, apart from earning himself a cushy job sharylattkisson.com/2023/11/bmj-in… with pharma (twice), after selling the COVID vaccine efficacy line to the world in order to get the EUA (emergency use authorization) approval done & dusted in less than 24 hours, the answer is likely not very much at all archive.md/BP7bC
• It is also worth an honourable mention to Moderna here, who managed to achieve a similar EUA approval only 7 days later (having played the same “central laboratory” trick) archive.md/lEd4P#selectio…
• Yes, that’s right, while Fink & crew were giving up their thanksgiving Turkey to sift through the 44,000 clinical trial participants data for Pfizer they were also apparently “thoroughly assessing” the 30,000 participant Moderna trial
• Either that, or any analysis they pretended to do was ghost written for them by pharma (again)
• But getting back to the Doran Fink analysis of the Pfizer trial…
• At the VRBPAC meeting itself it was actually Susan K Wollersheim who gave the statistical presentation
• Her ability to analyse a 44,000 participant clinical trial in record time is legendary as she has never published a clinical research study
• Therefore the probability of Wollersheim having analysed this 44,000 participant data is close to zero
• Here she is with her blue light filter glasses on noting that the FDA also had the inside information on the fabulous “95% efficacy” figure in October
13) • Of course only a cynic would suggest that this “miraculous” result could have been revealed to the US population before the 2020 election blog.maryannedemasi.com/p/pfizer-accus… so that they didn’t have to set up special ballot drops but that’s a story for another day imdb.com/title/tt189245…
• If you actually watch the VRBPAC monologue youtube.com/live/owveMJBTc… from the blue-tinted Wollersheim you can see that she is just reading a script
• It’s no surprise because there is no way that these people were doing this analysis
• They don’t have the skill set & the amount of work required is incredible - particularly for someone who is a practising doctor & therefore doesn’t have the time
• For context, what you will see below in my analysis is just a part of what we have been working on for over 3 years
• When I say “we” I mean a handful of people with the skillset to look through the Pfizer data that was eventually released over 2 years by the FDA
• That was the expedited release after the court quashed the FDA’s attempt to take 75 years to release that data econotimes.com/Judge-Forces-F…
• It is literally millions of pages econotimes.com/Judge-Forces-F… & there is not a chance in hell that the Susan Wollersheims of the world could have provided a full re-analysis of the data in two weeks
• Just working on this one aspect of the Pfizer data fraud (the subject of this article) has taken me 3 years on & off
• In comparison, one of the data reviewers from the FDA, Ye Yang, the lead statistician at the FDA, concluded in just a few weeks:
• No major statistical issues were identified for the safety data during review
• A higher percentage of subjects in the BNT162b2 group reported solicited local & systemic reactions than placebo recipients in both the younger (16 to 55 years) & older (>55 years) adult age groups after each dose
• There were no major imbalances in reported SAEs, AEs leading to withdrawal, or deaths between the treatment groups at one month & up to six months after the second dose or unblinding/data cut-off
(b) (6)
• There is evidence of reactogenicity associated with BNT162b2; the overwhelming majority of events were of mild or moderate severity & short duration
• There was no evidence of increased risk of unsolicited SAE or death associated with BNT162b2 in Study C4591001
• I defer to Drs. Susan Wollersheim & Ann Schwartz’s clinical review memo on the overall safety conclusion for BNT162b2
• Nice job, Ye Yang
• Not a single mention of Brook Jackson’s fraud complaint registered with the FDA in September 2020 bmj.com/content/375/bm…
• Everything rosy in the garden
• So I think we can safely say that the FDA have no interest in looking for fraud in these kind of trials
• In fact it’s very likely that the FDA didn’t analyse anything at all other than rehashing what Pfizer gave them
• What nobody has done is what I’m going to show you now
14) ~ The Pfizer Heist ~
(aka “how they did it”)
Background
• To understand what Pfizer needed to fake the trial result requires asking two questions:
1- How many infections should there have been in each group if the claims were true?
2- Did the antibody testing corroborate the numbers?
• So, let’s start with looking at the number of positive tests according to Pfizer
• This is directly from Susan Wollersheim’s presentation, cropped for readability
15) • I’ll just explain the numbers for a minute, because it’s important
• The first line shows 50 cases in the vaccine arm & 275 cases in the placebo arm for an overall efficacy of 82% (that is, 50 cases is 82% less than 275 cases for a similar number of participants in each arm).
[For the record, these numbers (50 vs 275) change slightly depending on which files from the Pfizer dump are used as you might notice in the charts below.]
• The second line is where the 95% comes from, when counting cases only happening after 4 weeks from the first jab
• And this is where the miracle comes in because, basically, they stopped accumulating cases (in the vaccinated group only) for a specified time period in order to make the cut
• In order for this to happen there either had to be a magic trick or the vaccine really works (& your 24 vaccinated friends who got COVID must have imagined it)
• Just to set the scene as to how the trick happens here’s a little reveal of a Penn & Teller (incidentally not nice people) sketch where the punter believes that the magicians correctly guessed the right amount of money in her hand
• In fact they had created the scene in such a way that whatever amount of money she picked up, the pizza guy would ask for the right amount
• And it’s a bit like that with the Pfizer C4591001 study which sold the vaccine to the world…
• They knew they were going to hit the “95% reduction” from the beginning
• I’ll show you
16) ~ The PCR Hustle ~
• Let’s start with the PCR tests
• This is a recreation of the PCR test results from one of the documents released in the first tranche of the Pfizer FOI release (in 2022), but instead of plotting the graph as “days from dose 1” we plot the graph from “days from the start of the study (i.e. 27th July) phmpt.org/pfizer-court-d…
17) • You can see that the numbers match the provided data (275 vs 50 cases) so that’s a good sanity check & in fact we can recreate the “days from dose 1” graph from the same data, just to confirm that we have the correct data
• Now, other than the fact that the vaccine group has much fewer cases overall I hope you can tell that there is something else odd about the vaccinated line
• Firstly, the cases start to accumulate at a similar rate to the unvaccinated & secondly there is a flattening in the middle, as if there’s a pause
• We can look at this better in this graph
18) • You should be able to see that up to the 6th September (about 5 weeks into the study when recruitment is increasing rapidly) there is a rapid rise in the number of cases in the vaccine arm & then this suddenly slows down until the 21st October when the rise rate goes back to normal
• This only happens in the vaccinated group
• It’s as if someone switched the machine off, or turned it down somehow
• Now going back to our pizza analogy remember that the pizza delivery guy had to quickly adapt & print his ticket to match the amount of money that they knew the lady had picked up
• It’s the same here
• In this chart the dotted line is the modelled12 (predicted) number of cases in the vaccine arm, assuming that the vaccine was 95% effective “after 4 weeks” as they said
19) • I have marked the inflection points on the curve & you might imagine the Pfizer people down at Pearl River doing something like this:
(A)
“Oh shit Albert we haven’t had any cases at all people will think there is something up & we need some cases to be believable so we better start collecting them, Turn the machine up*
(B)
“Whoa Albert turn that machine down you’re going to catch up with those pesky placebos if you don’t watch out & we’ve got all the cases we need now to look convincing. Don’t get any more cases before the 20th October or we’re in the shit”
(C)
“OK Albert you can turn the machine back up again now, the cases don’t count as long as they’re all recent recruits”
*By ”Up” of course I mean “Down” because the easiest way to impact whether you pick up any cases on a PCR test is just to adjust the Ct value (cycle threshold) for a positive test (who.int/news/item/20-0…)
• If the Ct is very high (over 40) you will pick up a bunch of false positives & if it’s very low (say, less than 16) you will only pick up the real cases with a high viral load
• Of course they wouldn’t know what the “sweet spot” would be which is why they would have had to change it as they went along
• And you might say “why didn’t they just record the tests as positive or negative in the case report forms?”
• Well that’s possible but some of the testing is automated so they can’t manually record false values for POSITIVE/NEGATIVE & if they did it might be very obvious on an audit
• What they could do was change the Ct threshold on the machine recording the tests so that they don’t record as positive
• We don’t know whether that happened because the field that should have recorded it & should have been released in the Pfizer files (MBORRESU) is missing
• So convenient
• But one thing we DO know is that Pfizer knew which tests were coming in from which arm of the study (vaccinated or placebo) & that is because they had the blood tests from every person in the study at the Pearl River lab
• And all they had to do to identify which subject was vaccinated or not is test the blood
• We know this to be true because Castruita showed in 2023 that even after 4 weeks there was enough circulating RNA (or DNA) from the COVID-19 vaccines to be able to perform genomic sequencing pmc.ncbi.nlm.nih.gov/articles/PMC10…
20) • In a highly controlled pharma randomised trial the databases holding information about which patient took which treatment (in this case vaccine vs placebo) are locked
• Unlocking them would create audit flags and so the FDA would be able to see that there had been tampering
• So it wasn’t possible to just cheat in the database
• But, because Pfizer already had the blood samples from every participant at the same lab that they insisted that the “cases” send their swab samples to, it was easy for them to record which sample was in which arm of the study
• The placebo tests could therefore just continue on the standard test machine & the vaccine arm group (having been identified from their own record of who was who, based on the blood tests) on another machine
• And because they knew from the placebo arm how many patients so far had got COVID, they just needed to adjust the “vaccinated” machine up or down according to the number of positive tests they needed
• A bit like the pizza guy
• But, you’re going to say, this is “conspiracy theory” & “there is no way to prove it” right?
• Well unfortunately for Pfizer they made a few mistakes & the big one was failing to fix the N-antibody (Nab) tests at the same time
21) ~ NABs Schmabs ~
• When you “get COVID” naturally, what happens is that your immune system produces two sets of antibodies
• One is directed against the spike protein (S-antibody) & the other is directed against the nucleocapsid (N-antibody)
• The nucleocapsid is inside the virus particle so in order to be exposed to it you need to have the virus spill its contents
• This will usually happen when your immune system kills the virus, so a natural immune response provides both sets of antibodies (anti-S & anti-N)
(frontiersin.org/journals/micro…)
22) • In contrast, following vaccination the spike gets flooded with antibodies & the immune system may not get the same exposure to the Nucleocapsid as in natural immunity, so the chance of showing N-antibodies (“NABs”) after a post-vaccine infection (which weren’t supposed to happen of course) is much lower
• How do we know?
Well the manufacturers told us
• Here is the chart from Lindsey Baden’s paper from the Moderna trial where they looked at exactly this question acpjournals.org/doi/10.7326/M2…
23) • The chart shows the probability of a “Anti-N serology test” being positive during the Moderna vaccine trial & the bottom line is that at for most infections (other than the most severe, so about 95% of all recorded infections in the trial) the chance of testing positive on a Anti-N serology test was 2.3x lower (93% vs 40%) in the vaccinated group
• The same result was seen by Dhakal et al so this wasn’t just a ruse by Moderna to create some narrative that the COVID vaccines prevented severe disease (which was always the back up story & never shown in a randomised controlled trial)
• But the backup story by Baden shot Pfizer in the foot
• So let’s look at what happened in the Pfizer trial
• Here are the N-antibody tests for each arm
24) • The blue dotted line is the total number of positive N-antibody tests in the vaccinated arm & is 11616
• But wait, there were only 50 infected cases reported in the study by PCR
• That can’t be right surely?
• You couldn’t have more than twice the number of cases of antibody-proven infection than PCR-documented infection in one group only - unless you were suppressing the PCR tests
• But it gets worse when you correct for the fact that, if you’re vaccinated, you have 2.3x less chance of showing N-antibody on a test
• So let’s correct the chart & show what the real infection rate was in the two groups
• Et voila…..
25) • Well look at that
• Pretty much identical curves
• What that graph shows is that, even according to Pfizer’s own data, the antibody-documented infection rate in both arms was pretty much the same
• No “95% reduction in infection” at all
• It was only the recording of the PCR tests that was different
• So it was a scam
• But of course you’re not going to believe that it was a scam because the next thing you’re going to say is “well they said it reduced severity so it doesn’t matter”
• Well they didn’t say that
• What they claimed was that the infection rate was less
• But what Pfizer were actually saying was this:
• In our large randomised controlled trial, the chance of a vaccinated person testing positive in our lab on our dedicated PCR machine was 95% less than an unvaccinated person testing positive
• It doesn’t sound such a good sell now does it?
• But this isn’t the end of the matter, because I know you’re going jump up & down & demand that the Pfizer vaccine trial showed that there were less symptoms suggestive of COVID in the vaccinated
• So let’s go there
26) ~ Muh Symptoms ~
• It was, in fact, the FDA that said (in their super intense thanksgiving-Turkey-sacrificing analysis that they spent at least 3 hours on)
• Among 3410 total cases of suspected but unconfirmed COVID-19 in the overall study population, 1594 occurred in the vaccine group vs 1816 in the placebo group
• Suspected COVID-19 cases that occurred within 7 days after any vaccination were 409 in the vaccine group vs 287 in the placebo group
• It is possible that the imbalance in suspected COVID-19 cases occurring in the 7 days postvaccination represents vaccine reactogenicity with symptoms that overlap with those of COVID-19
• “Suspected COVID” means that you felt like crap, had a fever, & probably had a cough or runny nose
• Just like every other respiratory viral infection which you normally recover from in a week
• So in the first week after vaccination you were much more likely (42%) to feel like crap with symptoms that felt like COVID, but over the rest of the time you were slightly more likely to think you had COVID (13%) if you didn’t have the vaccine
• What a trade off
• And if you want to compare these “symptoms” you can see clearly from this graph that the first week is worse for the vaccinated & then over time the placebo group sort of do worse - but it’s probably not enough to make up for the first week’s disaster
27) • So, what exactly was this miracle vaccine preventing?
• Well the worst thing about COVID, apart from the very small number of people who get post-viral pneumonia, is the fever - which makes you feel like crap and stops you going to work
• So presumably, if the MiracleVax™ was preventing this nasty viral infection by 95% then we should be able to see this reflected in the fevers
• As in, if you take away all the statistical nuances & PCR tests & bla bla bla there MUST be a benefit for Pfizer’s victims customers of preventing the fevers that stop you going to work
• Because otherwise, given there were no differences in overall deaths (actually the vaccinated group did marginally worse on that score too), then there has to be something that it actually worked for, given the dramatic 95% reduction in infection
• Right?
28) ~ Who got the Fever? ~
• Well, now we get into the nitty gritty of whether there was any way at all that the Pfizer trial “success” was real..
• the fevers (& their sister symptoms chills, which if you’ve ever had a bad fever you will know is not something to be sniffed at)
• You see, what the FDA failed to spot, whilst lauding the minor reduction in allocated “symptoms” from the vaccine, was the fever elephant in the room
• These are the numbers directly from the FDA’s review
29) • That is, there were over 1100 more fevers and over 2000 more reports of chills
• But you were stoked about the apparent 222 fewer people with “symptoms” in the vaccinated group, right?
• It’s worth noting at this point that this was followed into the real world with reports of healthcare workers having to take time of sick from work - with vaccine related fevers - 29% reported in the report from Lidström (sciencedirect.com/science/articl…) from the Pfizer vaccine alone, & with up to 48% of health care workers taking time off work from all symptoms following vaccination
• So, let’s get this right
• Not only did the vaccine not prevent transmission (news.com.au/technology/sci…) but you needed to take it to stop yourself getting sick enough that you couldn’t work, by getting sick enough that you couldn’t work
• The memes sort of write themselves don’t they?
30) • So what happens when we look at overall numbers of “fever or chills” in the whole trial irrespective of cause?
• Because if our MiracleVax™ really did work, then the NEJM were right & overall there would be a bunch less fevers or chills in the vaccinated group
• Well here you go
• Here’s the definitive analysis (that the FDA never did) looking at whether fever & chills - the major symptoms of “COVID” - were less in the placebo (blue) or vaccinated (red) arm
31) • Remember that this includes fevers & chills from all causes, including “COVID” & showed that the chance of getting fevers or chills if you were vaccinated was over double that of the unvaccinated
• It’s a slam dunk wouldn’t you say?
• All that money spent, all the hand waving about how the COVID vaccine was “95% effective at preventing COVID (whilst not actually showing a mortality benefit)”, all the cheating at trial centres, (openvaet.substack.com/p/pfizerbionte…) all the suppression of dissent (dailymail.co.uk/news/article-1…) from people who actually knew what they were talking about…
• All for a fraud that the CDC knew was a fraud the first time that not a single case was prevented in the largest public gathering after the vaccine rollout in Barnstable, Masschusetts in July 2021 - where a large COVID outbreak occurred in a fully vaccinated population
32) • And not a single “expert” on any of the panels - who were desperate to cross Pfizer’s palm with the public’s silver so they could get their subsequent awards & promotions - spotted the massive & obvious scam, or realised how they did it
• First off, Lyndsey—your story hits like a gut punch & a rallying cry all at once
• Four years of pre-treatment records painting a clear baseline, followed by post-therapy proof of amyloidogenic fibrinogen clot clearance & normalized cytokine levels?
• That's not just data; that's a beacon for every vaccine-injured person dismissed as "anxiety" or "long COVID” overlap
*** You're not just fighting for you—you're the proof-of-concept patient in a protocol that's already showing promise in niche circles ***
• @KevinMcCairnPhD’s amyloid fibrin microclot approach (stem cell growth factors, targeted fibrinolytics, & adjuncts like nattokinase or EDTA chelation) aligns with emerging research on spike protein-induced anomalies
• If replicated, this could rewrite the narrative from "untreatable" to "targetable."
• But will it scale to mass adoption & flip the script on pharma accountability?
• Let's break it down realistically, based on the science, trends, & barriers as of November 2025
~ The Science: Solid Foundation, But Replication Is Key ~
• Your results echo peer-reviewed work on amyloidogenic fibrin microclots—resistant, spike-triggered structures that trap inflammatory cytokines (like IL-6) & evade standard fibrinolysis
• These aren't your garden-variety clots; they're amyloid-like, prion-esque beasts linked to vaccine injury syndromes via S-protein misfolding
• Post-therapy clearance—That's huge—mirroring early trials with "triple" anticoagulants or nattokinase/bromelain/curcumin combos that dissolve these bad boys & drop cytokines
The CCR5 gene encodes a chemokine receptor that plays a critical role in immune cell function, particularly in the recruitment and activation of T-cells and B-cells
Below, I’ll explain how CCR5 influences T-cell and B-cell production, its potential to drive increased production, and the risks associated with chronic overproduction of these cells
1. How CCR5 Impacts T-Cell and B-Cell Production
- Role in Immune Cell Activation and Recruitment:
CCR5 is expressed on T-cells (especially Th1 cells), B-cells, macrophages, and dendritic cells
It binds chemokines (e.g., CCL3, CCL4, CCL5), which guide these cells to sites of infection or inflammation
This signaling enhances the activation and proliferation of T-cells and B-cells by amplifying immune responses
For example, CCR5 signaling can promote T-cell differentiation into effector or memory T-cells and enhance B-cell activation, leading to antibody production
- Stimulation of Proliferation:
CCR5-mediated chemokine signaling can upregulate cytokine production (e.g., IL-2, IFN-γ), which supports T-cell clonal expansion and survival
This indirectly boosts T-cell production in lymphoid organs (e.g., lymph nodes, spleen)
For B-cells, CCR5 signaling enhances their migration to germinal centers, where they undergo proliferation and differentiation into plasma cells for antibody production
This is particularly relevant in response to infections or chronic inflammatory signals
- Microenvironmental Influence:
In lymphoid tissues, CCR5 helps create a microenvironment that supports T-cell and B-cell interactions with antigen-presenting cells (e.g., dendritic cells)
This fosters higher production of activated T- and B-cells during immune responses
2. Mechanisms of Increased T-Cell and B-Cell Production
- Infections and Inflammation:
During infections (e.g., viral respiratory illnesses like influenza or SARS-CoV-2), CCR5 signaling is upregulated due to increased chemokine production
This drives T- and B-cell recruitment and proliferation to combat the pathogen
Chronic infections (e.g., HIV, hepatitis C) can lead to sustained CCR5 activation, resulting in prolonged T- and B-cell production
- Autoimmune and Inflammatory Conditions:
In diseases like rheumatoid arthritis or inflammatory lung conditions (e.g., asthma, COPD), persistent inflammation can maintain high levels of CCR5 ligands, leading to continuous T- and B-cell activation and proliferation
- Genetic Factors:
Variations in CCR5 expression or function (e.g., polymorphisms) can alter the intensity of immune responses
For instance, individuals with normal CCR5 function may experience robust T- and B-cell responses compared to those with the CCR5-Δ32 mutation, which reduces receptor activity
*** COVID Accountability Victory: Court Rules in Favor of Healthcare Whistleblower ***
~ An update on US ex rel. Conrad v. Rochester Regional Health System. ~
By: WARNER MENDENHALL
@MendenhallFirm
JUL 17, 2025
• For 21 years, Deborah Conrad served as a dedicated Physician Assistant
• She was fired from Rochester Regional Health for doing her job - reporting adverse events to protect public safety
• A federal court vindicated her actions and opened the door for accountability
• On June 11, 2025, the U.S. District Court for the Western District of New York issued a landmark ruling for my client, Deborah Conrad, in her case against Rochester Regional Health and United Memorial Medical Center
• Judge Sinatra denied the hospital's motion to dismiss the core claims in Deborah's False Claims Act lawsuit, letting her case go to discovery
• Here's what this means:
The Court Found:
•Rochester Regional Health had a material obligation to report serious adverse events to VAERS under their Provider Agreement with the CDC
•The hospital's failure to report while continuing to seek federal reimbursement was potential fraud against the government
•Deborah's detailed allegations were enough to meet the strict legal standards for fraud claims, even without access to internal billing records
•Her retaliation claim can move forward - the court found she was probably fired for trying to expose the hospital's failure to report adverse events
• This decision establishes critical legal precedents:
1VAERS Reporting is Not Optional:
• The court confirmed that adverse event reporting requirements are "material conditions of payment" - not just bureaucratic paperwork
2Hospitals Can Be Held Accountable:
• Healthcare providers who take federal money while failing to meet safety reporting obligations can face False Claims Act liability
3Whistleblowers Are Protected:
• The court recognized that employees who try to ensure proper adverse event reporting are engaging in protected activity
• Deborah's case involved 170 serious adverse events that the hospital allegedly prevented her from reporting
• 160 VAERS reports she successfully submitted on her own initiative
• Specific patient examples of adverse events following vaccination that went unreported
• The court found these allegations painted a picture of systematic non-compliance with federal safety monitoring requirements
• This ruling is significant beyond just Deborah's case
• It establishes that:
1) healthcare providers cannot ignore federal safety reporting requirements while continuing to collect taxpayer money
2) the False Claims Act can be used to hold institutions accountable for COVID-related misconduct
3) whistleblowers who expose these practices have legal protection
• We estimate over 500,000 were killed by the shots, millions lost their jobs for refusing them, and Big Pharma received billions for dangerous and experimental treatments
• This case reveals a legal pathway to begin holding the system accountable
• The case now moves to discovery, where we will seek the hospital's internal “vaccination,” treatment, and billing records to uncover the full scope of unreported adverse events which we believe are in the 1000s in this hospital system alone covidlawcast.com/p/covid-accoun…
1~ A THREAD EVERY HUMAN BEING NEEDS TO READ & WILL AFFECT EVERY PERSON ON THIS PLANET REGARDLESS OF VACCINE STATUS ~
~> Amyloidogenic Fibrin Microclotting Following Prenatal mRNA Vaccination Exposure <~
*** HOUSTON, WE HAVE A PROBLEM ***
(@KevinMcCairnPhD)
05.24.25 at 20:59
2~ PREAMBLE: Houston, WE HAVE A PROBLEM!
•Scientific investigations involving emerging & potentially paradigm-shifting findings often walk a difficult line between the need for caution & the imperative to inform
• While early publication of case studies carries inherent risks—such as overinterpretation of individual data points or lack of statistical power—it also provides critical, time-sensitive insights that can drive new lines of inquiry & inform ongoing clinical & public health departments
• This report forms part of a robust, real-time investigation into the proteopathic & vascular consequences of prenatal exposure to mRNA-based SARS-COV-2 “vaccines”
• The intention is not to draw definitive epidemiological conclusions at this stage, but to publicly document the emergence of novel findings as they occur
• This transparent approach is particularly important in areas where existing safety literature has not yet integrated proteomic misfolding or amyloidogenic biomarker screening into its framework
• This investigative format mirrors the best practices seen in real-time pathogen tracking & pharmacovigilance
• In such contexts, timelines & transparency are essential for mitigating long-term risk & prompting refinement of public health frameworks
~NOT SAFE & NOT EFFECTIVE: Full Evidence Dossier Packet~
*Prepared By: James Roguski* (@jamesroguski)
~Chapter 1: Evidence Dossier~
“The article discusses the urgent need for a global moratorium on COVID-19 mRNA vaccines due to their severe adverse events & unresolved safety concerns”
“The vaccines have been linked to a 6-fold increase in deaths, & their mechanism of action & potential harm are detailed in a comprehensive document”
“This free online resource provides EVIDENCE that the mRNA platform is a biological weapon delivery system & its ongoing & expanded use constitutes a grievous crime against humanity”
~ full evidence dossier packet below - use to follow along with this thread ~
(notsafeandnoteffective.com)
~ Chapter 2: A Letter to President Trump (@POTUS) ~