Host [00:05] So hello to everyone, we’re here with Christine Cotton, who just released a book on Covid-19 and Pierre vaccines, which is published on Twitter, notably under the pseudonym Cancer Mouse. And we’re going to go back to the different Pfizer trials and what we’ve got to say. On the one hand, for a long time, we will go back to the phase 3 trials that were released in December 2020 with Christine and also with Pierre on new elements that have come out more recently following the release of new documents that had been demanded for a long time. In my book, I talked a little bit about these essays in a chapter, both by reading the essays of Pfizer and Moderna, some conclusions that can come to any statistician, even a beginner, who reads the essays. And then, I also quoted Christine’s work that allowed us to see it a little clearer for a very long time in these essays. And today, I’d like to go back to these elements because the more things go, the more things go out, it’s going to be time to understand what was in these trials and what these different vaccines are giving. I’m going to let you each introduce your turn, Christine and Pierre, so that we understand who you are.

Christine Cotton [01:07] I am Christine Cotton, a biostatistician for the pharmaceutical industry for 23 years. I sold my company in 2018. I had a CRO, Clinical Research Organization, which was specialized in the management of data from clinical trials and post-MA surveys as well. I worked in more than 500 clinical trials in very different fields for large Roche-Sanofi laboratories, Aventis, Pierre-Fabre, Servier, etc. Janssen. And I was also a quality insurer of my company. So I know by heart all the so-called good clinical practices that must be followed when doing a clinical trial that includes a whole bunch of documents, rules to be followed by all those involved in a trial. So in January 2022 I wrote an expert opinion of the Pfizer clinical trial in relation to good clinical practice.

Host [02:08] Pierre, you can tell us in a few words who you are, what you did.

Pierre (OpenVAET) [02:13] Thank you Pierre. For my part, I started my career in economic intelligence, where I have a certain habit of forensics and large volumes of data. Then, I became a professional bettor. Today, I alternate a little between these two activities. I had to take an interest in the Pfizer essays, being prompted by a friend, Geoff Payne, who works in Australia on the issue. and that was about nine months ago and since then I haven’t been out of it so much and we stop exploring the galaxy of these key essays.

Host [02:52] Thank you Pierre and Christine, I propose that we start with the presentation, I believe that it is Christine who starts and will talk to us again about the different tests and we will go into good practice so as to show that in fact from very early we should have known, to realize collectively that the good practices being not respected we should not have put these products on the market.

Cotton [03:12] So what we need to understand, we have several kinds of documents. We have the documents that are available at each marketing authorization. So in December 2020, in January 2021, in October 2021, etc. That is, whenever there is a marketing authorization in the United States, we have deliberations on the IDF chain that are public. So we all have videos in which the speakers present a lot of documents, including the results.

So this is the very day of the deliberations. And on the IDF website, we have the reports that are reviewed that day, which are put online. So the first report in which we have these famous 95% effectiveness, So they date from December 2020. I started to look at these documents there and that’s what I wrote my expertise and then came the public documents that were released between quotation marks on November 17, 2021.

So on that basis we were able to explore PDF files. It was noted that there were a number of anomalies and that it was thought that this trial would be potentially fraudulent. So I say it in quotation marks since to attest to fraud, it would of course require an audit that I have been asking for since January 2022. So the normal process of a clinical trial is what I have just told you, it is extremely supervised by these famous good clinical practices.

So to make a brief reminder of the phases, we have phase 1 where we have a small number of healthy volunteers to test the safety of the product. So I say healthy because even when we have a product that is then intended for the sick, these, phase 1, they are never. That is, we look at normal people how the product is tolerated. Of course, on a vaccine, there are all kinds of volunteers. Phase 2 is to assess the safety and efficacy of the new product on a larger number of participants who normally have the disease that you want to treat. phase 3 we have several thousand subjects, so it depends, I have had lots of studies of phase 3 where I had only a few hundred, it is recalled that the number of subjects is a calculation that is carried out by the biostatistician during the writing of the protocol, At the same time of the feasibility study, since if I make a calculation where I say it takes 100,000 subjects, obviously the lab will answer me that it is not in its budget, so we will either have to change criteria or review what we measure.

So we can have several hundred, several thousand subjects who usually receive the product to be tested and placebo or another comparator that is already on the market. So obviously for vaccines, there we have the product, the vaccine and the placebo. And there, of course, one wants to look at the tolerance and above all the efficacy which is the criterion on which this calculation of number of subjects is made. Phase 4, the Phase 4 studies are post-AMM. And then, what we’re looking for in Phase 4 is eventually to detect rare side effects that we haven’t seen during the trials since we don’t have enough patients, and possibly also to look at the practices of environmental doctors. So, if John comes up with how these Covid trials went, we said x times, they have undergone a development accelerate phase 1. We don’t know too much, Peter, how many subjects we have in this phase 1.

Pierre [07:13] Indeed, the number varied from 830 to 640, then to 400, then to 195. So we’re pretty unsure of the number of subjects that would actually have participated.

Cotton [07:24] So in the database, we have 195, if I remember correctly. That’s, so phase 2, the results on phase 2 themselves, I’ve never seen them. No, it was completely merged with phase 3. That’s it. So phase 3, it is this famous efficacy confirmation study where we theoretically have several countries that are recruited, the two main ones being Argentina and the United States, which has almost included all the subjects out of the 44,000 recruited. Argentina has nevertheless done, I believe, 5,700 subjects. When we run PCR tests to confirm if the participants have a PCR-confirmed Covid, Pfizer sent them to the United States. So I’m going to let Pierre talk because he’s been digging this subject more than I am.

Pierre [08:21] So to sum up, subjects were tested according to protocol, locally and centrally, locally, because it was necessary to know quickly whether they had Covid and to allow them to prevent this deadly disease. And centrally, only the central test was liver. That is, even if there was a conflict, which happened fairly regularly between the central test and the local test, even if the machines were supposed to be fully reliable, only the result of Pearl River, a laboratory controlled by Pfizer, was liver at the end of the test.

Cotton [08:54] So here, we already see that from Argentina, it’s a nice little trip to send out the PCR tests. So that’s pretty classic in clinical trials, that we have local tests and a centralized laboratory. So normally, we can have this for biological tests, blood checks, because like that, we have the same standards everywhere. It allows us to analyze all the subjects with the same standards. Well, there, for the moment, at least 11 o’clock PCR tests, with 11 hours of journey, maybe they could have done better. So since it’s not my specialty, I don’t order.

Host [09:33] Is it possible to have a little accurate information on the importance of this topic of the PCR, since we are talking about a vaccine that it is supposed to protect not from having a disease, i.e., well-defined symptoms that form part of a list, but that the vaccine is supposed to protect from having a positive PCR test. And so the output you might be talking about later, but I’ll remind you right now. So it’s determining this history of the PCR since it’s the positive PCR that’s going to be counted as an output of the test, that is, we’re going to look at whether the placebos, the people who received placebo have far more positive PCR tests than the vaccinated ones, hence the initial importance immediately of talking about the PCR and reminding us that we are not vaccinated against VOCID-19, against a disease, but against having a positive test.

Cotton [10:28] So you still have to have symptoms.

Host [10:32] Any symptoms in a very broad list?

Cotton [10:34] Here, light or moderate, we’ll go back to that, confirmed by a PCR test.

Pierre [10:40] To be precise, what was measured was the prevention of a positive Covid with PCR-confirmed symptom 7 days after dose 2.

Cotton [10:49] Yes, but we’re going to go back to it. So, classical development, we’ve discussed it x times, normally we’re waiting for a phase to be completed to start the next one. So that’s not what was done at all. That’s why we say there’s an accelerated development. In addition, the so-called rolling review, that is, as they have results, they send out to the agencies. This also allows health agencies to review in such a short time the clinical report that they would have sent the day of the deliberations since they finally had results as they proceeded.

So the famous main criterion. So it’s actually this light or moderate Covid confirmed by PCR test. The symptoms that the participant could have, it’s fever, asset, difficulty breathing, chills, muscle pain, taste loss, sore throat, diarrhea, vomiting. So this trial, it was randomized. Phase 1, 2, 3, has been implemented because that’s how the protocol is written. Finally, there is only one protocol for all phases.

Finally, the 30 micrograms dose has been retained at the end of phase 2 and has therefore been included in phase 3, which was used in phase 3. Knowing that the objective of phase 3, therefore, was to evaluate the effectiveness of this famous vaccine, the BNT 162 B2. so as to protect the appearance of a symptomatic Covid. So be careful, here we see clearly that the title displayed, the objective we have in the protocol, which is a document available from the beginning, we clearly see that it is not a question of preventing transmission. And the analysis of the trial, finally, the famous calculation of the number of subjects, it allows us to make the final analysis when we have 164 cases of Covid, whether it be placebo or vaccine.

So this intermediate analysis that was carried out in November 2020 for the laboratory, the time to format, to present the results, is an intermediate analysis but which also finds itself to be final since there is no need for more cases than that to demonstrate effectiveness. What I did in my expertise, I’ve already looked at what we had in the protocol, so we knew we had excluded populations, I said thousands of times, pregnant or nursing women, immunocompromised patients. They’re not necessarily excluded, but we’re going to say that for some, we don’t have results presented on these populations. We couldn’t make sure we were effective on these people because even if there are a few, we don’t have a specific picture of these subpopulations, even when we have a few that are included.

So basically, we didn’t analyze the populations at risk. Since it was that fragile patients with co-morbidity, with autoimmune diseases, it is precisely… immunocompromised, it is precisely the most fragile. And pregnant women too, since they were classified as fragile. Finally, at risk, sorry. We had no interaction study with other vaccines, so the transmission was not studied. Of course, the asymptomatic Covid cases were not studied.

So, what did I demonstrate on the basis of the review of clinical reports, protocol, risk management plans, etc? So the analyses were carried out each time on a maximum follow-up of 3 months, with 50% of the people followed less than 2. And that was done thanks to changes in IDF recommendations in October 2020. That is, they allowed laboratories to provide results for up to three months, whereas the previous directives on vaccines were rather six months or even a year. We have this main criterion that is biased because we don’t have a systematic PCR test for all participants.

So, if he doesn’t have symptoms, he doesn’t have a test. This PCR test is symptom dependent. But what we know is that we have major biases, that is, if he calls the center and declares that he has symptoms and we don’t test him, well, well, it falls into the water, there is no test, no Covid, and that we mostly have antipiretics, so that they are supposed to drop the fever, and if I suppress my fever, it is also a symptom of Covid, that is, I have symptoms that are both reactions to the vaccine and also symptoms of Covid. So finally, the test is to little happiness luck.

Host [15:36] So we have two groups, we have a vaccinated group and a placebo group. They will each receive a product and a certain date and protocol to know if the vaccine is effective does not distinguish after seven days. So, that is, after seven days after the second dose, if I don’t say anything stupid.

Cotton [15:55] We count, then yes, we will count. That is, we have visits before, but we will only count the cases after the second dose. Finally, we have the visit inclusion vaccination 1, vaccination 2. We can have cases from dose 1, which is a table presented in the reports. But the main criterion is 7 days after dose 2.

Host [16:18] And here we are in a case where we have seen all the symptoms that are quite numerous and that correspond almost to all the known diseases, apart from the buttons that are not in it, but otherwise we really have a very wide range of symptoms. And under symptoms, what happens is that there is no systematic test, that is, we should say we have a placebo group, we have a vaccine group. If we want to know if the vaccine is effective after seven days on a Covid positivity criterion, and that the test works, we should say, we will test both groups in a perfectly equitable way over time each to be able to make a comparison. And that’s not what’s happening, the two groups will not be tested in an equivalent way, it’s not provided for in the trial. What any statistician knows, so I’m going to stop at this level, we’re going to say from the first readings, is to know, from the moment we don’t impose the rules, if there’s ever a bias that’s introduced, that is, we’re going to test placebo more often than the vaccine, we’re going to say that the vaccine is effective since we haven’t tested. And so here, what you add that is very interesting, is that we have in addition to side effects, a post-vaccino that happens as usual, and we have patients in particular vaccinated who, following the side effects they experience from the first few days, will take drugs like antipyretics, like nidoliprane, and are also painkillers.

So that is, we have people who will suffer symptoms right after the vaccination, who will take medication, the symptoms will disappear as a result of the medication, which means that after the seven days, they will no longer plead. And so we get a group, the vaccinated group in particular, that takes plenty of anti-piretics and painkillers so as to pass its symptoms and that will no longer complain about symptoms after seven days. And so we have an introduced bias, as there are no more symptoms, they’re not going to do their test and so we won’t have a positive output in them, which will bias the result. So that’s what you told us.

Cotton [18:04] Exactly. So actually that there is no systematic test, I think any statistician can notice it without even looking at the results. Then, we have to look at the results a little to see that we have more people under the vaccine who are taking antiperetics. I think we have three and a half times more. Fatally, I suppress symptoms, no symptoms, no tests, no tests, no Covid. So, that is, it benefits the vaccine since potentially, I decrease my cases for the vaccine group.

So above all, what we notice is that with this three-month analysis just after vaccination, with 50% of patients followed less than two months, it is that to the extent of antibodies, I do not have a measurement after two months after dose 2. However, what was already observed in the preclinical study of monkeys was that antibodies were falling, beginning to fall slightly, and it is even noticed in the graphs given to us for phase 1-2.

So this small drop in antibodies that we notice at two months after dose 2, it’s very practical behind that we don’t have any other dosages, since we have three months after dose 2, which we could have added, we wonder why they didn’t make this visit, we don’t even wonder. But so we don’t see this fall. So they didn’t take me for me deliberately not to show this fall that they know they’ve known since the beginning of December 2020, since the life of the HAS tells us that they’re considering studying a boost. No joke. It falls very well that in September 2021, I believe, they tell us, oh there, unfortunately, the antibodies only last a few months. Oh, well, we didn’t know at all.

So then, what do they do to us? They vaccinate placebo almost after the first intermediate analysis, which makes it completely obsolete the following results since I gradually remove my control group. So this, taking the active product to people on placebo, it exists, but it exists mostly for people who are sick in cancer and for In the trial, we just demonstrated that we have an anti-cancer that really works much better than the one that is taken by the participant.

So ethically, we can’t leave him a product that we know doesn’t work too well or that it works less well than the one we’re testing. So, we’re going to give them the product. Otherwise, it’s a loss of luck, it’s called. But then, as part of a vaccine, it wasn’t at all right to vaccinate placebo. we have the integrity of the data that is not verified during the IDA audits. So integrity is exactly what you want when you’re a quality insurer, that is to say, you want to be sure that the data that are carried over by the doctors who recruited the patients are absolutely accurate, that they are identical to those that are in the source files in the centres, that they recruited the people and that they were obviously verified. Because I in my company, having done a lot of data management, i.e. data management, i.e. data collection, data cleaning, we have people who grab anything from us. That is, with biology values that are completely out of the ordinary, of which we know that if the poor patient has that, he’s dead.

So we ask questions in general to those who recruit by asking them to correct inconsistent data and asking them to fill in missing data, so all this is data manager’s work. I, in my team, had up to 4, 5, I know more, but I still had a big data team and we managed a lot of deaths where we asked questions to have a clean base. That’s the point. Because if I don’t have that, I can’t have results that are reliable, of course. Little information about the analysis that came out at six months of the time.

So six months of follow-up and not three. We had a Covid death for the vaccine and two for placebo. and we had 15 deaths for the vaccine during the blind phase, i.e. before the placebos were vaccinated, and we had 3 deaths for the vaccine versus 2 after the blind had been lifted. So that’s placebos that had been vaccinated. So obviously, we couldn’t, on the basis of that, demonstrate an effectiveness on Covid mortality, or on total mortality.

So that’s on the basis of publication, it’s not on the basis of the documents made public. Now these famous documents made public, I will soon leave the floor to my friend Pierre, so it’s the ones we retrieve from the sites that put them online thanks to the action of Aaron Seary in the United States. And we have these famous SAS tables that are the XPT points. So I import them under SAS because it’s my analysis software since, finally I’ve been using it since I don’t know, 26 years, it doesn’t rejuvenate me. Others work under other software.

So it’s convenient because XPT is typically an SAS export file. So it’s very easy for me to import this in seconds. On the basis of these famous sas tables that were made public, Pierre and I realized the antibodies of phase 1. We found that, especially for people who had taken 30 micrograms, precisely the dose that is stored in phase 3, we have several assays of antibodies performed on the same day, without any explanation in the database, which is absolutely abnormal. That is to say, it happens that we redose, but normally we have a text variable behind which explains why. And here if we do an analysis with the dosage that has been preserved, we have the curve that is at the top dotted, that is the highest. And if we reanalyze on the unpreserved dosages, we have the curve that goes down.

So it means that from phase 1, by taking some dosages and not others, we already saw the fall of antibodies and this very quickly. So obviously we don’t know why, so it’s a question to ask Pfizer, why we have several dosages in phase 1? And then we realized the deaths, so this database obviously is not up to date, it is released at a time T and so we can only analyze until the date they gave us the database, otherwise if there have been deaths since we didn’t have them. So we calculated that there were 38 deaths out of more than 44,000 subjects, 19 deaths for the vaccine, 17 deaths for placebo and 2 deaths for the subsequent placebo vaccine. So obviously, we cannot say that we have any effect on the mortality of the vaccine since we have more vaccines. more mortality in the vaccine.

Pierre [25:12] So, as the abstract shelter Christine, we have been much to work on this topic of the dissection of documents. We naturally have Christine who was among the first, Josh Getsko in Israel. who is a professor of criminology who quickly seized on the analysis. Geoff Norman-Payne, who is a professor of chemistry and various other volunteers. Jayanti Kunadasan, who is an Australian anesthetist who was laid off after refusing to test the product. Brooke Jackson, who was one of the first whistleblowers during the sets of numerous anomalies she found. and our friend Amilo Idosis, another anonymous who works in Germany with great efficiency on German testing and Phase 1. It may be mentioned that I have listed many sources of trust, about thirty people on this Substack article which is the place where I publish all the source codes that result in the result that I present since, being anonymous, I do not ask anyone to trust. and I expect people to check what I publish until further notice, it turned out to be quite accurate. To summarize the key points of the data analysis, we have first indications that the trial was not really blind. We have the fact that the subjects in the treatment group were less likely to be tested for symptoms. This was a huge problem, which means that the team that managed the analysis was aware of who it was dealing with. with various anomalies on the holds to return. We have a major problem of data integrity with 301 subjects that have disappeared from the database, with Argentina that emerges as a major outlayer of this anomaly. There are significant differences between the transmus control authority relationships and the reality reflected in the database which again indicates the suppression of subjects. And finally, there is a phenomenon of bait and switch, that is, the product that has been placed on the market is not the one that has been tested on most subjects.

Host [27:28] So here, to put it very clearly, almost all of the people who received a Pfizer vaccine is a product that wasn’t that of the trial. That is, out of the 40,000 people in the trial, you found only 250 who received the same. So people, we received a product that is ultimately not tested, on which we can say nothing, in terms of efficiency and even less in terms of safety. Is that what you’re talking about?

Pierre [27:54] You can say a little, but that’s not reassuring.

Cotton [28:00] If I can add something, that is precisely why Europe, the EMA, has been slow to give its authorization since they made this remark to the laboratory saying that precisely there had been a change in the manufacture of the product. And we’re aware of that because we’ve got Russian hackers who hacked the Pfizer docs sent to EMA and also EMA’s remarks to Pfizer. And that’s what MEP Michèle Rivasi points out when she says that there is a problem with the integrity of the RNA, there are integrative RNA levels that are not the same in the clinical trial and in the doses that have been placed on the market. And the so-called problem has been solved and that’s why EMA ended up giving its authorisation.

Pierre [28:45] Absolutely. So in fact, that the trial was not really blind, we have symptoms, starting with the protocol, that Josh Getsco details on his excellent substac. I invite you to consult. So, at the site level, we have personnel who were blind, personnel who were not blind. And on that, maybe I can let Christine comment because she knows these protocol subjects much better than I do.

Cotton [29:10] Yes, so blindly, logically, we are in double blindness in the sense that those who evaluate the patient, that is, who evaluate the adverse effects, etc., the patient’s condition, do not know what was given. That is the theory. the only ones who know what is given to the participants are those who inject, since they have the management of the products, that is to say they have to order them at the pharmacy, we have to go to the pharmacy to pick them up, that is to say we give the patient a number, this number is that number that we will give to the clinic pharmacy of the center and we will bring the syringe that normally corresponds to that number, that’s how it happens in the trials.

So the participant is supposed to not know what he has since we are told that serenes are administered in such a way as to prevent participants from identifying the product. And the staff who do the serological tests also do not know, so the antibody assays etc., which is normal. So at the centre level, we still have a lot of people who are blind. So now, what’s weird is that we are told in the protocol that the study manager is not blind.

So the study manager, we didn’t understand what it was. I don’t understand myself. Is he the project manager? We don’t know. Next, we are told that the team members who ensure that the protocol requirements for the preparation, handling, distribution, administration of the product are met. For example, who is responsible for the study, so who is responsible? The one on the site, in the centre that recruits patients, we do not know, and the clinical research attaché. These people, normally, they must be blind. At the level of the study, clinicians were in charge of reviewing protocol deviations, so this is absolutely abnormal. When we have all the data and say we’re going to do an intermediate analysis or a final analysis, we’re doing what we call a blind review, that is, we’re making decisions to exclude participants from certain blind populations, not to create bias, not to exclude more in one group than in another.

So, I didn’t even notice it, that’s to say, it was Pierre who pointed out this to me, since it’s so unusual, for me it was so obvious that it was blind, why this job wasn’t done blindly, we don’t know, and we’ll see that it has consequences behind it. Then, the members of the DMC, so the Data Monitoring Committee, that’s the ones that provide the intermediate analyses, so they’re necessarily not blind, that’s normal. Me or members of my team, we participated in these famous DMCs as biostatistical experts.

So obviously we’re not blind because we need the randomization list to provide the results. The study submission team, so apparently that’s the people who probably take the results from Pfizer to pass them on to the authorities, so why they’re not blind we don’t know, because they can stay completely blind, and the protocol tells us clinical scientists or side effect monitors. So basically, compared to a trial, to other trials, there are still big anomalies that are relatively inexplicable, because there is no need at all for some to know the product that was administered to do their job. In particular, one of the biggest anomalies is this plane review story, because to look at listings, one will say, such, it has such a problem, such, it has such a problem. And so, I exclude it from such analysis populations for this work and it can perfectly be done blindly.

Host [33:05] Just to clarify, so that people understand, when you’re in the blind review phase, you have all the breaches of protocol that there may have been for some patients who arrive on the benches, on the table of those who are loaded, decided. The problem is that if they know if they are in the placebo or control group, for example, they might see that it is a vaccine that has been tested positive and may have a protocol failure but what will make the decision to remove it is to know that it is a vaccine tested positive and therefore it is absolutely necessary that this part of blind review be completely blinded to avoid this suspicion that this part of blind review has been used to evacuate a whole bunch of people who have unproven results. And I don’t know if you’ll talk about it, Pierre, but in fact there’s a lot more people who have been evacuated from studies on the side of the vaccinated than the unvaccinated ones, which makes the doubt quite serious about this part.

Pierre [34:04] No, I didn’t plan to talk about it, it’s one of the countless anomalies that we haven’t had time to list or present, but you’ll find it all on the Substax if you wish.

Host [34:13] There’s 200 decars, I think.

Pierre [34:15] There are 312 placebos excluded under curious circumstances for protocol deviation versus 312 BNT.

Host [34:31] Knowing that the efficacy of the product is 162 vs. 8 and there is 300 vs. 50 so that is, we are in the context where the total effectiveness can be entirely due people who were removed from the study and knowing that they were removed by not being blind and that we knew very well that they had withdrawn from the study.

Cotton [34:52] Knowing that I have listings of that, since that’s in the individual data that then I don’t know if that listing was made public, but we’d have to look at it seriously.

Pierre [35:02] We have the listing to be precise, I have detailed the entire exclusions to the questions on a substac and again to be precise it is a major red flag but it mainly indicates in our opinion anomalies in the management of patients rather than the desire to alter the effectiveness that has been altered in another way. Then we talked about clues that the study was not in avagle. It was not, and for the people who were involved in the study, i.e. the subjects, and for the supervision team, it is known that it was not, or less, for the subjects, since, for example, a much more pronounced share of placebo went to be re-accumulated with another product in another clinical trial, be it AstraZeneca or Moderna, at 78% compared to 22 for 546 of them, There are at the level of the study urine tests that are not done on the more advantageous subjects in placebo, in the NTBs, since if he received placebo, it is not worth worrying so much whether she is pregnant. Other influenza-type vaccines are received, which are more pronounced in placebo than in NTBs. It is understood that it is worth noting that a U.S. study highlights the fact that this influenza vaccine has engraved the chances of getting Covid and so on. All these anomalies are statistically significant.

Cotton [36:35] We have visits to Covid, opportunities for Covid, so people who have symptoms and don’t make their visits. We have more under the vaccine than for placebo. We wonder why. So it’s totally abnormal that in a centre, the product that is given freely circulates. It’s a real deviation from good clinical practice. The one who knows, he has to keep it for himself, there’s no way he’s going to scream that in the hallways.

Pierre [37:01] It should be noted that Brooke Jackson, who managed 3 sites in the 6 of Vantavia, gave the alert, among other things, on this point, stating that the entire team knew who had received what and that there was a major anomaly on this point. Then, speaking of a major anomaly, the local test rate, it was further mentioned that subjects were supposed to test locally and centrally when they had Covid symptoms. In this case, there is a significant anomaly on the proportion of subjects tested during local-scale symptomatic visits with a p-value of 0.00055, which is quite rare. A test rate that increases after obtaining UA, the authorization placed on the emergency market. In terms of these anomalies, to illustrate them a little better, it should be pointed out that they are concentrated only in the United States, i.e. in Argentina there were exceptional test rates of more than 90% for both groups and no anomalies between these tests.

But in the United States there were 6.8% of the symptomatic visits tested at a site compared to 31, 36 vs. 62, 40 vs. 76, it would appear that there was a fairly noticeable difference in treatment at sites, but that the anomaly is localized, which allows on a global scale that it is not so obvious. We had a central testing rate which, again, if we look at the global scale, appears uniform, except that if we look at the EUA, we find that before the EUA, the central testing rate was again significantly in favour of the BNT, if we intended not to detect that they had Covid. And then, we have a much more serious problem that is that serious side effects were either unregistered or requalified. That is, we have the case especially by talking about Augusto Roux, who is a lawyer law doctor in Argentina, who volunteered in the study and Josh was going to cut on his substac. And to sum up Augusto’s story, after his second dose that he received on September 9, 2020, he felt extra normal, fainted, ended up arriving at the hospital where he was diagnosed with pericarditis.

Then, BioNTech, the symptoms were looted by the BioNTech study intervened directly to requalify pericarditis addict in suspicion of Covid. And finally, the director of the Argentinian site Fernand de Polac, which we see in photography here. The principal investigator. And the chief author of the study, it is he who signs the study of the EUA and who poses 95% of effectiveness. and intervened to try to make him classify clinically insane, all while he is a pediatrician. A delicious boy.

Then, speaking of Fernando, we re-illustrated it here on another problem as an expert magician, since we have 301 subjects that have disappeared from the database, which is illustrated by the fact that the ideas of the subjects were sequentially assigned. Basically, the first four digits were the site identifier, and then the next four digits were their order of arrival in the study by disembarking to 1001 and accrement at point of 1 which was coded with an Oracle database in the middle for those familiar with computer science.

Cotton [40:29] To explain a little more, this is at the data management level. The data manager makes available a website on which you log in with password, all this is traced so that we know what data has been entered by who and when. It is set, what is called the audit trail. And so as the doctor sees the participants, he creates them on this electronic FIU, the electronic observation book, and it creased as he creates them. So if he is center 1231, I think he is our friend So the first patient who sees it is 1231.001 for example and the 1.001 and the second is 1.002 etc. So if we pass from 1.004 and in the database we pass behind to 1.008, it’s that in the middle we miss it because it couldn’t create 1.008 without creating those in the middle. So the big question is what became of these people? Were they created by mistake? But in which case all this is documented. So somewhere in the documents that explain that the participants nanana number were deleted for such and such reason.

Pierre [41:48] Finally, it should be made clear that it is possible to delete a subject from the database. We have a form that is intended for this purpose and we know that the platform used by Pfizer to manage the trial, the software of Icon Firecrest, allowed to delegate to the clinical manager of a study the power to remove subjects or symptoms himself, which is at least surprising. In Argentina, there are 111 of these 301 deletions.

So we mentioned, there was no anomaly on testing in Argentina, but there is a major anomaly on the fact that 111 of these subjects, i.e. 36.9% of total disappearances, i.e. in Argentina, the whole, while they documented, for example, 6 duplicates in the data review guide. And that would have been a good reason to delete a subject, to have registered twice. There are 6 patients who have been enrolled on several sites at the same time, that is, in the same way that others were going to seek vaccination in another clinical hesitation. These are listed in two sites at the same time, which requires some resourcefulness already, but it is a rare event that occurred 6 out of 44,000 times, not 301.

So this is a big open question. When we found the problem with Josh Gatsko, we also wrote early, after I had to check the information, it was at that time that I had a lot of trouble with Christine, and we checked with Bo Jackson that it wasn’t possible. We wrote to Peter Marx of the FDA, who is responsible for the quality of the data and the review of the clinical trials, who has delegated one of these sub-fifres, which told us it’s very interesting, we’ll come back to you soon, it was about two and a half months ago. and we’re still waiting. Probable that they will come back one day, but when you don’t know.

Then to illustrate more, finally to illustrate more why this problem is major, you have to have in mind that the subjects received both doses. First dose 1 on the day of their screening or a few days later, but it was not to be more than three days after screening. And then received the second dose 19 to 42 days later. Typically it was 21 days. What is particularly disturbing is that Augusto Roux, who was mentioned earlier as having had serious problems after his second dose, had enrolled in the study in August, and on the same day as his registration, there was the highest proportion of missing subjects, with 17 who disappeared on the same day as Augusto had arrived in the study. So we have very strong reasons to suspect that you received the second dose on the same day as Augusto. They were then less good to be visible than Augusto himself.

Host [44:24] The suspicion is that here, there will be something common to all these people that they would have received, for example, something defective that could have caused Auguste Roux to become ill and that it is surprising that a large part of the people vaccinated on the same day as Auguste Roux, a priori, disappear from the study and therefore possibly are people with problems. Which would be a trace that what they received as Auguste Roux did cause problems that we can’t see anymore.

Pierre [44:51] Indeed, yes. It is already known that there are huge variations in side effects by batching prepared products. There is little doubt about the issue in the disproportion of VAERS reports that have been reported by patients with side effects. In this case, it is very possible that there was an error in preparation or conditioning on the batch and that it caused the side effects in question, or that there were impurities typing otoxin during the preparation of the batch, which would stick enough to the symptoms reported by Augusto Roux. And finally, if we were not known…

Cotton [45:30] Knowing, sorry, knowing that all this is obviously traced in the center, normally.

Pierre [45:36] But it is one of the data that has not yet been communicated, whereas the communication of the data, after the order of the judge, should have been completed by the end of 2022. Finally, if there was still a doubt about the fact that this is a major problem, documents were communicated by the EMA via Freedom of Information Request. In these documents, there is a gap of about 60 subjects between the total per site and the reality of the database, which means that between the time these documents were communicated to the EMA and the time the database was made available to the public, the number of subjects moved.

Host [46:12] Screener means registered and checked, right?

Pierre [46:15] That’s right, it’s because they passed the screening procedure and either they were accepted into the study, or refused because they had serious commorbidities.

Host [46:23] So in the final document, there is on the one hand the sum of everything, which is official, which was said in the clinical trial, we have so many people who are screened, that is, who will participate in the total trial. And in this new document, it was requested by FOIA, i.e. by administrative document, make a request for administrative document, it was asked to obtain details by site and there it is realized that if we sum up at all sites of patients who have registered, there are 60 deviations from the total that is officially given. Is that what’s going on?

Pierre [46:56] So, class goal not list, it was mentioned in the introduction, but the process that was used to make the doses was a PCR-based process. It was extremely accurate in terms of manufacturing quality, but that was not extensible for large-scale manufacturing. At the end of the study, BioNTech officially discovered it. In fact, they knew it before they even started. They only tested this large-scale manufacturing process on 250 patients from October 19th. Thus, all the other subjects of the study received the high-purity process, in quotation marks. Of these 250 subjects that were successfully identified by cross-checking and analyzing which subject received the product after October 19th at the sites where process 2 had been distributed, there is a secondary effect ratio of x2.7 in relation to high purity produced. It was already not terrible. And that concludes the inventory of current problems.

Host [47:59] If I try to summarize your presentations, then we have a trial that was launched in an accelerated manner with even a fusion of procedures, as Christine said at the beginning, out of the final 48 people. We normally have in the case of a clinical trial, a bunch of standards, procedures that are put in place so as to avoid any deviation. And all that is done must normally be traced, traceable, to allow the authorities to verify everything, everything that has been done. And what you have shown in the first part is that this tracing, this traceability is not at all assured and that there is a lot missing in the processes and in the protocol. In the second point, you have shown that finally, this major clinical trial Pfizer International corresponds mainly to two countries, Argentina and the United States. And that we have a problem at the beginning of the game that is what we tested, that is, that we have a vaccine that does not protect from being ill or dying, it is not the beam path, but is supposed to protect from a positive test in the context where we would have symptoms. What is already something other than what people lean about, they think they’re going to be less sick, it’s not. What we promise to study is that you will have less positive tests in the case of mild symptoms. And what we know as a statistician, finally as soon as we even have a little sense of logic, is that to prove that a product allows for less positive tests in a fair manner, we would have had to test the same number of times at the same time the 20,000 people who received the vaccine, of the 20,000 people who received placebo. What has not been done is that there is no guarantee of testing. And we had in protocol only people who could call a center to say they were feeling symptoms and the center decided to then perform a test. Christine has shown that, in addition, we see that there are side effects that are major in the study, our same delegated ones, such as fevers, coughs, etc., which are symptoms stamped VOCID-19 outside.

But these symptoms have caused the people who suffered them to take antipyretics and painkillers. And since the first 7 days did not count in the post-vaccination study, we therefore have people immunized with the test product who took antipyretics and painkillers and who did not necessarily feel the need to be tested once their symptoms disappeared ex post facto. In any case, since people have not been tested the same number of times, the question must be asked how many times each group has been tested to see if it is fair. And there you have discovered major problems that are very different from one country to another. There’s the side of the United States where you show that on the sites, we tested placebo much more often than the vaccinated. What’s a problem in terms of protocols since obviously, it was said, no test, no Covid and no Covid, the vaccine works.

So obviously, there in the United States, it’s pretty clear. And you showed a second problem. which is part of the protocol in Argentina, which has been to show that there are a lot of patients who have been excluded from the study on that country which is Argentina. And you have shown that in the trials, one understands that when one discussed the exclusion of patients, in particular, there are other times, people who managed exclusion, they were not blind. That is, they could know whether the person had received the vaccine or not.

So we have a problem with the integrity of the data. The demonstration to say that the vaccine is safe and effective is of the order of, there were 8 positive cases in the vaccine against 162 in the unvaccinated, which are very small figures in the end. It’s a 95% difference, but it’s very small. It means that even weak interventions within the given base, not to test vaccines next door or to exclude people who are uncomfortable in the other, it can be much enough to create the full vaccine effectiveness. So you have removed more than doubts, there are shortcomings in the protocol, procedures that are not followed, etc. And on the balance, the whole trial is to be reviewed and anything that could be told in terms of efficiency can totally have been built by the choices that have been made not to test people and exclude people from the protocol. Did I summarize the situation?

Pierre [52:15] Indeed, I will just clarify the term exclusion, because exclusion is something that is provided for in the protocol and someone who does not behave as the study provides. For example, a woman who falls pregnant can be legitimately excluded. In this case, we are not talking about this at all, we are talking about deletion.

Cotton [52:33] There are the exclusions of the analysis populations that are defined in the protocol from the beginning. And there, it’s totally deletions. And that, it’s totally abnormal.

Pierre [52:43] I take the trouble to make it clear because the first thing that was answered when I released the article on deletions is yes, it’s provided for in the protocol, there are exclusions. But no, I wrote two articles on the exclusions in question, I know what it is. And here we’re talking about people who have disappeared, which is another problem.

Cotton [52:58] So in fact, what we see is that when you put your nose in the database, it completely confirms what I wrote in January 2022. That is, there are very important deviations from good clinical practice and that the only way to validate this trial or not is to go to audit all the sites, to ask for these famous audit trails that trace all the data entered and changes with reason for modification. And to trace all of them, finally to retrieve the logs, the tracking we have in the sites, that is to say, when the participant called, when he was asked to do a test, etc. So all these are normally available documents and are completely auditable.

Pierre [53:47] The site is in this case the data manager, i.e. that ICON, which was responsible for the quality of the data, must in my opinion also be audited. I would very much like to have a copy of the database to look at the logs of it.

Cotton [53:59] Yes, it’s the trail audit. After there’s the logs. So I mean why health agencies don’t do it from the beginning by having people like Augusto Roux alerting about serious unreported effects as Garé said in the United States, we don’t know.

Host [54:19] Finally, what is required is to do as all other clinical trials that are normally follow the good practices of clinical trials and what has not been done. So it is not even a matter of going into a circumvolution on efficiency or discussing something, it is a matter of entering into a framework which is a legal framework, which is a framework of good regulatory practice, and pointing out that from the beginning the regulation is not respected, that the documents are not provided, and that besides that, there are within the disappearances, irregularities which are massive that should have made the trial obsolete, and even, I think, the people being prosecuted inside, we notice that the irregularities are flagrant and we have access to them that since a judge, for some of them, has given us the order to have access to documents which should have been public and analysed. So we’re in this framework, we’re relying on the regulation, and that is also to say to the people that here, it’s not stuffy things, it’s about enforcing the regulation that exists in the other trials, to Pfizer and eventually also to the others who participated in these vaccines.

Cotton [55:29] So I want to add something, that is, I’ve seen a lot of comments from people who say yes but it hasn’t been tested by other labs, but clinical trials are never tested by other labs. Just when all stakeholders follow these good clinical practices, which allow for this traceability, that way of working that is correct, that allows for reliable and integrity data, there is no need at all for it to be validated by another body. Finally, the IDF is on the program, they have standard programs, they’re going to do their own tests, but on the database that’s provided by the lab, but there’s no need for it to be validated by anyone else. This is the whole problem with the Clinical Pfizer EC, the data is not valid, so the de facto results are not valid. So all the health agencies should have done this reanalysis work at least, since now we’ve seen it well, it’s been a while since the vaccines came out, you can still see that it’s been totally ineffective and it still creates a number of side effects. So why this work of reanalysis, of questioning was not done, we wonder what they are doing in the health agencies in fact. That’s not why we are paying these people. That’s it.

Host [56:46] This is a great question. Look, I thank you for being precise. I recall that Christine Cotton released her book which you can recall the title Christine.

Cotton [56:55] All vaccinated, all protected, question mark.Vaccination VOCID-19 chronic of a health disaster announced.

Host [57:04] So this is an expert from a person from industry, who has worked with the pharmaceutical industry for a very long time and is familiar with good practices and who shows that they have not been respected in this. So, of course, I invite everyone to buy Christine’s book to read it and, above all, to understand that he has a problem with these vaccines from the regulatory point of view and that we are not discovering today that there are problems, we could find out from the reading of Pfizer’s Phase 3 trials and that is where everything that has happened should have stopped.

Cotton [57:36] So a little bit more precision, this book that seems a little barbaric like that, when we say oh there clinical trials it’s going to be from a dying dog, not at all. There’s the summary I think is available or I put it on Twitter, or it must be available on one of the sales sites. But it’s not at all boring, precisely, since the only way I found to make it pleasant to readers is to tell a little bit about my life and give the word to the victims, who was initially the publisher’s request. And so, it’s not boring at all, because when you have a little bit of technical passages, you’re going to say, behind, you’re going into a witness with another style, or you’re going into little stories of life that, sometimes, are a little crazy. So thank you so much for giving us the floor.

Host [58:23] Thank you very much Pierre. Thank you and I hope that this work will be more known than it is yet in the future so that we can protect ourselves above all that it will start again even if this scam is coming to an end we should avoid that being had a second time. Thank you and thank you for all your work.

Pierre [58:43] Thank you, everyone.