Commissioner [00:10] Hello, Mrs. Cotton, can you hear me?

Christine Cotton [00:15] Hello, singer.

Commissioner [00:16] Yes, good morning, so first of all, on behalf of the committee, I want to thank you for agreeing to testify today, which is very important to us.

Speaker [00:26] Thank you.

Commissioner [00:28] So, we’re gonna do the identification, if you’d like to, just name your name and surname.

Cotton [00:38] Christine Cotton.

Commissioner [00:39] Perfect. I will also go there for formality, I will swear to you. So solemnly declare that you are telling the truth, just the truth. Say “I affirm it”.

Cotton [00:49] I’m saying it.

Commissioner [00:51] So, Christine Cotton, I’ll describe you very briefly, but after that, of course, you’ll be able to complete this description of everything you’ve done and all your work. So, you’re a biostatistician, you have 23 years of experience in the pharmaceutical industry, you’ve been CEO of your own company for 22 years in the organization in clinical research, CRO. under handling, monitoring, data management, statistics. You’ve had, even as customers, AstraZeneca, Pfizer, Sanofi, AB Science, Bayer, Aventis and I go to different hospitals as well, to name only these. And you have experience in all types of trials in various therapeutic areas. oncology, central nervous system, gastrointestinal system, autoimmune disease, osteoarticular system, odontology, pneumology, ophthalmology, nutrition. You really have a very wide field of expertise, including also you have done clinical trials in phases 1, 2, 3 and 4 and observational studies. Is that a good summary, but I see that you really have a very sharp field.

Cotton [02:19] I have worked in a lot of pathologies, in Viral too, hepatitis C. I have worked in duperculosis, in kidney transplantation. When we are under-treated, we have many clients in diabetes. So, actually, I have participated in nearly 500 clinical trials. And what you need to know is that it’s not at all a doctor’s job to do a statistical analysis of clinical trials, it’s a biostatistician’s job. There. So, Christine… I’ve been doing this for a very long time.

Commissioner [02:57] So Christine Cotton, we’re very curious to hear your results and your research and clinical trials, including the poor evaluation of the effectiveness you can address. I don’t know if you had a step in the right direction.

Cotton [03:21] Can I share my screen maybe?

Commissioner [03:23] Yes, absolutely.

Cotton [03:26] So I reviewed all the documents from the Pfizer Clinic trial. A clinical trial is hundreds, tens, or even hundreds of stakeholders because if I sum up, I had made a small summary document, we have those who recruit the participants, we obviously have the sponsor, it is the one who initiates the study, we have the data management service, it is the one who creates the system to record the data, we have the statistical department, we have the monitoring that will see the sites that recruit the patients to check the documents. We have the pharmacovigilance service obviously, we can have laboratory services to analyze a whole bunch of parameters. We have the quality assurance service that makes sure all these people work properly.

So the statistician, he intervenes at the beginning since he writes the methodology of a clinical trial, he is the guarantor of the validity of a clinical trial, and he intervenes at the end when we have all the data or possibly during intermediate analyses, since it is he who programs, valid, because we get to several in general, depending on the importance of the trial, to be sure that we make the exact results well, since in this profession we cannot afford to be mistaken.

So he returns the results and it’s going to be a medical writer who will write the clinical reports. So that’s why obviously, as a biostatistician, I can read all the clinical reports since I was writing them, at least half, in collaboration with the doctor who wrote them. What is known about Covid clinical trials is that usually it takes about 15 years between the discovery of molecules until a marketing authorisation has been obtained and these trials have benefited from what is known as accelerated development, i.e. each phase to be started before the previous one is completed.

So obviously, we don’t have all the results every time, we start a phase without having the results. So the clinical trial Pfizer, since that’s the one that I’ve examined in length, wide, across, it has to last about two years. There are a number of visits that are planned, where the participants, so those who have been recruited, who volunteered and have signed informed consent, will go to the site that recruited them, to do a number of analyses.

So obviously, if they have a Covid before they have a visit to the site, they report that they have such and such symptoms. And in that case, we’ll give them an appointment to do a PCR test. So what we know since December 2020 is that in a clinical trial, pregnant or lactating women are never included, since they are part of the protected populations. It is also known that immunocompromised patients have not been included. patients with co-morbidity, therefore diabetes, lung pathologies, etc. patients with autoimmune diseases or inflammatory problems have not been included, i.e., the most fragile of all. What is also known is that the interaction with other vaccines has not been studied, that the transmission has not been studied. There has been a lot of hay with this unstudyed transmission history. The major problem with the Pfizer Clinic trial is not that the transmission was not studied at all. This is for fun in the gallery. Symptomatic cases have not been studied.

So, in fact, what did they do? It is because they conducted intermediate analyses to be able to provide results before the end of the test, as it was seen that it would last two years. So, every time they provide results on a population, whether it’s adults over 16 years of age, teens 12-15 years of age, 5-11 years of age, babies, etc., we always have a maximum of 3 months of follow-up for participants.

So it means we’re looking at, we’re counting the Covid cases over these 3 months, so we’re going to look at the tolerance over these 3 months. So it’s a short time and obviously we can’t have a conclusion on a medium- or long-term tolerance when we have a decline every time of max 3 months or even 50% less of 2. It’s very fast. We realize that with this, we can’t say it’s safe. When we say it’s safe, yes, it’s safe according to the results over the period under review. Already, you see that it’s changing a lot of things.

So, what’s very important? It’s this famous criterion of efficiency. There, we were told that we have 95% efficiency, it’s great, etc. When we look at this efficacy criterion, the efficacy, these famous 95%, it is a calculated efficacy on mild or moderate Covid cases, confirmed by PCR test. And how we know if one is a Covid case, is that one has a number of symptoms, fever, sourness, diarrhea, bulging, etc.

However, the vaccine causes these symptoms. So, I’m going to have a number of possible symptoms that the patient is going to have, and instead of going to a Covid test, because it’s a potential Covid, we’re going to put this on the back of the vaccine reaction. So what we know from the documents made public, i.e. in the documents made public on court decisions thanks to Aaron, Siri and the United States, we can retrieve the database, i.e. the tables, what is called SAS, that is the software under which the statistical analyses are carried out and which was used to analyze this trial, we know that we had fewer PCR tests for the vaccine than for placebo. So we realize that if we don’t run PCR tests, we won’t be a confirmed VOCID case by PCR test since we didn’t. And we also know, so if you don’t understand, you have questions, you interrupt me, since I know him so much about this trial that I run.

Commissioner [10:31] In fact, you usually compare yourself to what we’ve been doing in clinical trials with what has happened since 2020. You really see that there’s a difference in protocol. Exactly.

Cotton [10:41] That is, clinical trials are methods, they are the regulation of the piles of rules to follow. that have been in place for years, which are called good clinical practice. And if my trial does not meet, in the choice of its criteria of effectiveness, in the analyses made, it does not respect the good clinical practice, it is worth nothing. That’s why we need to know the clinical trials usually to know if this is valid or not. Because we need to know all these good practices where we have hundreds of documents that frame all the tasks of all the stakeholders I spoke to you about earlier. And if the tasks are not well done, then I have deviations from good clinical practice.

So I have some that are very serious and I have others that are less serious. So what we also know in this trial is that participants have the right to take anti-piretics. So it’s for fever, it’s going to remove some symptoms. And we find that there are a lot more participants who have taken these anti-piretics in the vaccine group. So I’m removing symptoms, I’m not likely to do any PCR tests. So that’s called a methodological bias, a statistical bias that prevents me from properly evaluating my effectiveness. What we’re sure about is that this choice of efficacy criteria only measures part of the disease. To really measure the disease as a whole, it would have been necessary to use a criterion that they have fully measured, which is therefore the antinucleocapside acerology. And then, it tells us, who had VOCID during the IC? How many did we have? And when we calculate the effectiveness on that, we don’t have 95 anymore, we have around 55.

Commissioner [12:43] There was no measurement of antibodies, if I understand Mrs. Cotter.

Cotton [12:47] So that’s something else.

Speaker [12:48] We’re gonna go to the antibodies.

(unclear) [13:23] …