Pfizer/BioNTech C4591001 Trial - DailyClout Report 86 on Process 2

Short comments on an overlooked key finding.

Some hours ago, the Daily Clout published a report1 which appeared to us initially as a very inelegant hijacking attempt2 of the work of Josh Guetzkow & Retsef Levi3 on the key issue of the Process 2 “bait & switch” (things were later clarified as illustrated in the comments).

If you haven’t followed this subject, this recent talk, between Josh & John Campbell, is a great way to catch up.

The DailyClout’s “AEs analytics” itself adds further evidence to the findings already exposed by Josh’s great work, highlighting Process 2 batches increased risks compared to Process 1 ones4, this time by comparing these 252 subjects with those 250 placebo recipients “selected by Pfizer/BioNTech”.

This article adds another major element, which is the finding by Erika Delph on randomization numbers. It seems to have been overlooked by the writers themselves, as it’s just “casually” mentioned (circled in red).

We verified the “randomization numbers” statement, confirming its accuracy.

Assuming that you have setup your project the way described here5, you can reproduce these analytics by running “scan_randomization_process_2.R”.

We used the .CSV list we had already isolated, and sent to the Daily Clout in August (and that they have now “discovered”) as control, to verify that:

• 1. 252 process 2 BNT162b2, and 250 Placebo subjects, in the ADSL file6 , are indeed the only ones with randomization numbers between 400000 and 499999.
• 2. All of these subjects have been recruited on Batch EE8493 sites (1133, 1135, 1146, 1170), on or after October 19, 2020, and are indeed therefore our Process 2 subjects.
• 3. None of the Process 2 subjects are missing from this list.

This finding is extremely significant.

It tells us that ICON was working directly in collaboration with Pfizer, and that the “randomization numbers”, which so far appeared to have no logical sense, are “tags” allowing them to reflect information on the subjects.

In this scenario it’s not a randomization number anymore, but a “secret code” between the data provider and the clinical trial sponsors, directly reflecting critical data about the subject treatment, which is the opposite of how this data is supposed to be managed.

This only stresses further the need for investigations to be triggered on ICON, which we were already highlighting in a previous article with Josh Guetzkow, on another major issue, namely 301 subjects records, highly suspiciously missing from the files7.