EXPERT REPORTin the caseof

Sam White & Others
V
MHRA

PJH Law
18a Maiden Lane
Stamford
Lincolnshire
PE9 2AZ

Dated 28th December 2021

Alexandra Latypova

1

Contents:
1-3 - Introduction
4 - Background and Experience
5-8 - Personal Reasons for This Analysis
9 - Methodology
10-11 - Questions Examined in My Analysis
12 - The Covid19 Vaccine Dataset
13-14 - The Flu Vaccine Dataset
15-16 - Summary of Findings
17-21 - Limitations of this Analysis
22-25 - Results for Finding 1
26-38 - Results for Finding 2
39-43 - Additional Information
44 - Declaration of Responsibilities

2

Introduction:
1. Mass vaccination with covid vaccines has been under way for nearly a year now in
the US and worldwide. Millions of doses have been administered, majority are theso-called mRNA vaccines manufactured by Pfizer, Moderna, Janssen, Astra
Zeneca and others.
2. Established in 1990, the Vaccine Adverse Event Reporting System (VAERS)
https://vaers.hhs.gov/about.html is a national early warning system to detect
possible safety problems in U.S.-licensed vaccines. VAERS is co-managed by theCenters for Disease Control and Prevention (CDC) and the U.S. Food and Drug
Administration (FDA). VAERS accepts and analyzes reports of adverse events(possible side effects) after a person has received a vaccination. Anyone can reportan adverse event to VAERS. Healthcare professionals are required to reportcertain adverse events and vaccine manufacturers are required to report all adverse
events that come to their attention.
3. As stated on the CDC website: “VAERS is a passive reporting system, meaning it
relies on individuals to send in reports of their experiences to CDC and FDA.
VAERS is not designed to determine if a vaccine caused a health problem but isespecially useful for detecting unusual or unexpected patterns of adverse event
reporting that might indicate a possible safety problem with a vaccine. This way,
VAERS can provide CDC and FDA with valuable information that additional
work and evaluation is necessary to further assess a possible safety concern”.
Background and Experience:
4. I am a retired business executive with 20+ years of experience in pharmaceuticaland medical device Research and Development (R&D) industry as well as in a
broader data analytics field. Throughout my career my primary expertise wascollection and analysis of data from global clinical trials. My experience covers
all therapeutic areas of drug development. I was senior executive at several
clinical research organizations (CROs) conducting data collection and analysis onbehalf of pharmaceutical companies for the purpose of clinical trial datasubmissions to regulatory authorities such as FDA, EMA and other relevant
agencies. I left the Pharmaceutical R&D industry in 2014. Prior to working in the
CRO field, I worked as analytical consultant in the area of econometrics andlitigation support, working primarily for pharmaceutical and medical device
clients. I hold Master of Business Administration degree from DartmouthCollege, Hanover, NH.

Personal Reasons for This Analysis:
5. I personally have never been against vaccines in general. I received many
vaccines during my life, and my children have always been up to date on3childhood vaccinations. Prior to 2020 I did not know anyone personally who havedied or was injured by the vaccines. I now know several people who have been
injured by the Covid 19 vaccines, and I have witnessed a young man (late 20’s –early 30’s) falling unconscious immediately post Covid 19 vaccine injection at mylocal Safeway Pharmacy. I saw his CDC issued vaccination card lying on the floor
next to him. I do not know whether this young man survived.
6. Prior to 2020 and while working in the pharmaceutical industry I had general trustin the scientific method and I observed most people in the industry, including staff
at the FDA working honorably and following their own procedures and guidelines.
7. In 2020 I was following the industry news closely, and I decided to use my own
skills and experience and publicly available VAERS data to evaluate for myself
and my family whether these vaccines are safe and reliable products as now
advertised broadly in media.
8. The following analysis is all my own work. Everything I say below is based onfact and data. My analysis is easily reproducible and can be checked by anyone
with intermediate skills in Microsoft Excel software. I have included files that I
downloaded from VAERS and used in this analysis in the Technical Appendix.
Methodology:
9. Since most people believe that vaccines in general are very safe, I decided to study
the patterns of VAERS data for Covid 19 vaccines manufactured by Pfizer,
Moderna and Janssen in comparison to the seasonal flu vaccines from a variety of
manufacturers. Seasonal flu vaccines are some of the most widely used vaccine
products and are given annually to approximately 50% of the US population(according to CDC). Thus, they represent a reasonable comparison for Covid 19
vaccines. I decided to examine the data in relation to specific manufacturing lot
numbers.

Questions Examined in My Analysis:
10. Are Covid 19 vaccines similar to the seasonal flu vaccines in regard to the overall
patterns of Severe Adverse Events and Death Reports?
11. Are there unusual patterns in manufacturing lot-to-lot variability for Covid 19
vaccines in comparison to the seasonal flu vaccines?

4

The Covid19 Vaccine Dataset:
12. The dataset for my analysis was downloaded from the VAERS website (as ofDecember 10, 2021), limited to the reports submitted from the United States only.
The final dataset was merged from several files available in VAERS with thefollowing information:••••

Vaccine Lot Number
Manufacturer
Number of Adverse Event (AE) Reports that contained this Lot Number
Number of Severe Adverse Event (SAE) Reports that contained this Lot
Number. In my analysis Severe Adverse Events were identified by checking“Severe” tab in Section 5 of VAERS search engine.
• Number of Death reports that contained this Lot Number
The Flu Vaccine Dataset:
13. The dataset with the same parameters as above was downloaded from VAERS for
the following 9 flu vaccine products.

14. Intranasal sprays and H1N1 products were not included. I downloaded allavailable manufacturers and all available years of data, for the United States only.

5

Summary of Findings:
15. My analysis revealed two findings for covid vaccines:••

Finding 1: The total number of adverse events, serious adverse events and deaths
reported in lots of COVID-19 vaccines over the period of less than 12 months
appear to be much higher than the total number of these events reported in lots ofseasonal flu vaccines over the total available time (approx. 30 years).
• A very large difference exists for every assessed category: total as well as
maximum and average per lot adverse events, serious adverse events, anddeaths.
Finding 2: A dramatic variation of adverse events, serious adverse events, anddeaths between lots of COVID-19 vaccines appears to stand in stark contrast to
much lower variation of adverse events associated with the lots of the seasonal flu
vaccines reported over a 30-year period.
• This latter finding puts in question whether the manufacturing process for
Covid 19 vaccines conforms to the Current Good Manufacturing Practice(CGMP) requirements from the FDA and EMA.

16. These results indicate unusual and alarming data patterns in the adverse event anddeaths reporting from covid vaccines associated with specific lot numbers. Thesefindings are easy to detect and obvious, yet no regulatory or public health agency
have “detected” these signals to date. This willful inaction speaks even louder
than my numbers do.
Limitations of this Analysis:
17. VAERS database is set up for spontaneous voluntary reporting, and significant
under-reporting factors have been found in the past, ranging from 10-100x underreporting of significant adverse events. A Columbia University study found thatvaccine related deaths were under-reported by a factor of 20x: (PDF) COVID
vaccination and age-stratified all-cause mortality risk (researchgate.net)
18. I do not have access to a definitive list of manufacturing lot numbers. This
limitation is not relevant to the lot numbers that have hundreds or thousands
adverse event reports associated with them, since it is impossible to mistype a lot
number in the same way thousands of times from various geographic locations.
Therefore, lot numbers associated with at least several adverse events should beconsidered valid lot numbers.
19. I do not have the complete information about the lot sizes in terms of doses forthese datasets. However, it is highly unlikely that manufacturing process for theseproducts produces lots in the range of sizes that would explain ~1000% lot-to-lot
variability that I have detected in the adverse event reports. Something else must
be going on to fully explain these highly unusual patterns.

620. VAERS database contains many “lot numbers” with 1 adverse event reported thatare apparent typos. This problem applies to both flu vaccine and covid 19 vaccine
datasets, therefore it is unlikely to significantly affect my conclusions. Note thatwhen these typos are corrected and an event is correctly attributed to a lot withlarger number of events, the variability lot-to-lot increases. Thus, if all typos werecorrected, the variability for the Covid 19 vaccines would likely be even worse
than I detected in my analysis. Additionally, I removed most obvious typos fromboth datasets prior to performing my analyses, and I further tested my conclusions
when all 1- and 2 – event lots are removed from the dataset, and this does notchange the conclusions.
21. Factors such as person’s age and co-morbidities, temperature control for thevaccine products, distribution, transportation and storage issues, possible errors in
administration, and other similar parameters can affect adverse event analysis.
This limitation does not matter when looking at the total lot-to-lot variability,
since both flu vaccines and Covid19 vaccines are by these possible issues.
Furthermore, it is manufacturers’ responsibility to endure that the product can bedelivered and administered safely throughout the supply and distribution chain.
My analysis looks at the total variability on the output of the system – how many
people are affected, and how these negative events are distributed between 2 typesof products when we look at the real-world data.
Results for Finding 1:
22. The datasets after data downloaded from VAERS and obvious typos and missing
values are removed.

*Unvalidated – i.e. lots that are present in VAERS database, contains typos. This does
not matter when comparing two datasets that have similar population and methods of datacollection. This does not affect lot numbers that are associated with high numbers ofadverse events and deaths.
**Numbers of events reported to VAERS in each category. Remove “unknown”, “none”,
reports with missing data and some obvious typos. Not 100% of typos were removed –discussed in “Limitations”.
723. As of December 3, 2021, the data comparing COVID-19 vaccine lots to seasonal
flu vaccine lots from over 30 years show the following:

24. I found that over 30 years, the seasonal flu vaccine has never had more than 137
adverse events reported for a single lot. However, according to VAERS data, inless than one year, 5,297 adverse events were associated with one lot of the
COVID-19 vaccines (Moderna 039K20A). In addition, over 1,000 reports ofadverse events were linked to 186 COVID-19 vaccine lots, and another 500-999
reports of adverse events were associated with 70 lots. The analysis further showsthat approximately 80% of U.S.-only adverse events reported on VAERS for
COVID-19 vaccines are associated with approximately only 1% of vaccine lot
numbers, and approximately 80% of serious adverse events (those involving
emergency room visits, hospitalization, or death) are associated withapproximately only 5% of vaccine lot numbers.
25. In conclusion, the significant differences between COVID-19 and seasonal flu
vaccines on VAERS, both in terms of absolute numbers of reported adverse eventsand lot variation, should be raising major alarms with the vaccine manufacturers
and regulatory health agencies. However, it remains unclear the extent to which
vaccine manufacturers and regulatory health agencies have reviewed or conductedrobust safety investigations based on the COVID-19 VAERS data.

8

Results for Finding 2: Manufacturing Lot-to-Lot Variability for Covid-19 Vaccines vsSeasonal Flu Vaccines
26. This part of my analysis is primarily concerned with manufacturing quality,
stability, reproducibility, and other factors that relate to the consistency of the
manufactured product lot-to-lot.
27. Vaccine manufacturing is a regulated industry, in the United States relevant
regulations include Current Good Manufacturing Practices (CGMP), 21CFR
210.1, and related FDA regulatory guidances https://www.fda.gov/vaccines-bloodbiologics/general-biologics-guidances/cmc-and-gmp-guidances, including
Chemistry Manufacturing and Controls (CMC) and other relevant guidances.
These regulations are harmonized with other countries’ regulatory bodies via
International Conference on Harmonization (ICH). While under public healthemergency, some of these requirements can be waived by the regulators, it isnonetheless expected that the products are manufactured in a high-quality
manufacturing environment with conformity of the product lot-to-lot.
28. Pharmaceutical products such as vaccines are expected to fall within certain
narrow limits of variability on a set of controlled parameters between production
lots. There is expectation and assurance from the manufacturers and regulators thatthe product sampled from different production lots will be essentially the same. In
addition, there is assurance from manufacturers and public health authorities that
Covid-19 vaccines can be used interchangeably from different manufacturers.
There are no clinical studies demonstrating this, however, the public is expected totake the manufacturers’ and health authorities’ word for it.
29. To investigate the lot-to-lot variability for Covid-19 vaccines in comparison to theseasonal flu vaccines, I first plotted Serious Adverse Events for all manufacturing
lot numbers in the Seasonal Flu dataset, sorted alphabetically:930. Seasonal Flu Vaccines, All Lots with Non-Zero Serious Adverse Events

31. The chart above illustrates several findings for seasonal flu vaccines:• Overall narrow range of Serious Adverse Events (SAE) per lot over the entire
dataset. Nearly all lots are below 10 events per lot. Only 2 significant outliers (37and 20+ events/lot) in the entire dataset.
• There are no significant patterns of lot-to-lot variability – the dataset looks
homogeneous across all manufacturers.
• Maximum SAE observed in one lot over approx. 30 years is 37 reports/lot.
32. Descriptive statistics for the Seasonal Flu Vaccine Dataset:
#LOTS
TOTAL
22,334
MAX/LOTAVERAGEMEDIANSTD DEV
COEFF
VAR

AE
SAE
REPORTS REPORTS DEATHS
123,651
137
6
1
9

9,427
37
0.4
0.0
0.9

906
30
0.04
0.00
1

169%

224%

99%

33. Next, I created the same plot for the Covid-19 Vaccine dataset, looking at the
Serious Adverse Events/manufacturing lot, sorted alphabetically.

1034. Covid-19 Vaccines Dataset

35. The chart above illustrates several findings for the Covid-19 vaccines:• Overall, extremely wide range of Reports/Lot (1-622), nearly 17 times broader
range vs the flu vaccines data
• Visually clearly different patterns of data associated with each of the 3
manufacturers• Unusual “clusters” of lots with high numbers of SAE reports and lots that have 1
report or only a few reports. Note that removing typos in lot numbers does notchange this conclusion or pattern.
36. The table below provides Descriptive Statistics for the Covid-19 vaccines dataset:
AE
SAE#LOTS REPORTS REPORTS DEATHS
TOTAL
24,945
483,410
47,239
7,335
MAX/LOT
5,307
622
139
AVERAGE/LOT
19
1.9
0.29
MEDIAN/LOT
100
STD DEV
178
19
4
COEFF VAR
916%
1019%
1195%
37. To summarize the differences in manufacturing lot-to-lot variability between thesedatasets, I compared coefficient of variation for each dataset. The coefficient ofvariation (CV) is a relative measure of variability that indicates the size of astandard deviation in relation to its mean. It is a standardized, unitless measure
11that allows one to compare variability between disparate groups andcharacteristics. It is often expressed in percentages. The results demonstrate that
the Covid-19 dataset the CV is up to 12 times greater that that for the seasonal flu
vaccines dataset.

38. In conclusion, the Covid-19 vaccines do not demonstrate consistency inmanufacturing lot-to-lot. This result puts in question whether manufacturing forthese products that are being injected into millions of people, including young
healthy adults, children and pregnant women are compliant or consistent with
manufacturing quality standards expected from medicines. The public is underassumption that these vaccines are safe, effective, and produced with the highest
standards of quality. My analysis demonstrates that this is not the case based on
the real-world outcomes data. These findings are very alarming and require
investigation into the drivers of these unusual, high variations lot-to-lot.
Additional Information:
39. Tables below summarizes the top lots for Pfizer and Moderna products withrespect to the numbers of Serious Adverse Events and Deaths for reports
submitted from the United States, and from Foreign Locations.
AllC19Vaccines, US Only
VaccineAll AE
Manuf
Lot
Reports*
SAE** Deaths***
Pfizer
EN6201
3020
622
139
Pfizer
EN62002638
580
110
Pfizer
EN53182935
507
108
Pfizer
EN61982497
486
103
Pfizerel9261
2015
391
100
Moderna 039K20A
5297
299
97
12

Pfizer
EM98101308
348
94
PfizerEL32482085
286
90
Pfizer
EN62022457
474
87
PfizerEL92691585
360
87
PfizerEL32492177
313
79
Pfizer
EL33021622
270
75
Moderna 013l20a
3290
274
72
PfizerEL89822067
270
71
Moderna 012L20A
3175
260
69
Moderna 010m20a
2282
260
67
Pfizer
EN62082754
445
66
PfizerEL92671253
251
66
Pfizer
EN61992307
371
65
PfizerEL9264
1580
242
63
PfizerEL01401842
187
63Moderna 037K20A
3007
212
60
Pfizer
EL12832457
287
59
Notes:*All Lot Numbers within the Range of Adverse Event Reports**"Serious" tag in VAERS search, included in AE
Reports*** Deaths are included in AE and SAE
Reports
All C19V Manufacturers, Foreign Locations
All
Manuf
Vaccine Lot
AE
SAE Deaths
Pfizer
EK97882538 729
136
PfizerER17412130 419
19
Pfizer
EM0477
1923 773
230
Pfizer
EW41091913 296
6
Pfizer
EJ67971885 413
73
PfizerER17491756 313
9
Moderna
039K20A
1653 121
65
Pfizer
EP96051525 597
53
Pfizer
ET88851512 208
5
Pfizer
EW31431484 197
6
Pfizer
EL14841433 354
37
PfizerFD68401286 201
12
Pfizer
FE62081267 164
1
Pfizer
EJ61341229 464
90
Pfizer
FA10271229 154
1
Pfizer
EW22391220 431
70
13

Pfizer
Pfizer
Pfizer
Pfizer

EJ6136
Ff3319EM4965
EP2163

1209
1207
1197
1159

197
141
212
509

41
0
2
68

40. Additionally, based on published news reports, in January 2021 the Orange
County (CA) Health Care Agency recalled the use of a Moderna COVID-19
vaccine lot following reports of allergic reactions.
https://www.ocbj.com/news/2021/jan/19/oc-recalls-moderna-vaccine-lot/
41. At the time of the recall, the injections from this lot were given to 5200 people in
Orange County.
42. The news article indicated that the Moderna vaccine lot 041L20A was underinvestigation by the Centers for Disease Control and Prevention, U.S Food andDrug Administration and the manufacturer.
43. Nevertheless, this lot from Moderna was distributed in 40 US states and territories,
where it was continued being administered, which resulted in the following total
Adverse Events and Deaths (see attached file with all reports for this lot inTechnical Appendix):• Adverse Events: 2796 reports (by date of vaccination from January 2021 toNovember 2021)• Serious Adverse Events: 193 reports (by date of vaccination from January
2021 to May 2021)• Death: 35 reports (by date of vaccination from January 2021 to March 2021)

Declaration of Responsibilities
44. I understand that my overriding duty is to the Court, both in preparing reports andin giving oral evidence and I have complied with this duty.
I confirm that I am aware of the requirements of Part 35, practice direction 35 andthe Protocol for Instruction of Experts to give evidence in Civil Claims.
I have set out in my report what I understand from those instructing me to be thequestions in respect of which my opinion as an expert is required.
I have done my best, in preparing this report, to be accurate and complete. I havementioned all matters which I regard as relevant to the opinions I have expressed.
All of the matters on which I have expressed an opinion lie within my field ofexpertise.
I confirm that I have made clear which facts and matters referred to in this report
are within my own knowledge and which are not. Those that are within my own

14knowledge I confirm to be true. The opinions I have expressed represent my trueand complete professional opinions on the matters to which they refer.
I have drawn to the attention of the Court all matters of which I am aware thatmight adversely affect my opinion.
Wherever I have no personal knowledge I have indicated the source of factual
information.
I have not included anything in this report which has been suggested to me byanyone, including lawyers instructing me, without forming an independent view ofthe matter.
Where, in my view, there is a range of reasonable opinion, I have indicated theextent of that range in the report.
At the time of signing the report I consider it to be complete and accurate. I will
notify those instructing me if, for any reason, I subsequently consider that thereport requires any correction or qualification.
I understand this report will be the evidence I will give under oath, subject to any
correction or qualification I may make before swearing to its veracity.
I believe the facts I have stated in this report are true and that the opinions I haveexpressed are correct. I understand that proceedings for contempt of court may bebrought against anyone who makes, or causes to be made, a false statement in adocument verified by a statement of truth without an honest belief in its truth.

A Latypova
28/12/2021 18:00:04

Alexandra Latypova
Signed: …………………………….
Alexandra Latypova

Date: 28th December 2021

Source files for all data downloaded from VAERS and examined in this report are available in TechnicalAppendix

Alexandra Latypova
326 Barrett Dr, P2981
Stateline, NV, 89449, USA
latypova@hotmail.com

15This Document has been Signed with a secure electronic signature via E-Sign.

Document Details
Title

ALEXANDRA LATYPOVA EXPERT REPORT.docx

AuthorBroad Yorkshire Law (claims@broadyorkshirelaw.co.uk)

Document Created on

Tue, 28 Dec 2021 16:17:18

Digital Fingerprint

e65d3105-2554-421c-900f-a206b8911c44

Document Signers Scan/Click the QR Code to view signature information
Name

Alexandra Latypova

Emaillatypova@hotmail.com

StatusSIGNED at Tue, 28 Dec 2021 18:00:05

Signature Fingerprint

728d2a14-ca72-417e-b746-24ff2aed70ae

Document History
Tue, 28 Dec 2021 18:00:06

Alexandra Latypova Signed the Document