I have been speaking about the C-19 bio-chemical poison variability lot-to-lot since early 2021 when these bio-chemical weapons first hit the market. I got immediately banned on mainstream social media, even my Instagram account dedicated 100% to art was nuked and I have not been able to get it back. That was completely expected. The criminal cartel were going after all professionals, and anyone credible in this topic got immediately suppressed and smeared. What I was surprised by - the disregard for the subject, and dismissal of me as a “conspiracists” by “prominent voices” on the health freedom side. You know who they are

I don’t take this personally, ever, and I attribute the misguided attitude on this issue to just being, well, misguided. No practicing doctor or PhD in academic sciences ever made any pharmaceutical or medical device, produced at scale safely and in regulatory compliance to cGMP. Therefore, they think it is a minor problem that gets taken care by the lowly manufacturing people. They do not understand the significance, difficulty or the sheer scale of effort required, and therefore see this issue (mistakenly) as a threat to THEIR preferred narrative of “jabs are bad”. They believe pointing to the variability lot-to-lot means that some batches are “good”, and that this problem will be simply fixed by the lowly manufacturing people some day, and the vaxxes will remain in use as “good batches only”.

This is absolutely wrong! Ability to manufacture the product to cGMP standards determines whether the product can exist as a pharmaceutical in the first place. That comes before clinical trials, before safety and efficacy can be even assessed. If you cannot demonstrate that you are making the XYZ formulation every time, in every pill, vial, capsule, in millions and billions of them, in every batch - you cannot BEGIN to assess whether XYZ is safe or efficacious for anything! Thousands of papers have been written by academics and doctors about the spike protein. “Their” side writes that it is efficacious for preventing covid, “our side” writes that it is deadly and destructive. But we have no evidence yet that spike making components are in every vial and every shot. Far from it! That’s because the manufacturers cannot make those reliably, if at all! And it is not a simple problem, and nobody is in a hurry to fix it - after 2.5 years it only got much worse with the bivalent productions. Of course, we know why - the criminal government-pharma cartel is fully aware of this. To them it is a feature, not a bug: the randomness of the product is a desired feature of a state-of-the-art weapons system ordered by the US Department of Defense from pharma companies as part of the global military operation.

Back in 2021 I met Craig Paardekooper due to us being seemingly the only 2 people on the planet who noticed the batch variability issue. There was a third person, a friend in Texas who was instrumental in quickly pointing out this issue but he preferers to stay anonymous. Craig and I worked on the website that he coded and has been running successfully - How Bad Is Your Batch (www.howbad.info). My early analyses are still available there. The site has grown to an incredible resource of all things related to tracking batches, vax injury and death, and many other related data analyses. Thousands of people reported to us that this site and related batch variability data were the only things that were able to “redpill” their brainwashed family and friends, and I take it as a big win. As of late 2022, the site had over 100 million visitors from all over the world.

There were other researchers who were pointing to this issue and related issues of product contamination, sloppiness of manufacturing and disregard for consumer protection - all hallmarks of the criminality involved in the entire program:

Vinu’s Newsletter

Fraudulent drug safety studies have destroyed medicine; "Safety" researchers ignore lot-to-lot variation but in reality 100X difference in contaminant level, adverse events, is common

A recent study in the BMJ claimed no association between COVID-19 vaccines and Bell’s palsy. However, it is obvious from the Pfizer and Moderna trials that the vaccines induced Bell’s palsy. The 7X difference in the number of Bell’s palsy cases observed between vaccine and placebo arm has only a…

2 years ago · 54 likes · 18 comments · Vinu Arumugham #RFKJr2024

Around late 2021-early 2022 Craig and I talked to Max Schmeling, a statistician and an economist from Denmark, and a few of his colleagues about our analyses of the batch data from VAERS, and we discussed a similar dataset that they obtained from the European health authorities. Max and his colleagues were early advocates of looking at the alarming batch variability data as clear evidence of malfeasance and law breaking. He wrote letters to Danish politicians on this topic.

Max was finally able to publish his analysis of Danish adverse event reports by batch numbers as a letter to the editor of a mainstream peer reviewed journal European Journal of Clinical Investigation.

Here are the findings:

A total of 7,835,280 doses were administered to 3,748,215 persons with the use of 52 different BNT162b2 vaccine batches (2340–814,320 doses per batch) and 43,496 SAEs were registered in 13,635 persons, equaling 3.19 ± 0.03 (mean ± SEM) SAEs per person. In each person, individual SAEs were associated with vaccine doses from 1.531 ± 0.004 batches resulting in a total of 66,587 SAEs distributed between the 52 batches. Batch labels were incompletely registered or missing for 7.11% of SAEs, leaving 61,847 batch-identifiable SAEs for further analysis of which 14,509 (23.5%) were classified as severe SAEs and 579 (0.9%) were SAE-related deaths. Unexpectedly, rates of SAEs per 1000 doses varied considerably between vaccine batches with 2.32 (0.09–3.59) (median [interquartile range]) SAEs per 1000 doses, and significant heterogeneity (p < .0001) was observed in the relationship between numbers of SAEs per 1000 doses and numbers of doses in the individual batches. Three predominant trendlines were discerned, with noticeable lower SAE rates in larger vaccine batches and additional batch-dependent heterogeneity in the distribution of SAE seriousness between the batches representing the three trendlines (Figure 1). Compared to the rates of all SAEs, serious SAEs and SAE-related deaths per 1.000 doses were much less frequent and numbers of these SAEs per 1000 doses displayed considerably greater variability between batches, with lesser separation between the three trendlines (not shown).
The observed variation in SAE rates and seriousness between BTN162b2 vaccine batches in this nationwide study was contrary to the expected homogenous rate and distribution of SAEs between batches. In Denmark and other EU/EEA countries, vaccine quality is monitored according to Official Control Authority Batch Release (OCABR) guidelines and to our knowledge, potential differences in BNT162b2 vaccine batch clinical safety or effectiveness have not been reported previously, for example in pre-authorization trials and subsequent population-based studies.⁴^,⁵ Such effects may be easier to detect in small countries like Denmark where BNT162b2 vaccines during the study period were generally provided in several smaller batches. Also, regulatory monitoring and scientific interest in COVID-19 vaccine safety have primarily focused on serious adverse events, for example myocarditis.⁶ In any case, identification of such effects evidently requires that observed adverse events are linked with the respective individual batch labels and sizes (dose numbers). Previously, variation in the production (culture growth) of the Bacille Calmette-Guérin vaccine has been shown to influence important immunological effects of this vaccine,⁷ and two cases of myocarditis have been reported in two young males after receiving mRNA-1273 COVID-19 vaccine (Moderna) from the same vaccine batch on the same day.⁸ Indeed, variations (batch-to-batch, vial-to-vial and even dose-to-dose) in vaccines may occur as a result of variabilities and practice breaches in, for example vaccine manufacturing, storage, transportation, clinical handling and control aspects, and in 2021, three lots of the mRNA1273 vaccine totalling more than 1.6 million doses were recalled in Japan after 39 vials of the vaccine were found to contain foreign materials.⁹ Leaked and contested data have also suggested that some early commercial batches of the BNT162b2 vaccine contained lower than expected levels of intact mRNA.¹⁰

FIGURE1: Numbers of suspected adverse events (SAEs) after BNT612b2 mRNA vaccination in Denmark (27 December 2020–11 January 2022) according to the number of doses per vaccine batch. Each dot represents a single vaccine batch. Trendlines are linear regression lines. Blue: R² = 0.78, β = 0.0898 (95% confidence interval [CI] 0.0514–0.1281), green: R² = 0.89, β = 0.0025 (95% CI 0.0021–0.0029), yellow: R² = 0.68, β = 0.000087 (95% CI 0.000056–0.000118). Vaccine batches representing the blue, green and yellow trendlines comprised 4.22%, 63.69% and 32.09% of all vaccine doses, respectively, with 70.78%, 27.49% and 47.15% (blue trendline), 28.84%, 71.50% and 51.99% (green trendline), and 0.38%, 1.01%, and 0.86% (yellow trendline) of all SAEs, serious SAEs, and SAE-related deaths, respectively.

A couple of comments to the detractors of this analysis:

All standard covariates never explained more than 30% of batch variability data. Meaning 70%-90% of it remains unexplained by things like age, socioeconomic or health status of the injected population;
Adjustments by lot size do not explain lot variability (as Max has shown);
Adjustment by USED doses in a batch is impossible as we do not have that data. And in practice, I am not aware of any drug pharmacovigilance system that is designed to track reports based on used doses per batch. Batches get pulled from the shelves when “many” reports for them come in, and usually the thresholds triggering a pull are quite low. Nobody in their right mind who is facing product liability would insist on doing the math on how many doses from the batch were administered before recalling a lot, as they would be digging themselves a deeper liability hole. Therefore, this adjustment is a theoretically nice thing to have but not necessary for drawing actionable conclusions. The main issue here is product liability, or rather lack of any product liability for C-19 poisons which enables complete criminality in their production.
In practice, when we look at the flu vaccine data by batch, over 20 years, numerous manufacturers, lot sizes, etc. - there is barely any variability. If one looks at any cGMP compliant product - aspirin, antibiotics, saline, or even something poisonous as chemo drugs for example, same thing happens. The more inherently toxic substances will have more batch variability, but not 1000% batch to batch!

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