BioNTech-InstaDeep Early Warning System to Detect High-Risk SARS-CoV-2 Variants (opens in new tab)

This is the kind of education that needs to be done in high school during health and biology classes. We can’t hope the general public will become epidemiologically literate on 240 character tweets and 30-second television quotes. Heck, my old high school biology teacher remains a source of coronavirus FUD, so maybe that’s not even enough.

Public messaging often includes the more extensive PANGO lineage (e.g., B.1.1.529 for Omicron). I think there is a limit to what can be conveyed in each news story.

Well to be classified as a variant it would have to be phenotypically different right? And also viable enough to infect a number of people.

I am the second author of the paper. We have been putting our head on the line for the last half a year. We detected Lambda, Mu (with a caveat, that we did not consider it competitive) and Omicron - all blindly.

We have been verifying all our predictions experimentally, post factum. And the method is purely data driven - with no fitting to the experiments or observations.

The first author came up with the approach, participated in analysis and got his hands dirty as everyone else. While he is a CEO of a 160+ person company, this has been a labor of love for all of us, done to a large extent in the evenings, during weekends and holidays. It is indeed an unusual situation. But this was not a regular project and InstaDeep is not a regular company either.

Because of both founder effects and potentially people taking earlier containment actions, I’m unsure that’s a realistic measure.

It’s like how people said Y2K was just a conspiracy theory because most systems kept running — without realizing the early warnings and preparations is the reason Y2K wasn’t a civilizational disruption.

> As a side note, the first author on this paper is the CEO of InstaDeep. I see it as a red flag that the CEO of a 150+ person company would put themselves as first author on this paper. Perhaps I'm unfairly judging and the CEO really was the lead contributor to the study.

Authors on scientific papers are ordered by name, so whoever's name is first is pure coincidence.

Another author of the paper here. We are recruiting in case you would like to contribute in further meaningful projects. https://www.instadeep.com/about-us/careers/

We are actively looking for motivated colleagues. Feel free to look at the page above or drop us an email at hello[at]instadeep.com. We are also happy to make new friends and work together on exciting projects - same email as above works.

From the wikipedia page you linked:

> Molnupiravir is indicated for the treatment of mild-to-moderate coronavirus disease (COVID-19) in adults with positive results of direct SARS-CoV-2 viral testing, and who are at high risk for progression to severe COVID-19.[1][5]

So after the risk of creating mutations in the Covid virus has been assessed and weighed against the chances of patients just outright dying due to not having this medicine available, the board full of medical professionals trained in this matter voted 13 to 10 that they thought the risk was acceptable.

"I'm all for stopping new variants of COVID"

That's very likely not even possible[1]; and, it not being realistic, would be a waste of time, effort, and money. There are lots of corona viruses that we have never stopped, and we live with via herd immunity, hygiene, and therapeutics[2].

[1] https://www.acsh.org/news/2020/11/05/covid-why-we-will-never...

[2] https://www.cdc.gov/coronavirus/general-information.html

Because it helps keep people alive and the risks are judged to be worth the cost in high-risk patients. Hopefully Paxlovid will obsolete this one soon enough though.

How does it seem clear to you? What's the mechanism through with Molnupiravir creates new CoV mutations?

Because it’s possible to justify the risk with saving lives.

Because creating mutations and prolonged pandemics are more profitable.

Pretty cool stuff!

> When using a weekly watch-list with a size of 20 variants (less than 0.5% of the weekly average of new variant sequences), EWS flagged 12 WHO designated variants out of 13 (Fig. 4.A), with an average of 58 days of lead time (i.e two months) before these were designated as such by the WHO (Table S.4).

> Our system however does not accurately pinpoint the emergence of the B.1.617.2 Delta family of variants. Delta is known to be neutralised by vaccines24 and its global prevalence can be attributed to other fitness-enhancing factors [than immune escape]. These factors, such as P681R mutation, which abrogates O-glycosylation, thus further enabling furin cleavage, are outside of the scope of our approach.

> Specifically, the EWS identified Omicron as the highest immune escaping variant over more than 70,000 variants discovered between early October and late November 2021.

That's the key bit here. Supervised learning is not applicable here and any sort of fitting to known labels is doomed to fail. The system is not calibrated, tuned or parameterized. The ML part learns in a self-supervised manner what are the spike sequence features important for a successful (proliferating) coronavirus (or - more correctly - learns low-dimensional embeddings of multi-point interactions/co-occurrences of different amino acids in spike proteins). The rest is based on either frequentist statistics, or computational biochemistry. At no point in training EWS any information about certain sequences belonging to High Risk Variant classes (Variant of Concern, Variant of Interest etc.) is fed to EWS.

Is the concern that this tool would be prioritized over other information?

Like what is the harm in doing the data collection and publishing about how it is going?

One of the authors states here that the goal was to create sanity(data) for the press to reference on each new variant.

Not exactly "finding out", but rather estimating. It's all about prioritizing testing through detecting suspiciously "good" and unexpected outliers popping up.

The idea is to introduce a bit of sanity into the current world, to calm down overreactions to every new, scary looking variant. And on the flip side - to identify the truly scary ones early on, so that proper measures can be taken.

But the idea above directly follows from the work in the paper.