Recent comments in /f/IAmA

ShakeNBakeGibson OP t1_j7mcrga wrote

Love that we have one of our first questions even before the official start. Honestly, the millions of simulations that fail enable the one that solves the problem. Both matter!

…and yes, Viagra was a drug originally developed for hypertension and angina pectoris, and as the story goes, when the drug didn’t work that well for those indications and they stopped the trials, none of the participants wanted to give back their clinical trial drugs…. because, well, you know…

But counting on serendipity to give us outcomes like that, in diseases of higher unmet need of course, is not a recipe for success. So we’ve created Recursion to systemize serendipity. But we aren’t stopping at known drugs… we’ve built a dataset spanning over a million molecules that could help us find totally new drugs for many diseases. So its alternative uses, new uses, unexpected uses, and more.

My super fun lawyer would want me to also say: this discussion may contain forward looking statements that are based on current day estimates and operations and importantly are subject to a number of risks. For more details please see the "Risk Factors" in our 10-Q and 10-K SEC filings.

EDIT: added link to comment

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Novel-Time-1279 t1_j7mcq3y wrote

What evidence exists that the insights gained via single-cell perturbations can help uncover novel disease targets? A critic might say a single cell perturbations are simply not a good model for complex multicellular disease processes as the disease phenotype is rarely a linear sum of single cell phenotypes. Is the method most applicable to rare diseases with a clearly understood gene driver or also to highly prevalent diseases? I think Yumanity failed recently with their yeast disease model in neurology so I’m curious of how you address this criticism

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ShakeNBakeGibson OP t1_j7mcdru wrote

Thank you for the questions!
AI has made huge inroads into tough problems like protein folding. Huge credit to Deepmind and so many others there!
We’ve gone after a different problem than AlphaFold (and others). Can we understand the function of all the proteins in our body without necessarily needing to know the structure? If one could understand cause and effect of all the proteins (when they are overactive, not present, or broken, etc), we could start to better understand what protein to target… and that is important because 90% of drugs that go into clinical trials fail and most often that is because the wrong target is picked.
In terms of successes predicting the results of experiments — we can test ourselves by looking for “ground truths” about biology and chemistry – relationships and pathways that have been proven out in humans – that show up in our maps of biology and chemistry. When our teams search the map and see landmarks they expect, it gives them (and us) extra confidence to explore new ideas surfaced there.
And to your final question – while I can’t say exactly what we’ll charge for future medicines because we’re still fairly early in the development process, I do believe the best way to bring down drug prices is to industrialize the drug discovery process. If we can find a way to scale our pipeline, bringing better medicines to patients faster, with less failure, we can start to bend the cost curve. That’s our goal in the coming decades.

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BioRevolution t1_j7mbq3y wrote

Questions regarding your lab automation:

  1. What are your ambitions for the automated chemical synthesis platforms? And how do they compare to e.g. the Eli Lilly platforms that they build together with Strateos? (https://www.youtube.com/watch?v=fX1wssRFwaE)

  2. Have you looked into partnering up for advanced automation with companies such as Zymergen/Gingko Bioworks and buy their RACS (Reconfiguarble Automation Carts)

  3. What Vendors are you most happy with/planning to continue using in that area? Hamilton/Tecan/Thermo Fischer/Chemspeed...

  4. Can you show more footage of your automated labs?

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4rch t1_j7mb1oh wrote

It's comments that I'm seeing in this thread that have made me realize this isn't the same reddit I came to when Digg 4.0 came out.

There's giving feedback, and then there's being an asshole. Many people have quit their jobs to do something that other people don't value. Who gives a fuck if it's for a backpack.

Old reddit would have provided feedback and the assholes would have been downvoted, but you all have become so jaded that none of you can even take a moment for some empathy and understand why this person is doing it.

My backpack as a kid weighed 20 pounds, that shit has real impacts on children for years to come, so fuck OP for wanting to create something that is designed for kids when other brands have essentially just taken an adult backpack and turned it into a miniature version?

OP, I'm sorry that people here who downvoted you are the same people upvoting AMAs by billionaires and other "fan favorites" that I've seen over the years (Bill Nye).

So on behalf of OP, I want to give everyone a kind gesture and let them all know that even though they might not care about backpacks, responses like this create a chilling effect for small operations who want to do an AMA.

The top comment is "get a marketing department" for Christ's sake! You all are complaining about reddit becoming corporate but in the same breath give a noncorporate OP shit for not having the bland decorum of a corporate PR department!

There are real people behind each of our posts and I'm ashamed of each and every one of you. There's karma to get upvotes, then there's the bullshit I'm witnessing today.

For anyone who disagrees with my sentiment, my only request is that you downvote me to a point where my comment karma reaches 0, because the people who used to upvote posts aren't the same one upvoting shit now and I do not want to be associated with the pervasive negativity that reddit has become in recent times.

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Chance-Mammoth1245 t1_j7m8xyz wrote

You recently posted on LinkedIn that you were publicly sharing millions of microscopy images that Recursion had collected in order to enhance community drug development efforts. BUT, in that release, you purposefully kept 16,000 of the genes anonymous.

Are you trying to get the benefits of appearing to support "open science", while not actually providing data that could help your competitors?

Linkedin post: https://www.linkedin.com/posts/chris-gibson-5ab66065_introducing-molrec-and-rxrx3-activity-7024406260905050113-SWTp/?utm_source=share&utm_medium=member_ios

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