AlQuraishi on why DeepMind won
Many of you will have seen coverage of Google’s DeepMind “solving protein folding” in the context of the CASP experiment this year (CASP announcement, Nature, Tech Review). Professor Mohammad AlQuraishi at Columbia wrote a detailed review and commentary on protein folding and DeepMind’s remarkable performance, and we highly recommend you read it in its entirety.
We wanted to highlight one section of Professor AlQuraishi’s write-up, speculating on why this breakthrough came from the DeepMind team and not an academic collaboration, which mirrors our motivation for tackling IVG as a startup:
[...] DeepMind is organized very differently from academic groups. There are minimal administrative requirements, freeing up time to do research. This research is done by professionals working at the same job for years and who have achieved mastery of at least one discipline. Contrast this with academic labs where there is constant turnover of students and postdocs. This is as it should be, as their primary mission is the training of the next generation of scientists. Furthermore, at DeepMind everyone is rowing in the same direction. There is a reason that the AF2 abstract has 18 co-first authors and it is reflective of an incentive structure wholly foreign to academia. Research at universities is ultimately about individual effort and building a personal brand, irrespective of how collaborative one wants to be. This means the power of coordination that DeepMind can leverage is never available to academic groups. Taken together these factors result in a “fast and focused” research paradigm.
It’s an understatement to say that there are differences between Google’s DeepMind and our three-person startup, but this insight into incentive structures is part of our reason for being. Our team cares about the clinical applications of in vitro gametogenesis, and the benefits it could bring to women and families, and we believe that a startup is the best way to align incentives to realize that goal.
Of course, our existence also critically depends on the scientific and technical inflection points which are driving our approach to IVG. But in light of those, the problem becomes, how do we incentivize the simultaneous solution of the myriad challenges making in vitro gametogenesis in humans scientifically possible, clinically safe, and commercially accessible?
That’s our mission, and our priorities reflect that: from our reprogramming system, which is designed to avoid genome modification and eliminate the need for donor tissue, to leveraging machine learning to accelerate and lower the cost of development. Our goal is to build a vehicle to solve this problem, to get everyone rowing together.
We’re just setting out, but that’s our vision. If you are excited by what we’re doing, don’t hesitate to get in touch! Whether it’s as a collaborator, partner, future colleague, or anything else, we’d love to hear from you.