Who knows, but I do have guesses, I'll just go through them. Obv this is my personal opinion that shouldn't be tied to anybody I work for
1. They are primarily a small molecule company, and seem to be having enough success there that they don't care about trying to make PPI stuff better (which is what MD, imo, will be primarily useful for…
Who knows, but I do have guesses, I'll just go through them. Obv this is my personal opinion that shouldn't be tied to anybody I work for
1. They are primarily a small molecule company, and seem to be having enough success there that they don't care about trying to make PPI stuff better (which is what MD, imo, will be primarily useful for).
2. They have relatively few computational/engineering people just from going through linkedin, seems much more heavy on the wet-lab side, the lift in creating these sorts of models may be out of their desired scope.
3. They also co-author a lot with DESRES. A lot of the MD work may occur with DESRES in-the-loop and they understandably may want to keep a lot of that stuff private.
4. And the last, most probable possibility is that creating these sorts of models is probably an organizational nightmare. It's so costly, requires so many of the right people, and takes an immense amount of patience for it to work well. PhD students at the right labs seem much better set up to create the first iterations of these models (e.g. AlphaFlow came from 3 people at MIT), I feel like companies will wait for it to be de-risked further + ideated upon before investing time into it. Relay isn't trying to be a general purpose research org (e.g. Deepmind), so I wouldn't expect them to make the same pie-in-the-sky bets.
Of course, there's always the chance that Relay tried this 2 years ago, it didn't work, and they moved on :)
Who knows, but I do have guesses, I'll just go through them. Obv this is my personal opinion that shouldn't be tied to anybody I work for
1. They are primarily a small molecule company, and seem to be having enough success there that they don't care about trying to make PPI stuff better (which is what MD, imo, will be primarily useful for).
2. They have relatively few computational/engineering people just from going through linkedin, seems much more heavy on the wet-lab side, the lift in creating these sorts of models may be out of their desired scope.
3. They also co-author a lot with DESRES. A lot of the MD work may occur with DESRES in-the-loop and they understandably may want to keep a lot of that stuff private.
4. And the last, most probable possibility is that creating these sorts of models is probably an organizational nightmare. It's so costly, requires so many of the right people, and takes an immense amount of patience for it to work well. PhD students at the right labs seem much better set up to create the first iterations of these models (e.g. AlphaFlow came from 3 people at MIT), I feel like companies will wait for it to be de-risked further + ideated upon before investing time into it. Relay isn't trying to be a general purpose research org (e.g. Deepmind), so I wouldn't expect them to make the same pie-in-the-sky bets.
Of course, there's always the chance that Relay tried this 2 years ago, it didn't work, and they moved on :)