I was prompted to write this question by reading this excellent blog post about AlphaFold I’ll quote it at length because it serves as a candidate answer to my question:
What is worse than academic groups getting scooped by DeepMind? The fact that the collective powers of Novartis, Pfizer, etc, with their hundreds of thousands (~million?) of employees, let an industrial lab that is a complete outsider to the field, with virtually no prior molecular sciences experience, come in and thoroughly beat them on a problem that is, quite frankly, of far greater importance to pharmaceuticals than it is to Alphabet. It is an indictment of the laughable “basic research” groups of these companies, which pay lip service to fundamental science but focus myopically on target-driven research that they managed to so badly embarrass themselves in this episode.
If you think I’m being overly dramatic, consider this counterfactual scenario. Take a problem proximal to tech companies’ bottom line, e.g. image recognition or speech, and imagine that no tech company was investing research money into the problem. (IBM alone has been working on speech for decades.) Then imagine that a pharmaceutical company suddenly enters ImageNet and blows the competition out of the water, leaving the academics scratching their heads at what just happened and the tech companies almost unaware it even happened. Does this seem like a realistic scenario? Of course not. It would be absurd. That’s because tech companies have broad research agendas spanning the basic to the applied, while pharmas maintain anemic research groups on their seemingly ever continuing mission to downsize internal research labs while building up sales armies numbering in the tens of thousands of employees.
If you think that image recognition is closer to tech’s bottom line than protein structure is to pharma’s, consider the fact that some pharmaceuticals have internal crystallographic databases that rival or exceed the PDB in size for some protein families.
I was once chatting with someone being business development at Sanofi. According to him they took 1 1⁄2 years to exchange a button on their website because their internal processes are filled with bureaucracy.
From that perspective there’s the justified belief that big pharma has no capacity to develop new technology of this kind inhouse. They could hire a bunch of AI Phds but they likely would drown them in bureaucracy so that they wouldn’t get the kind of results that AlphaFold got. It’s much easier to let someone else do the work and then license it.
I was prompted to write this question by reading this excellent blog post about AlphaFold I’ll quote it at length because it serves as a candidate answer to my question:
This was about AlphaFold, by the way, not AlphaFold2. (!!!)
I was once chatting with someone being business development at Sanofi. According to him they took 1 1⁄2 years to exchange a button on their website because their internal processes are filled with bureaucracy.
From that perspective there’s the justified belief that big pharma has no capacity to develop new technology of this kind inhouse. They could hire a bunch of AI Phds but they likely would drown them in bureaucracy so that they wouldn’t get the kind of results that AlphaFold got. It’s much easier to let someone else do the work and then license it.
Exactly. Machine learning is not pharma’s comparative advantage.