Christopher Bishop is the director of Microsoft Research AI4Science, which focuses on the intersection of machine learning and the natural sciences, such as using AI to speed up drug discovery. Q: Did you pick certain disease targets? A: Yes, COVID-19 and tuberculosis are the world’s two biggest killers in terms of infectious diseases. So they’re very obvious targets to go after. And then in partnership with [China’s Global Health Drug Discovery Institute], they helped define targets for us, meaning proteins that we can then try to build molecules that will dock with it. A real breakthrough here is the way in which we’re doing generative AI. We’ve had a partnership, for example, with Novartis for the last five years doing generative machine learning to design new drug molecules. That’s going extremely well. What’s very interesting about this particular model is the way we brought together some real state of the art technology, and showed that it leads to this very significant acceleration compared to what we had even a year or 18 months ago. The actual molecules that we’ve produced are very interesting. They are comparable to, or even superior to, the best known state of the art [ones]. They’re not themselves a final drug; they’re a lead to more optimization, testing, refinement. We’d love to see, eventually, some descendants of those molecules go into clinical practice. By using this generative model, we’re able to design new molecules that are actually target aware. We’re not claiming that’s the final molecule that’s going to cure TB. But the fact we could do that so rapidly is the real excitement here. We’re kind of on the beginning of this S-curve of research disruption in this space. I kind of wish I was 22 and doing a PhD again. The next decade is going to be phenomenal. And a year is a very long time in the field right now. Q: And this is a small molecule, meaning it could be stored for long periods at room temperature and taken in pill form. In the case of your work on COVID, is that also a small molecule? A: It’s the same story. The difference is the protein target. The starting molecules are different and the end molecules are different. But it’s the same architecture. Q: The COVID vaccines that we’re all used to are not small molecules. They’re these mRNA vaccines. So why wasn’t it possible to have a small molecule drug treat COVID? And this technology would make that possible where it wasn’t before? A: There are lots of factors there. Obviously, the power of the mRNA approach was incredibly impressive, so I’m not in any way belittling that. It’s an alternative approach to tackling COVID. We know that COVID is constantly mutating and changing, so it’s a different sort of vector. Whether this ultimately is how we tackle COVID long term remains to be seen. The thing we’re excited about is that we could take a disease that’s killing millions of people, and in a relatively short time, find a new state of the art molecule, compared to ones that were previously known.  MicrosoftQ: Do you see a world where you would basically design small molecule drugs for every iteration of COVID as it comes out? A: We’re very interested in working on an adjacent project, which is trying to predict where these mutations are going to go. Because they have a sort of random element. There’s natural selection that picks some of them as the survivors, and they can escape drugs. It will always be an arms race. But can we look one step ahead in the arms race, look one chess move ahead, and actually try to understand where it could mutate and anticipate that? The power of machine learning, deep learning techniques now to look across huge datasets of past mutations and understand the pattern of those mutations is really exciting. Q: So why is Microsoft funding this? A: What Microsoft brings to the table is, first of all, AI expertise. The other is Microsoft’s compute platform. And there’s an opportunity to partner with organizations like GHDDI, with drug companies, with materials companies, and together make these transformational advances. There should be good business in that. But it also should be good for the planet and good for other companies as well. Everybody wins in this sort of partnership. Q: In other words, there are revenue opportunities. A: The potential is so huge. There are opportunities both for societal impact and for commercial purposes for many organizations, including Microsoft. Read here for the rest of the conversation, including whether AI advances mean you can now start a drug company in your dorm room. → |
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