Drug Discovery

“This is not a magic to discover drugs, because the hard part of drugs has always been candidates. Not candidates. It's always been efficacy and safety. The candidates have, since the eighties, have been able to develop more than we could test. It's human patie…”

“Our contention is that the highest leverage application of artificial intelligence Is the drug discovery and drug design process.”

“Predicting all of those properties is also just as important as, or maybe even more important than predicting the crystal structure itself.”

“I would say there's over 30 or so assays, each of which you could imagine if you're a neural net person, like a multitask neural network or multi-head, it's got to predict over 30, you know, three dozen-ish properties, each of which, if it's in the wrong range…”

“The reality is that the translation of high throughput screens, whether it's Dell, DNA encoded libraries, or more traditional screens, the R-squared of those predictions to, like, the actual business of resynthesizing a molecule de novo and doing a Low through…”

“I was told by some of my, you know, pharma executive friends that, you know, almost every drug Discovered from now on will have used alpha fold at some point in it, in the drug discovery process.”

“Pharma is a two trillion dollar industry. Of that trillion dollar, only a hundred billion dollars is in drug discovery, so this early stage. A hundred bill out of two trillion is a tiny fraction”

“Since the hardest part of drug discovery, whether in humans or dogs, is target validation, the lack of which leads to a lack of efficacy. The number one reason for drug failure.”

“Humanity isn't very good at drug discovery. Every now and then you kind of find a thing. It's amazing. Like you find a GLP one or you find like there's every, like there's a handful of drugs that are, we were lucky to find, but it's much more common that you s…”

“I think in future Almost every single drug that's discovered from now on will probably have used AlphaFold at some point in that process, which is, you know, amazing for us, and, you know, really, that's what we do, all the work we do for.”

“While I would love for that to happen, and I'm maybe more optimistic on a longer time scale, we will get there. I think in the short term, I'm next one to two years, which, you know, already feels like an eternity in AI time. I'm a little bit more bullish on s…”

“Simply doing prediction and getting that prediction right, and by the way, it doesn't have to be right a hundred percent of time, it has to be right, like, one percent of the time, because you can validate the other 99% were it right, and then finding that one…”

“I think we could reduce down drug discovery from taking years, sometimes a decade to do, down to maybe weeks, or even days over the next 10 years.”

“A big part of our future vision and roadmap is that we think there will be a moment where from a virtual cell model, a drug is spit out, and basically the drug will actually cause a healthy disease cell to become a healthy cell again.”

“Look, we'll have to figure that out because that'll be an issue once we get to what is, you know, somewhere maybe minimum 2000 or 5000 logical quantum bits, qubits. So that's at 2000 to 5000 or more is when you get into the encryption issues. I'd call it a 150…”

“Yeah, I think you touched on, like, probably the core problem of, like, you know, ML applied to science. While we have a lot of, like, unlabeled data, like, there's just not that much label data out there. And a lot of it is because, like, it's very experiment…”

“Usually in a drug discovery project, you know, if you have a hundred actives, you should be close to a drug, but a hundred data points is, like, tiny for machine learning, right?”

“If you look at the actual numbers of what makes drug discovery so expensive, it is the fact that 95% of drug programs fail. They just do not succeed.”

“We have product managers who do scrums and do you know, these agile planning processes, and we apply that also to our platform development, even on the biology side. But at the same time, you know, drug discovery projects, which are years long, you don't do sc…”

“Nothing kills a great idea faster and has been more of a disaster to innovation, certainly in my industry in drug discovery, than the idea of market projections.”

“Moreover, we can now see how building a large bank of human genetics variations will transform our understanding on optimizing of drug discovery and response, both for understanding side effects and toxicity, as well as making better drugs and going after new …”

“The return on investment for drug discovery is exponentially decreasing.”

“Particularly the earliest phase of discovery, that is an area where there's significant underinvestment just generally in the industry.”

“For most antibody research. The discovery process itself is a work in process. There's no formula for spitting out a drug by going through some set of steps that's going to work.”