When I last wrote about AI on this blog three years ago, I spoke of it being a tool with the potential to transform scientific discovery, but the application I described was primarily theoretical. For AI to be a meaningful tool in R&D, I argued, we needed better sources of “truth” – better data sets that AI tools could query and learn from over time – and technology capable of integrating multiple steps into a semi-automated system. My message was that AI-enabled drug discovery was coming…someday.
Fast forward to 2025, and that someday is now.
We’ve seen an explosion in the availability and capability of AI tools. Just 10 months after I wrote about the theoretical possibilities of AI in biopharma, OpenAI debuted ChatGPT. Shortly after that, we saw the rollout of Microsoft Copilot and Meta AI. We now have immense computational power at our fingertips, with programs specifically designed to query biological problems. Combined with the ingenuity of skilled scientists, who can define the research problem and generate curated datasets that will enable solutions, AI has become an important and practical tool that is helping researchers accelerate discovery (link to Google DeepMind podcast on this topic here).…
At the beginning of the summer, I had the opportunity to join the team at Royalty Pharma for a great event at MIT (link here). It was an interesting time for me as I was thinking about the new role I was about to take at Bristol Myers Squibb. While I had certainly been “a leader” for several years now, I was pushing myself to think through and question my perspectives on R&D now that I was taking on increasing responsibilities as “the leader” of the research organization.
And so the presentation opportunity with Royalty really pushed me to articulate my views in a way that would hopefully resonate with and inspire others. I titled my presentation “Bullseye.Aim.Fire” and then renamed it “Increasing R&D Productivity to Deliver Transformational Medicines” so the topic would be more obvious. What I’m really sharing in the presentation is my fundamental belief about R&D, linking together several factors that I see as mission critical.
To me, it really all comes down to causal human biology. In order to be successful, we must understand the cause-and-effect relationship between perturbing a particular biological target with a medicine and the outcome that will then impact human physiology.…
“Water does not resist. Water flows…But water always goes where it wants to go, and nothing in the end can stand against it.” – Margaret Atwood
“The path of least resistance leads to crooked rivers and crooked men.” – Henry David Thoreau
What fraction of potential protein targets is accessible to conventional therapeutic modalities such as small molecules and protein biologics? The “druggable genome”, a term coined by Hopkins and Groom in 2002 (here), provides an estimate: approximately 10% of proteins in the human body are druggable by small molecule therapeutics. Greg Verdine and others estimate that an additional 10% of protein targets – those that are extracellular proteins – are druggable by biologics (here; excellent podcast by Janelle Anderson, humanPoC, here). Derek Lowe, however, has blogged that there is a lot of uncertainty in these estimates (here, here).
These two issues create a natural tension for drug hunters at the start of a drug discovery program: pursue those targets that are druggable or those targets with the most compelling human evidence.…
