Until a few months ago, I hadn’t given much thought to Moloch, the ancient figure associated in historical texts with extreme and costly sacrifices. But as I prepared for a conversation at SXSW with World Series of Poker champion turned game-theory evangelist Liv Boeree, I found myself going down a Moloch rabbit hole.

In her TED Talk and Win-Win Podcast, Boeree talks about something called “Moloch’s trap,” a concept that originates from Scott Alexander’s seminal 2014 essay “Meditations on Moloch.” In ancient accounts of Moloch, people are described as offering up things of immense value – most starkly, their own children! – not because such acts were desirable, but because they believed making such sacrifices would avert something far worse. Alexander uses Moloch as a metaphor for coordination failures: situations where individually rational, self-interested decisions by multiple actors collectively produce outcomes that are bad for everyone.

Boeree extends this metaphor further: Moloch’s trap is the name we give systems where no individual is the villain, yet everyone is complicit – and the consequences are severe. It is, importantly, distinct from simple greed or bad intent. It is a structural trap, where even well-intentioned, intelligent actors get pulled toward destructive outcomes because the incentive architecture leaves them no choice.…

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In a previous blog post, I argued that pharmaceutical Research and Development (R&D) is more like poker than chess given the probabilistic nature of developing new medicines. In this blog, I build out this argument further and introduce a new concept, the Critical Value Creation Period (CVCP). The CVCP is the moment in R&D where the probability of success (PoS) for an investigational medicine becoming a new medicine jumps substantially. For most investigational medicines, this period is in early clinical development. By analogy, early development is like the “flop” in Texas hold ’em poker. Stay with me on this one…hopefully this will become clear by the end of this blog post!

Here, I first build out the CVCP argument, which is modeled after an investment thesis proposed by Bain Capital Life Sciences (see here for a presentation by Dr. Adam Koppel at BCLS). Then, I introduce the poker analogy – with focus on the flop. Next, I discuss practical implication of the CVCP model on decision making in biopharma. Finally, I provide two brief case studies that reinforce these concepts. For those not interested in poker, you can skip the second section and focus on the first, third and fourth sections.…

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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; link to a start-up’s pragmatic journey of AI in drug discovery here).…

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