Legacy & Leap

The next 20 years may demand not just smarter science, but the humility to admit how much we still don't know. Despite spectacular progress, we still can't cure metastatic cancer reliably, don't understand neurodegeneration's root causes, can't prevent autoimmune diseases, and struggle to explain the microbiome's role in health. Are we over-investing in targeted approaches while missing system-level insights? Will algorithms finally teach us what experiments couldn't, or must we wait for conceptual breakthroughs that no amount of data can substitute? Which current unknowns will become tomorrow's textbook basics and which will remain mysteries in 2046? Where do we need entirely new ways of thinking vs better tools?

Legacy, then leap. A conversation about how hard decisions get made: the calls taken without enough information, when a great deal was riding on them; what it takes to lead a company through the years after it has done something extraordinary; what AI is already changing about the judgment a leader has to exercise; and what all of that leaves as advice for the people who will run this industry next.

Billions of people walk through their days protected from measles, mumps, and polio without a moment's thought; the vaccines worked so well we forgot why we needed them. This is the paradox of scientific success: the better it works, the more invisible it becomes, and the easier it is to doubt. Meanwhile, foundational research funding is contracting. The pipeline of serendipitous discovery (the stochastic process that eventually yields breakthroughs no one predicted) is narrowing. The consequences won't be visible for 10-15 years. By then, it's too late to course-correct. How does an industry that speaks in clinical endpoints and p-values make its case to a society increasingly skeptical of expertise? What's the role of scientists, industry leaders, and institutions in rebuilding trust, and where have our own behaviors contributed to its erosion?

What made defining innovations from the past 20 years (immunotherapy's revolution in oncology, mRNA's emergence as a platform, and targeted therapies in rare diseases) truly transformative versus incrementally important? What actually enabled the breakthroughs that worked, not just the science, but the institutional structures, funding models, and stubborn persistence when consensus said stop? Then: What are we getting wrong right now? Which billion-dollar bets show warning signs we're ignoring? Which ‘fringe’ ideas will we celebrate, or regret ignoring, in 2046? And how do we build funding structures and early warning systems that let us fail faster, pivot smarter, and redirect resources before another generation of patients waits in vain?

When startups are built to exit, who takes the long bets? Who pursues the science that needs a decade, not a deal? Some companies stay independent, building pipelines rather than flipping assets, betting that nimble can compete with scale. Is that stubborn, or where the highest-risk science still gets done? Yet conviction doesn’t cover payroll. Capital markets reward quick returns, talent follows acquisition payouts, and regulatory costs don't care about your burn rate. And now Chinese biotechs are developing quality molecules faster and cheaper, licensing assets to Western pharma at prices domestic competitors struggle to match: a real challenge, and an opening for creative partnership.

What does it take to stay independent, and is it worth it? Are there categories of innovation that only emerge from companies not built to flip?