Sahin Boydas
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AI Drug Discovery: Why a Niche Wins

I've been in the Silicon Valley trenches for over a decade, and I've never seen a shift as massive as AI in healthcare. I'm sharing the hard-won lessons from my own startups and investments—the wins, the failures, and the counterintuitive strategies that actually work.

2024-08-216 min read536 words

I've been in the Silicon Valley trenches for over a decade, and I've never seen a shift as massive as AI in healthcare. I'm sharing the hard-won lessons from my own startups and investments—the wins, the failures, and the counterintuitive strategies that actually work.

What I've Learned From 132 Companies

Across 234 angel investments, including Anthropic, a few patterns in AI drug discovery come up again and again.

The founders who handle AI drug discovery well understand that the best solutions are often the simplest ones.

The Reality Nobody Talks About

A lot of the advice on AI drug discovery rests on assumptions that made sense five years ago. The world has moved on.

The first thing to understand is that most founders overthink this and underspend on execution. I've seen this play out across dozens of companies. The pattern is unmistakable.

Many teams spend months on the wrong path before realizing that you need to move fast and break things. Once they make the switch, everything changes.

Lessons From the Trenches

I want to share a few specific lessons I've picked up over the years. These aren't theoretical. They come from real companies, real failures, and real successes.

Lesson 1: The best time to start thinking about AI drug discovery was yesterday. The second best time is now. Don't wait until you have the perfect plan.

Lesson 2: Hire for attitude, train for skill. The best people at AI drug discovery are rarely the most technically gifted. They are the most curious and persistent.

Lesson 3: Your competitors are probably getting this wrong too. That's your opportunity. While everyone else is following the same playbook, you can zig when they zag.

This connects to broader themes around AI diagnostics, biotech AI, clinical AI, drug discovery AI, AI mental health that I've been thinking about a lot lately.

Wrapping Up

I've shared a lot here, and I know it can feel overwhelming. But you don't need to get AI drug discovery right on day one. You just need to get started and keep improving.

Founders who do well at AI drug discovery tend to share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.

That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.

As always, I'm rooting for you.

FAQ

Frequently Asked Questions

Q:Do all experts agree with this view?

No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.

Q:What's the most common pushback you get on this?

People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.

Q:How has this view evolved over time?

My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.

Written by

Sahin Boydas

Serial entrepreneur, #1 angel investor, author of Becoming Top 1%

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