Bruce Booth

Peter Kolchinsky Verified account @PeterKolchinsky · 5d

Having waded through 163 pages of the draft COINS rule published by Treasury, my team and I can now respond with a simple graphic.

It will blind US companies and undermine our biopharma capabilities and national security, exactly opposite to what the policy is aiming to achieve. It does nothing to actually block a Chinese biotech from commercializing a drug in the US, with a European partner, European investors, or on its own. We value medicines highly and will now be paying others for them. Why would we do this to ourselves? We shouldn’t.

But you can’t submit a comic to Treasury so we wrote out a detailed comment that both lays out how the draft rule would backfire on American biotech and what revisions would allow Treasury to better achieve their stated national security objectives.

Have a look. Biotech investors and executives are welcome to sign onto our comment but the main purpose of publishing it now is to drive discussion that helps everyone sharpen their thinking and informs their own comment to Treasury, due Dec 7th. Anyone is welcome to crib from this. No need to ask.

We wrote it after considerable input from legal experts and peers. Since coins draft rule is itself unclear on many points, reasonable people can disagree as to its intent and meaning, so some of our comments address broader points meant to encompass a range of possibilities.

If you read what Treasury wrote, you might get the sense that they know this will backfire on America and are looking for support to revise their language to avert harm. So give this thought and submit your own analysis. We provide links in the article to the submission page.

And thanks to all who have already signed on.

@NPLB_org

racap.com/rapport/commen…

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Bruce Booth Verified account @LifeSciVC · Oct 31

It's Halloween. Here's a trick-or-treat "thought experiment" for Anthropic (or OpenAI) going big into the Life Sciences. Probably more trick, than treat, but here goes...

Both have made making medicines a top priority, as described in Anthropic's S1.  Right now they are taking some “small” bets in the space (~0.1% of expected market cap's).  These are welcome moves and we are hopeful for more engagement in #biotech in general from the frontier lab companies.

But if you are a $2T public company (as they are likely to be post-IPO), how could you achieve scale in this life science domain?  What’s the best way for maximum impact on bringing drugs to patients? [assuming that's the goal for their efforts in the life science]

I’d argue it's buying a large Pharma company and then radically changing the operating model to put compute and integration in the center.

Sort of like retrofitting a big Pharma R&D enterprise into a @NimbusTx model on steroids with compute and tech integration in the center, intercolated with deep biology and drug hunting capabilities, with operational execution on the periphery (impt, but not the driver). Own the learning loops, compress the DMTA cycle across a huge portfolio. Nucleate and empower teams around great potential medicines in a decentralized R&D model...

Let me get vaguely specific, for illustrative purposes.

Anthropic could buy $BMY for less than 10% of its market cap, an all-stock deal.

BMS has about 30,000 people.  Trim commercial (a distraction to the radical change mission) by selling the long list of tail products (top 5 products are 70% of revenues).

Then apply frontier AI models to the business across the board - commercial, manufacturing, and R&D. Tons of data sits in these silos. With data, figure out where the bloat is in the corporate bureaucracy and remove it. Be especially aggressive on scaling back G&A and the lawyers, replacing headcount in those functions with AI-enablement.  In the business functions, allow change-makers to focus on operational efficiency.

In R&D, BMS has about 3000 scientists/clinicians and operators on their R&D team.  Keep or even grow this group - its where the magic has to start.

BMS has a legacy of great R&D advances and has tons of historical data.  Frankly, they probably have some of the deepest datasets on mAb discovery (Mederex mouse one of the most prolific mAb platforms ever), induced proximity (CelMod and related datasets are without peer), cell therapy (Juno was a pioneer with one of largest CART datasets), radiopharma (more recently), and so much more. Deeply mine these datasets.

Take all the "me-too" R&D spend on crowded targets and dial it out of the portfolio...  Refocus all that energy on building deep biology datasets to complement the historical modality data. Invest in deep cell and tissue profiling, all the ‘omics, at scale and in an integrated way.  Put AI into the center of the operational workflow as an enabling tool for drug hunters, not replacing them. Work on fewer projects as a whole, but focus on “holy grail” drug targets and first-in-class/first-in-modality programs aiming for step-changes in treatment. And let AI operational efficiency compress clinical timelines as much as possible (10-20%).

Unleash teams of drug hunters with AI-powered R&D at scale on any/all therapeutic areas, not restricted to where commercial wants you to focus.  A true science-first enterprise at scale.  “A great medicine makes a commercial franchise, a commercial franchise doesn’t make great medicines” rings true to me here. Commercial voices, I'm told, dominate at BMS, even back in R&D. Maybe that's not optimal?

This would be a radical overhaul of a large R&D-intensive company.  Give the experiment 5-7 years to alter the vector of R&D output.  Long enough to see discovery-led changes percolate into early development and clinical PoC...

This kind of ongoing R&D investment would be tiny fraction of Anthropic’s revenues during that period, offset in part by the profits from the big commercial brands.  A rounding error for them, but if it worked, this would fundamentally alter the industry’s trajectory.

Probably can’t be done - changing large legacy groups is hard - but seems like the only near-term way to truly test “AI at scale in drug R&D” is thru something audacious like this, rather than just thru small (and beautiful) case studies of program-focused biotech …

With $5T+ of anticipated market cap between the handful of frontier lab companies, this seems like a relatively small bet on a big prize.

And, lastly, make @Prof_Oak_ head of the BMS business unit of $ANT.

Trick or treat? Boo!!

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Jason Rhodes Verified account @JasonPaulRhodes · Oct 31

On Mithril, AI, biotech venture capital...a few (more) thoughts.

First, big congratulations again to Cody @Prof_Oak_, who's terrific and keeps hitting it out of the park. He's been a vital colleague at @atlasventure

And big congratulations to @AnthropicAI on the acquisition and bringing Cody on board.

Mithril is a story about an intriguing new pharmacologic mechanism, a virtual team with deep disease biology expertise and killer track records in new therapeutic modalities, and AI for operational efficiency.

If I had to reduce the secret of success to one thing, in biotech and in life more broadly, it would be to surround yourself with great, great people.

Great biotechs pull the right people together for a common purpose, whether employees, consultants, advisors, or at CROs. Our companies have all of them along with all of the people and resources at Atlas that lean in, push, pull, sweat, and strive to build them.

Capital intensity and speed are critical issues in biotech. Anything that reduces the first and increase the latter with rigor is a good thing, including the clever application of AI to orchestrate teams of remarkable, real people.

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