Derek Brand

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!!

You have $300 million in spare cash... You can pick anywhere in there world... And you pick.... Naples.

I'm on team "I don't care how you made your damn drug" just show me: INDs filed, patients dosed, trials completed, BLAs filed, successful commercial launches, & patients able to access that drug that makes them better. Everything else is noise, always has been, always will be.

NYC is 30x better than Chicago.

As someone who has helped companies pioneering the use of AI for drug discovery, this is BS. Sure, AI is a tool that we all should deploy to the best of our abilities, but the idea that AI is going to unveil new medicines at a stunning rate the way it will upend cinema, video games, financial services, advertising, gambling, etc., is a bit absurd. New medicine discovery will be one of the laggards in terms of AI revolution. Healthcare provision, diagnostics, and paperwork streamlining will all move ahead faster. Biology will continue to eat everything, AI included.

A 700-year-old castle in Kent with a moat, a jousting yard, 42 acres and nine cottages, where Henry VIII dined with Anne Boleyn. Just listed for $6.6 million. In Manhattan, that buys you a two-bedroom with a doorman who reports to your wife.

What’s stopping you from buying this $54,500,000 Beverly Park mansion?

So ice hockey. Where do I begin eliminating teams if I were to choose a team to get behind. Which ones are out of the question?

The list of chants so far tonight. - You can't read - You eat crayons - Traitor - Matthew's better - We don't need you - Little brother - Fuck you - Brady sucks - Timmy's better -Brady’s balding - You’re a sellout - Matthew’s bridesmaid.

This isn't true. People watch full 2 hour podcast episodes on YouTube. You have to make things worth watching

Simple: ship a working version of the @theranos vision powered by SI Could be 10% of the original vision, with the promise to keep iterating For bonus points open source all the technology and patents And given the pace of super intelligence, someone will and then folks will start saying “seeeeeeeee! @ElizabethHolmes was just too early!!!” I will leave it to @nathanfielder and @JohnCarreyrou to adjudicate that moment! 😂😂😂 [ go see the film ]

Bryan, you’re right that for someone measuring hundreds of biomarkers a month, the genome adds less on the cardiometabolic side. But you’re an outlier. Most people don’t want to test themselves continuously, and most can’t. Even for you, your genome answers questions your biomarkers can’t. Blood work shows where you are now, not what’s coming. If you carried a BRCA2 variant, your prostate cancer risk would be meaningfully higher, often with earlier onset and faster progression. No panel flags that risk, but it changes when you start screening and how often. And most people with harmful variants in genes like BRCA1 and BRCA2 are not aware that they have them. There are also new and impactful discoveries still being made from the genome. We recently published a Science paper with Dana Farber on our discovery of an EGFR variant that increases lung cancer risk by 25x - far more than smoking history does (~3.8x). Lung screening guidelines are based on smoking history, so carriers go unnoticed unless someone reads their genome. The negatives matter just as much. Knowing you don’t carry a high-risk variant is information too. It enables you to know you don’t need increased screening beyond what guidelines recommend. Your APOE result counts even though it didn’t change your protocol, because it ruled something out. The genome also answers questions that go beyond your own health. For anyone planning to have kids, carrier screening shows whether both parents carry a recessive variant for a heritable condition like cystic fibrosis or spinal muscular atrophy. It’s an answer you want before a pregnancy, not after, and learning you’re not a carrier is just as valuable. This isn’t niche. On Friday at the American Society of Human Genetics (ASHG), Dr. Noura Abul-Husn presents data on ~6M people who got 23andMe health reports. More than 1 in 10 (660K+) had a medically actionable result linked to a health risk with established screening or prevention guidelines. These results change how people understand their personal health risks and empower them (and their doctors) to take action to stay healthy. Your genome isn’t a daily dashboard. It tells you which dashboard to build, and where to focus your attention.

The only opinion that I care about re: Elizabeth Holmes and "You can see everything" 👇

If you don't think that there is a bubble in AI x Bio valuations, just consider that the purported valuation of Isomorphic Labs is more than that of Revolution Medicines. Investors are acting as if preclinical Isomorphic already has an approved KRAS scale blockbuster.

No question that @IsomorphicLabs and other AI drug discovery initiatives can radically accelerate the process, which today is ridiculously protracted. But the objective or expectation of finding "cures" for all diseases is unrealistic IMHO, no matter how much capital is invested. Good summary of today's news @grok

Stepbrothers Dayyan Armstrong and Ross Beane have been adventuring together since they were both 7. With Sailing Collective, they want to bring you along. on.wsj.com/3TLeSr1

BREAKING: Elon Musk says SpaceXAI will be renamed to "SpaceXSI" after President Trump changed the name of "Artificial Intelligence (AI)" to "Super Intelligence (SI)." "No more AI. SI. It’s better," Elon Musk says.

The patient view of forever chemo for #cancer