Brian Finrow retweeted
Clinical trials in the US are slow, costly, and often out of reach for patients who might benefit from participation. 1Day Sooner and 18 organizations, 13 of them rare disease groups, are backing the bipartisan Faster Clinical Trials Act from @RepAuchincloss and @RepMGriffith.
Infinita is proudly declaring its support for the "Faster Clinical Trials Act", a bipartisan bill introduced by Reps.
@JakeAuch (D-MA) and @RepMGriffith (R-VA).
Clinical trial reform at the federal level has suffered from a lack of ambition.
This is the first bill that I've g ambition whatsoever.
"The bill also sets targets to reduce the cost per patient for the clinical trials conducted by these networks by 30 to 50 percent and speed participant enrollment in those trials by 30 percent."
The mechanisms how to reduce costs are a distillation best policy research that I've seen over the years, incl. by @IFP, @RuxandraTeslo, @sytses & many more
The things I am most excited about:
- Bringing evidence generation closer into the clinic; proving real-world effectiveness has been an afterthought in FDA approvals, leading to lack of safety & efficacy
- Streamlined trial site networks that can be accessed via a "multi-site, single-IRB", overcoming the IRB fragmentation that is a major source of delay in early research
- Governance sandboxes - critically, the bill does not make the mistake of trying to fix everything at once. Its mandate is to support sandboxes, innovative trial models
With this, the US has a real shot at retaining its competitive advantage in biotech, and could do right by millions of patients to access trials in the US instead of abroad.
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Brian Finrow retweeted
There's a lot to focus on right now, but "The richest man to ever live just spent $200 million to support the Republican Senate candidate in Texas, and his man lost by double-digits in a statewide wipeout" is a completely insane sentence.
Put another way, the most expensive US Senate race before 2020 was $200 million. *One guy* spent that amount in Texas, and it doesn't seem to have made any difference. It might have hurt in a kind of Streisand effect way, in that the spending level was seen as obscene to people sympathetic to the argument that billionaires shouldn't "buy" elections.
The implications here seem pretty interesting! Especially re the limits of billionaire political power and/or the diminishing returns of money in politics.
Put another way, the most expensive US Senate race before 2020 was $200 million. *One guy* spent that amount in Texas, and it doesn't seem to have made any difference. It might have hurt in a kind of Streisand effect way, in that the spending level was seen as obscene to people sympathetic to the argument that billionaires shouldn't "buy" elections.
The implications here seem pretty interesting! Especially re the limits of billionaire political power and/or the diminishing returns of money in politics.
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Brian Finrow retweeted
Evidence is growing that we’re turning the corner on productivity.
US productivity grew at a 3.6% annual rate this past quarter.
That’s more than double the 1.5% average from 2007-2019.
The new numbers put me further ahead for my bet with Bob Gordon about productivity growth how far the US is now ahead of the CBO estimate at the start of the decade (before they knew about the pandemic or LLMs) courtesy of @jasonfurman’s
Econvitals.
US productivity grew at a 3.6% annual rate this past quarter.
That’s more than double the 1.5% average from 2007-2019.
The new numbers put me further ahead for my bet with Bob Gordon about productivity growth how far the US is now ahead of the CBO estimate at the start of the decade (before they knew about the pandemic or LLMs) courtesy of @jasonfurman’s
Econvitals.
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Brian Finrow retweeted
The best cultural criticism is impossible to unsee: the comparisons are so obviously true that once explained, they set in the back of one's minds forever. It almost feels like they have always been there, that they are obvious. So it is with Sitte, and with this excellent piece about his guide to building wonderful cities.
How can we make lovable cities? If you had asked a European architect this question in 1900, they would probably have referred you to a slender, lively book by the Austrian writer Camillo Sitte, translated as ‘The Art of Building Cities’. Published in 1889, ‘The Art of Building Cities’ swiftly came to be revered around the world.
worksinprogress.co/issue/the-forg…
Sitte was repudiated by the modernists and fell into obscurity, but his ideas are beginning to be revived. My cousin @PMArslanagic and I have distilled nineteenth century's finest work on urbanism into five principles:
- Create enclosed spaces
- Keep squares small
- Symmetry is overrated
- Move monuments to the edges of spaces
- Nestle monuments in vernacular fabric
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Thoughtful piece from @LifeSciVC (link in replies)
But Bruce’s causal story seems backwards to me: most *observable* AI-designed drug molecules are me-too’s precisely because that’s what VCs and big pharma prefer to fund!
It’s survivorship bias: the hypothetical full data set the funding stage by investors, most of whom are skittish about novel target risk.
But Bruce’s causal story seems backwards to me: most *observable* AI-designed drug molecules are me-too’s precisely because that’s what VCs and big pharma prefer to fund!
It’s survivorship bias: the hypothetical full data set the funding stage by investors, most of whom are skittish about novel target risk.
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Anyway, Bruce’s full piece is here—full of great insight as always: lifescivc.com/2026/10/the-fr…
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Lots of great stuff out there on this topic from @IFP, @RuxandraTeslo, @kroetscha, @cremieuxrecueil, @DerekLowe and @salonium
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Brian Finrow retweeted
Biotech companies will materially change their form and shape. Old structures are gone. But AI is a massive injection of new capital into drug dev and biotech. Start a biotech company - just a very different one from before. $XBI
Surprise 1: Anthropic acquired a one-person biotech
.
.
.
Surprise 2: that person is me
Surprise 3: I’m here to tell you all about it
Yes, this is what you think it is; after 6 yrs of increasingly loose anonymity: the Professor Oak reveal post
…and yes, it has gotten so boring around here that I’m literally doxxing myself to spice up the timeline
-------
Ok, allow me to introduce myself. My name is Cody Tranbarger. I mostly tweet, but occasionally find time to dabble in drug dev & starting/building biotechs. My past lives span the VC, crossover, startup continuum; Prof Oak has been my way of keeping a digital foot in those worlds, despite having my physical feet planted elsewhere.
The past 18 mo, ‘elsewhere’ was Mithril Medicine, a co. I founded to develop bsAbs for LAMA2-CMD & other ECM-related genetic diseases.
Mithril was born out of hands-on building with @MikeNGladstone, @JasonPaulRhodes, @LifeSciVC, & team @atlasventure. Somehow, I made enough half-decent calls along the way (even a broken clock is right twice a day, eh?) to convince them Mithril/I warranted a small seed. While I can hardly rationalize such an outrageously cavalier bet, I’m grateful for it, & I'd partner with Atlas again in a heartbeat.
In typical AV fashion, Mithril’s primordial form was virtual, decentralized, & ultra-lean. This stage tends to be short-lived, but for Mithril, it worked surprisingly well, for surprisingly long, thanks in part to the rapid maturation of the AI tools I used liberally.
Eventually, Mithril became a bit of an experiment itself - to find the upper bound of how far it could scale as a single operator + a bunch of Claude (+ a stellar bench of part-time consultants).
In parallel, I started spending time with @nc_frey, @an1lam, & @CoefficientBio team; and promptly experienced, for the 1st time, AI at the frontier. Soon thereafter, Mithril stopped looking like an experiment, & started looking like a preview of an entirely new operating model.
From that spark came “Pipeline-in-a-Person.” The idea immediately resonated when we shared it here back in April; and it was central to the shared vision that led to Anthropic’s acquisition of Mithril, & my joining the team.
Why join Anthropic? Three reasons.
(1) For Mithril, the programs continue, with more resources & infrastructure behind them, and as much Claude as I can put to work.
(2) For me, the chance to start several more programs, & find out how many one person can actually run in parallel - an almost unprecedented luxury for a curious drug hunter.
(3) For our mission, a path to institutionalize & scale this new way of working, then put it in the hands of all of biopharma, all over the world - which, candidly, I find the most energizing.
Will AI x Bio cure diseases? Unequivocally yes, imo… but not by the route that gets the most airtime. Rather than timeline acceleration & compression, I see orchestration & parallelization as today's low-hanging fruit.
Most drug hunters see a handful of go/no-go calls in a career, & spend entirely too much of the rest trading emails (my inbox can attest).
Give them the bandwidth to run several programs at once, and the time to focus on scientific judgment, and I’m willing to bet they’ll make better calls. And at scale, better calls translate to more drugs, higher hit rates, broader patient impact, & likely, a disease or 10 or 100 cured. I couldn't be more excited to build toward that future @AnthropicAI.
Finally, a heartfelt thank you to BioTwitter/X. The end of anonymity is bittersweet, but if anyone’s earned a proper introduction, you all have.
It’s difficult to overstate how much this app has done for me: a decade of education, plenty of friends, many job opportunities, several mentors, a few investors, even a co-founder (fmr). It was the generosity of this community that inspired me to start posting 6 years ago, after just as many years lurking. I hope I’ve been able to pay it forward, in my own small way.
But, to be clear, Prof Oak isn’t going anywhere. Same beat, same themes, and now, a front-row seat to drug development at the frontier. Stay tuned for dispatches from the trenches; and remember...
Gotta Cure 'Em All
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Brian Finrow retweeted
It just comes down to structural factors: wages, the number of people, the organization of the healthcare system, and SOC. Wages are low, despite essentially 0 difference in skill, hours are longer, SOC is bad+people are many → speeding enrollment.
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Brian Finrow retweeted
I have now lost the last bit of respect I had left for Terence Tao! This is one of the most ridiculous arguments I have ever heard. He also clearly has little understanding of biomedicine.
There are many drugs whose mechanisms of action we still don’t fully understand. In fact, even aspirin was used for decades before scientists established its principal mechanism of action! Currently used lithium drug still has no known mechanism of action!
If you were a cancer patient or seriously ill, would you really care whether scientists fully understood how a drug worked if it could save your life?
How can such brilliant people fall so deep into the abyss of coping? I suspect we will see much more of this as AI continues to challenge established intellectual hierarchies.
There are many drugs whose mechanisms of action we still don’t fully understand. In fact, even aspirin was used for decades before scientists established its principal mechanism of action! Currently used lithium drug still has no known mechanism of action!
If you were a cancer patient or seriously ill, would you really care whether scientists fully understood how a drug worked if it could save your life?
How can such brilliant people fall so deep into the abyss of coping? I suspect we will see much more of this as AI continues to challenge established intellectual hierarchies.
This is a slide from Terence Tao's 'Math 2.0' public lecture yesterday evening at Caltech. I am highly confident that, if the cure actually worked, almost any Stage 4 cancer patient would tell you that human comprehension of its mechanism is completely irrelevant to them.
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Brian Finrow retweeted
Assorted things I've been mulling over regarding agents in the economy:
• Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies.
• How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be.
• In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good!
• It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.)
• A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to).
• Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big.
• Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions.
Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
• Companies are in some sense the original superintelligence. It's often the case that they can use their amortized cognitive surplus to advance their interests against those of certain consumers: relative to the optimization capacity of companies, consumers can be inattentive, underinformed, irrational, etc. (Think, say, of some of the classic insurance upsells at the end of a booking process, which is typically priced substantially above what a regular policy would cost.) Herbert Simon introduced the idea of bounded rationality, and firms often end up benefiting from it. Thanks to personal agents, we will probably get somewhat more rational in how we engage with companies.
• How exactly will outcomes change? Well, certain kinds of price discrimination will work less well (how do coupons work if every agent hunts fastidiously for them?), and certain kinds of customer cross-subsidy will change (today, people who forget to cancel subscriptions subsidize those who don't). Taken across the economy as a whole, I'm not sure what the incidence of all of this will be.
• In corporate strategy, people have long debated the relative importance of distribution and product quality. Perhaps you've made something better, but does anyone know about it? Won't people just continue to buy the ACME Corp Mousetraps? Personal agents will, I think, act as a kind of structural subsidy for product quality. How would markets look different if individuals always spent at least 10 hours researching their purchases? On the margin, focusing on making a product better is, I think, going to become a more effective strategy for companies. This is good!
• It true, a corollary is that information about product quality will become more important and impactful. Today, most people have very limited ability to aggregate and integrate such data, but agents will have insatiable thirst for such signals. (It's often said that data is becoming more valuable because it helps in the training of models. That's obviously true, but I think there's a secondary way in which it's more valuable simply as a complement to cheaper intelligence.)
• A big question is whether agents will increase superstar effects (rational agents all settle on the same product) or increase dispersion (because everyone has slightly different tastes and preferences, which agents are good at eliciting, finally overcoming the artificial clustering we've been subjected to).
• Many internet companies have monetized demand routing, which is in turn often predicated on short attention spans. "I'll click on the first thing I see." This has led to some amount of inefficiency, as companies try to propitiate capricious ranking algorithms and incur various placement fees. It's not all deadweight loss (willingness to pay is itself a kind of signal, which is valuable to buyers), but it's not great. How will the nature and value of this routing change in a world of personal agents? I don't know the answer, but I think that the effects might be pretty big.
• Much of what I'm writing hinges on the assumption that personal agents will be on the consumer's side. I suspect that that will be the winning strategy, but whether it's true, and what it means to be true, involves a lot of other questions.
Taken as a whole, the market is a massively parallelized, decentralized, and highly imperfect value attribution machine, and, taking stock of all of the effects, it seems to me that the quality point may well be the biggest: that agents will change the nature of the backpropagation such that the rewards for better products increase. Maybe this is too optimistic, but I suspect (and hope) that companies that make things that they're proud of will feel that the universe is a little more partisan in their favor.
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Brian Finrow retweeted
A real contribution of AI is showing the critical weaknesses of humans and human structures.
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Brian Finrow retweeted
open-sourcing CTDs is extremely exciting. we have found clinical protocols available on clinicaltrials.gov to be extremely helpful at y-trap. this will be an OOM jump beyond that in utility, especially for lean teams without decades of regulatory experience.
CTD Commons will preserve and publish regulatory knowledge from failed drug development programs so future teams can learn from precedent that is usually locked away, to help uncover effective treatments for patients faster.
A CTD, or Common Technical Document, is a document that compiles the full journey of an investigational drug – everything from animal toxicology, manufacturing details, and, perhaps most usefully, correspondence with the FDA. Yet only a small fraction of that work appears in published papers.
CTD Commons will test the possibility of acquiring CTDs from failed or shelved drug programs, and make them openly available for research and analysis, for everyone to use.
@antonioregalado wrote about the project, and @RuxandraTeslo's essay on the topic, here: x.com/antonioregalad…
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Brian Finrow retweeted
CTD Commons will preserve and publish regulatory knowledge from failed drug development programs so future teams can learn from precedent that is usually locked away, to help uncover effective treatments for patients faster.
A CTD, or Common Technical Document, is a document that compiles the full journey of an investigational drug – everything from animal toxicology, manufacturing details, and, perhaps most usefully, correspondence with the FDA. Yet only a small fraction of that work appears in published papers.
CTD Commons will test the possibility of acquiring CTDs from failed or shelved drug programs, and make them openly available for research and analysis, for everyone to use.
@antonioregalado wrote about the project, and @RuxandraTeslo's essay on the topic, here: x.com/antonioregalad…
A CTD, or Common Technical Document, is a document that compiles the full journey of an investigational drug – everything from animal toxicology, manufacturing details, and, perhaps most usefully, correspondence with the FDA. Yet only a small fraction of that work appears in published papers.
CTD Commons will test the possibility of acquiring CTDs from failed or shelved drug programs, and make them openly available for research and analysis, for everyone to use.
@antonioregalado wrote about the project, and @RuxandraTeslo's essay on the topic, here: x.com/antonioregalad…
OpenAI Foundation owns 26% of OpenAI. Could be the richest nonprofit/charity in the world? This year, it's staffing up and started giving grants. We wrote about grants to ramp up biological data production. technologyreview.com/2026/09/15/114…
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