Pat Dwyer, Co Founder | Miami | Naples | SFO

JUST IN: Experimental peptide retatrutide completely eliminates sleep apnea in up to 25% of patients in clinical trials.

New in Claude for Legal: a gallery of ready-made artifacts for contract review, regulatory horizon scans, cite checks, and more. Start from the built-in example, add your own documents and connectors, and share it with anyone across the business.

The lesson from Lula winning (after Bolsonaro was priced ~82%) is that prediction markets are just a function of polls—which are increasingly unreliable. There’s no signal from betting odds… just more opportunity to speculate. Expect a lot of “surprises” during midterms.

What is AI really capable of in bio? To separate hype from reality, we spent 3 months working firsthand with @AnthropicAI's internal research model to see if it could create an experimental scorpion antivenom. Introducing Citrini Therapeutics. citriniresearch.com/p/citrin…

There’s a really pronounced divide between people who are on the AI side of things and people who are on the biology side of things. Even among people working in AI, the divide persists based on where they’re focused. The AI side, adherents of scaling laws and the bitter lesson, believe that AI getting better means AI being more capable of novel discoveries in medicine (that go beyond discovering new drugs in well understood targets or speeding up dry lab work etc). The biology people think the idea of a bitter lesson in biology is kind of ridiculous and that regardless of AI’s capabilities it’s going to be at least 5-10 years until you could hope to reliably simulate human toxicology in silico (right now AI/ML can’t even reliably simulate in vivo studies like binding affinities or functional assays). Even the most AI pilled of them, who will list all the areas that AI can reduce the time spent on various areas, don’t think the concept of AI discovering novel targets or generating new understanding of causal biology is realistic in the near term. Most, in fact, will readily characterize the assumption that even an “ASI” level model could find cures hidden in our current understanding (without expanding that understanding with significantly more biological data) as patently false. This was a big part of why we wanted to experience it ourselves by using AI for a (very) small portion of what it can do in biology. It was both mind blowing and revealed some poignant insights into how different the problem of making AI better at something like coding is to the problems of biology. Even if it unlocked the ability to generate new molecules at a stunning pace, its simulation (in silico) of binding only had 49% accuracy. And if we wanted to improve that, we’d need to feed it back the data from the lab - data that took about 30x as long to get as it took to generate the molecules. And these were tests in a test tube (turn of phrase), imagine how long it would take if we wanted to improve the model with data that required recruiting humans and monitoring their reactions. Human biology is very complex, and adding a drug - especially a novel drug and doubly so for a novel drug acting on a novel mechanism - means mapping interactions that have nth-order-effects that we don’t have the data to predict. Virtual cells have made advancements enabled by AI, but the perturbations equate to a small fraction of the possible. This is before you even get into curing disease, especially uniquely human diseases. Brain function involves cellular identities that are unique to humans, meaning animal studies are of little use. How long does it take to understand what the side effects of chronic administration of a drug in humans are? AI can speed up analyzing the data, or designing the trial or even getting it approved…but it can’t make a 6 month trial complete in 3 months. I think its important to point out that significant advancements can be made in AI that contribute to biology, while also being realistic about how much it speeds up something as complex as curing a specific cancer or diseases of the brain.

First non r*tarded explanation of this I’ve seen on X

We are developing a drug that opens up the capillaries and fills the body’s tissues with a compound that - according to our partner military labs - destroys all known pathogenic bacteria, all known pathogenic fungi, biofilms, influenza virus as well as viruses of the herpes family. These are facts. The FDA recently designed this product a Qualified Infectious Disease Product (QIDP) for all cause pneumonia, giving us FDA Fast Track, and Priority Review. Good news for the day. ❤️‍🩹🫡

Underrated life advice: Keep your personal burn rate low. Cheaper car. Smaller house than the bank says you can afford. No payment you'd panic about if work got weird. Low expenses aren't about being cheap. Low expenses give you options. And options = freedom.