Proximal Ventures raises debut fund to back startups bringing AI to drug development; plus, PSI is trying to make a business out of AI-driven scientific discovery

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0:50So you can focus on other important things, like savoring that last bit of pumpkin pie. From early startups to Fortune 500 companies, thousands are turning to Framer to build a website they'll love. Learn how you can get more out of your site from a Framer specialist or get started building for free today at framer.com slash tcstartups for 30 % off a Framer Pro annual plan. That's framer.com slash tcstartups for 30 % off. Rules and restrictions may apply. While established venture firms continue to attract capital, first-time fund managers are facing one of the toughest fundraising environments in years.

1:31But that did not stop Sahir Raouf, a former SignalFire investor and executive at two healthcare startups, from raising$27.5 million for his first solo VC fund. Raouf's firm Proximal Ventures is betting that AI can transform the tools, infrastructure, and services that support drug development. Pharmaceutical companies have historically outsourced various stages of drug development to specialized service providers, from synthesizing thousands of molecular compounds and figuring out how to manufacture drugs at scale to analyzing clinical trial data. Raouf told TechCrunch, for a long time, the assumption was that pharma is not a great buyer of software, but a really good buyer of services.

2:22Roof believes AI could automate much of that work, creating an opportunity for startups to capture billions of dollars in pharmaceutical industry spending. By using AI, these companies could deliver the same services at a lower cost and in significantly less time. Some of the most valuable applications of AI so far have been in service-oriented industries like law and finance. Now, Roof sees similar opportunities in pharmaceutical services. Proximo plans to invest in pre-seed and seed-stage startups, writing checks for a half a million up to one and a half million dollars. The firm has already backed seven startups, including Chronicle Bio, co-founded by former OpenAI executive Vigisimo, which uses AI to analyze biological and medical data to better understand chronic diseases and identify potential treatments.

3:19Before spending two years as a principal at SignalFire, Raouf led business development at clinical trial recruitment startup Iterative Health and previously oversaw partnerships at Flatiron Health, an oncology data company acquired by Roche, for$1.9 billion back in 2018. Roof said, if you're building a company that's selling into the life sciences, one of the hardest things to do is starting that initial commercial flywheel. His sales chops, deep understanding of the healthcare ecosystem, and extensive industry relationships gave limited partners, the investors in VC funds, the confidence that he could spot strong startups and help them land customers.

4:04Proximal's backers include VC firms SignalFire and Kleiner Perkins, Bertelsmann Healthcare Investments, and individual investors such as Dimension Capital co-founders Nan Lee and Zavane Dar. Anne Abernathy, co-founder of Highlander Health and former principal deputy commissioner of the FDA, is also an investor. She first met when they worked together at Flatiron Health, where she served as chief medical officer. She told TechCrunch that his ability to build relationships and spot industry bottlenecks made a lasting impression. Abernathy is convinced that his abilities, along with the understanding of what the healthcare market needs, will make him a successful investor.

4:48It is those qualities that have helped Proximal invest in startups alongside some of the better-known, much larger funds.

4:59David Tertarian, a recent MIT graduate and a member of the technical staff at the startup lab Physical Superintelligence, also known as PSI, used early access to Anthropik's Fable 5.2 model to solve an 18-year-old problem about quantum computing. The problem in question, the Aaron Aronson-Ambinus conjecture concerns the ability of quantum computers to solve problems faster than classical ones. Scott Aronson, one of the two researchers who posed the problem, wrote that he does not quite understand the proof, but that he believes it is correct because it was auto-formalized in Lean, a coding language for math, and explained by a team of top researchers with whom PSI shared the solution.

5:45The solution appears to close the door on one avenue quantum computers could follow to solve certain difficult problems at high speed, but not all of them. Terturian said, it's a negative result that allows people to know, okay, we're no longer looking there. More broadly, it reflects the upheaval in the scientific world caused by AI problem-solving. Aronson, who describes himself feeling satisfied, all-struck, disappointed, and fatigued by the news, wrote, a proof of full Aronson and Binus conjecture was one of the last remaining open problems in quantum query complexity that everyone seemed to agree was centrally important.

6:26I was surprised, honestly, to see it missing from OpenAI's Mathocalypse dump a few weeks ago. Surely they tried it. So was it really so much harder than all the problems that were solved? And that's a point in favor of PSI's model, which is to solve scientific problems with specialized model harnesses and scaffolding. PSI CEO Matt Pines told TechCrunch, an effect kind of research system should have lots of things related to harnesses, lots related to tools, memory systems, simulation infrastructure. You want to be able to really go after a problem at breadth and depth, and be able to consider a wide range of potential alternatives.

7:04For now, the company's revenue comes from using its tools to optimize data centers, simulating the variables of heat, power, water, and sound, where the performance of that site, as well as its impact on the community are a direct function of its physics. The long play, however, is converting theoretical physics breakthroughs into actual technologies. Pines said, six to nine months ago, when I was talking to investors, like I had to sort of stretch to validate that conditional, right? You know, like, no, no, no, trust me, pretty soon theoretical physics is going to be mostly the domain of machines.

7:40And it's not there yet, but it is on the way. Still, while AI has claimed important solutions in fields like mathematics and computer science, where it is possible to express them in validated code, doing so in less abstracted disciplines like the life sciences or physics has proven more difficult. Last week, the startup Discovered Materials released a million-dollar grand challenge for researchers using AI to understand problems like superconductivity and heat dissipation. Pines said, at the end of the day, physics is different than math because it's the real world. Nature gets a vote in your models of reality.

8:19Now, he said the startup is focused on understanding how to take computational results and validate them with experiments in the most efficient way possible. If it's a true fact of nature, well, that's a trick that you can exploit. You could build a device out of it, right? The AI suggests an idea. It allows you to do something in the world you weren't able to do before. and so each of those are kind of loops that PSI is building. As Neo Labs for Science become a pathway for potentially groundbreaking science, the participants are still figuring out what the standards are for this new world. Because PSI had to hold its result until Anthropik's model was nearly ready for release, they were able to share it with relevant researchers to better understand it.

9:07As an academic, we wanted to play our role in doing things the right way. So says Jim Halverson, a professor at Northeastern University who advises PSI. He'll be attending a summit at MIT next week, where leading physicists will try to hash out a response to the new pace of science. He said, best practices are still emerging. We figured that transparency is a good way to go, and contacting experts is a good way to go. We had some time to sit on it, and it was the first time that I actually took one of my AI-elicited solutions on print. And I read through it, and I was like, okay, how can I make this be presented more naturally for a human?

9:52Terturian, who said the academic community will expect him to be able to explain the result, told TechCrunch, I think it also made me realize, oh my god, the weight of what AI can do. That's all for now. For the latest in startup tech news, go to TechCrunch.com.

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