The more I work with powerful AI systems the more optimistic I become about the future of biology. As described in this great post from @citrini it will take time to see the impact of AI across the full complexity of human biology. My view is that drug design is where we are seeing and, in the near term, will continue to see the most visible impact. Drug design is to drug development what coding is to software development. It is the most verifiable step with only weeks or months needed to get results. Solving drug design is necessary but not sufficient and at minimum progress here will reduce the time it takes to bring drugs to patients. My more optimistic vision is that AI will enable us to create drugs beyond our current imagination.

It's why 23andMe never turned a profit. Customers rarely returned to their results, and the company never figured out how to use its massive trove of genetic data to develop drugs.

The reputational destruction of Prof. David Sabatini was one of the worst excesses of the Great Awokening / Me-Too era. @BillAckman acted bravely in offering him support when the entire academic establishment cancelled him. Without his efforts, the complete absence of due process in his treatment by @MIT might never have come to light. The question I am left with: Will those whose misconduct has finally been exposed pay anything like the price they imposed on Sabatini? Will they be fired? Will their reputations be destroyed? They deserve it. He did not.

The victim is more than Dr Sabatini: his family, his friends, his students, his peers, MIT, all universities (yes, all), and of course, science.

Boston lab space is 28.9% empty. The Bay Area is at 30.7%. Houston is at 26.3%. The XBI is up more than 20% this year. So why is no one moving back into these labs? Honestly, it shouldn't surprise anyone. Back in 2021 and 2022, the whole game was cramming as many researchers and benches into a building as you could. A few things changed that pretty fast. - AI-native biotechs lease about a third less space per person. - Pharma is licensing molecules and sending manufacturing overseas. When we ran a talk at MBC Biolabs, we heard that close to 80% of the companies there outsource some or all of their manufacturing to Chinese firms. - Later-stage companies want office, not lab. They're managing assets already in trials. The lab of 2026 just looks different. Teams are smaller. The science is AI-native. And a lot of the actual work isn't happening in Boston or SF anymore. It's happening in Shanghai and Suzhou. The R&D that does happen here is smaller, leaner, and set up to scale out somewhere else. Those teams don't need rows of benches. They need machines. If your building has 500 benches but not a single mass spec, liquid handler, or flow cytometer, nobody's going to want it. The equipment is the real bottleneck for early-stage work. The few groups that still want big footprints are building them around robots and power. @LilaSciences grabbed about 244,000 sq ft at Alewife Park in Cambridge for autonomous labs. @medra_ai put hundreds of robots into a concrete industrial building in SF. So here's the uncomfortable part. These buildings were built for a tenant that doesn't exist anymore. That tenant isn't coming back. Leaving the space empty and hoping 2021 returns isn't a plan. You have to rebuild it for who actually needs space now. - Deep tech and hard tech. I've been talking with groups here in SF, and a lot of robotics and hardware teams are looking for exactly this kind of space. Strong floors, real power, good ventilation. Retrofitting a lab is way faster than building new. - Incubators built around machines, not benches. Rip out the bench rows and put in the instruments early-stage companies can't afford on their own. MBC Biolabs is already doing this. Shared instruments, shared equipment, small teams that don't need 50,000 sq ft. Landlords who follow that blueprint will fill their buildings. The ones waiting on 2021 are going to keep sitting empty.

The vast majority of biopharma/biotech spent a decade plus dismissing AI as hype and nonsense and the thing is that they were demonstrably right on the seemingly dismissable nature of the AI, its immediate capabilities and its near term growth at basically every point along the curve... until it became undeniable that the entire economy was going to be dominated by AI and pharma was no exception. When you are in these seats of long standing success, power and prestige the danger is that you are right in your long standing views and supported by all the data as being right until you are just beginning to be wrong With the risk then you are behind those who committed and understood how the tide was changing earlier and bought in at the right time

If we want to unlock biological engineering we need to kill the manual lab bench. I've tried almost everything else over the last 20 years😛and PhDs still having to be in the lab is the rate limiter.

We built an 8000 sqft. high-throughput wet-lab in 30 days, to solve molecular discovery - starting with pesticides. Most teams in drug-discovery don’t receive target-organism verification until clinical trials. Pesticides allow us to rapidly validate our model in the target organism directly. With the help of our high-throughput lab, we were able to generate compounds that killed a $13 billion pest, the Fall Armyworm. We believe that the bitter lesson is coming for biology.

Biohub pay ranges (both NY-based) Research Scientist, AI: $214-375k Scientist I, Spatial Omics: $120-150k (or $93k for a postdoc) but sure, continue to promise investing heavily in new data modalities

Just like what’s the end goal here? Nothing left open in sf??

Announcing the Most Ambitious Set of Science Initiatives This Century whitehouse.gov/fact-sheets/2…