"If goods don't cross borders, soldiers will." - Bastiat, 1850. We're seeing the decoupling of US and Chinese biotech in real time right now but many in the US have never been to China. I encourage you to come see things on the ground for yourself. I’m taking 30 CEOs, founders & investors to tour the biotech ecosystem, July 20-28. We have 5 spots remaining. DM me if you’d like to see the agenda.

China was the undeniable winner of JPM2026. During the conference itself, Chinese biotech firms closed the most deals, totaling approximately $𝟳.𝟯 𝗯𝗶𝗹𝗹𝗶𝗼𝗻—dwarfing the week's combined $𝟭.𝟱𝗕–$𝟮𝗕 in AI infrastructure bets. 🧵👇

We held a memorial for Craig Venter, who passed away last week. Barry Merriman, Craig's CTO, joined me on stage to read messages that attendees had written on a tribute wall in the expo hall. The messages people left were specific in the way that matters. One person wrote that Celera Genomics was the first investor in their company. Another said Craig was the reason they entered biology. Someone wrote that he inspired them to do their PhD in synthetic biology. My favorite was from someone named Nico: "Craig, you inspired me and gave me shit. I hope to dream as big as you and live life as fully." George Church sent a note too. He first met Craig in 1989 at one of the early genome meetings. Craig was central to progress and centrally to excitement in these fields. Barry shared three things he took from working with Craig directly. 1) Always think bigger. If you've thought of something, ask how you could think bigger. 2) One person can do great things. Craig proved that repeatedly in an era of committees and consortia. 3) ...And this is the one I think about most, Craig pioneered a whole new way of funding science. He went to the capital markets out of frustration with government grants and used the scale of industry to fund research at a level nobody else was doing. Human Genome Sciences became a $10 billion company. Celera became a $30 billion company. Neither had a business plan. They ran on Craig's vision. People misread him as someone chasing money, but Barry said that wasn't it. He figured out that if you harness global capital markets, you can do science at a scale that NIH grants will never touch. One last detail I love. At Human Longevity, Inc., they ran Craig's own genome as the calibration standard for their production sequencing pipeline. He's been sequenced over a thousand times. More than any person ever has been or ever will be. When the Science journal demanded they submit all 10,000 genomes from their first paper, Craig said that was $50 million worth of data and refused. He gave them the thousand sequencings of his own genome instead! Craig. Direct, bold, unrepeatable. #CraigVenter #SynBioBeta2026 #SyntheticBiology

I've always been drawn to solving science and engineering problems to benefit people. Throughout my career, it has been an honor to partner with the federal government in these pursuits. The ability to express reasonable disagreement with our government, without untoward retaliation, is part of the fabric of American society, and is part of what makes our technology development environment the best in the world. I'm hopeful that we can continue doing important work with our federal government partners, and I'm proud to be part of the Anthropic team.

DeepSeq.AI’s Andrew Chang said the company can quantify more than 10 billion antibody-antigen interactions and their affinities in a single experiment, arguing that dynamic protein-protein interaction data is the missing layer for drug discovery. #SynBioBeta #Biotech

@GoodFoodInst founder and president Bruce Friedrich said feeding 900 calories to a chicken yields about 100 calories back, framing animal agriculture as a deeply inefficient system that plant-based and cultivated meat aim to replace. #SynBioBeta #Biotech

Jason T. Gammack said @AnsaBio shipped 47 megabases of DNA, about 26,000 genes, with a 97.3% fulfillment rate as it expands clonal DNA up to 50 kb through @idtdna. #SynBioBeta #Biotech

Ola Wlodek said 80% of APIs used by the EU or U.S. come from just two countries, China and India. On this panel, @BioConstructiv, @antheiabio, and Aralez Bio laid out how biology could localize and simplify pharma manufacturing from starting materials to complex peptides. #SynBioBeta #Biotech

“Where does biology actually compute?” I had the privilege of unpacking this question today on a fantastic panel with 2 of the sharpest minds in the space: @iamjohnnyyu of @tahoe_ai & @glebkuz of @ManifoldBio, masterfully moderated by @FabioZB_I of Polyphron. 🧵

"What keeps me up at night is the fast pace of acceleration of open weight models in the ecosystem. They do not prioritize the same type of safety refusals." - Yunyun Wang, @OpenAI We just ran a biosecurity panel at @SynBioBeta today. Here's what you missed: AI is making it easier to design dangerous biology. The design-build-test cycle is compressing so fast the panel debated whether it's still a cycle at all. The screening tools mostly work. Kevin Flyangolts from @aclid said even heavily AI-redesigned sequences still conserve key functional residues, so current systems catch most of them... for now. But nobody wants to pay for screening. Jake Beal from @Raytheon said plainly that biosecurity is a pure cost center for every DNA provider. If you refuse to synthesize a flagged sequence, the customer goes to your competitor. Now, it's a race to the bottom. OpenAI deliberately downweighted biology training in their open weight models to reduce misuse risk. The problem is that the people building drug therapies and medical countermeasures need those same capabilities. The defenders lose too. Know-your-customer matters as much as computational screening. Scott Fay from @AnsaBio made this case. We've been talking about a passport system for legitimate users of risky sequences for years. Still doesn't exist. The Sequence Biosecurity Risk Consortium is trying to shift screening from "does this match a known pathogen" to "does this do something harmful to human cells." It's the right direction, but the speed needs to pick up. We love talking about what synthetic biology can build. We're less excited about what it takes to keep it safe. So who exactly is going to fund the defense side of this equation before something goes wrong? Something to think about. @DARPA @mkoeris #SynBioBeta2026 #SyntheticBiology #Biosecurity #Biotech

Not all our #SynBioBeta2026 attendees walk on 2 legs 🐶 Taco here found the "From Cells to Patients: Solving the Scale Mismatch in Virtual Biology" Main Stage Panel particularly interesting.

Anthropic Says Life Sciences Is Its Biggest Bet After Code. Eric Kauderer-Abrams started @AnthropicAI 's life sciences division ten months ago. He took on the stage at @SynBioBeta with Marc Tessier-Lavigne from @Xaira_Thera , and what caught my attention was how plainly Eric stated the following: "The greatest opportunity to have a beneficial, scaled impact with everything that's happening in frontier AI is in the life sciences." After coding, it's their biggest investment area. They've been training Claude on bioinformatics, chemistry, molecule design, structural biology, clinical regulatory. Their models went from mediocre in life sciences to roughly PhD level across most domains in under a year. That's a steep curve. But what I found more telling than the benchmarks was the infrastructure they're building around it. Wet labs for basic research so their own scientists hit the walls firsthand. An acquisition of Coefficient Bio (acquired by Anthropic) to teach @claudeai how to think like a biotech program manager, not just a bench scientist. The gap between "Claude can answer a biology question" and "Claude can help you run a drug program" is enormous, and they're clearly aware of it. Marc mentioned that 90% of drugs fail in the clinic. Two-thirds of those failures aren't bad science, but patient matching. You have a good target, a good drug, and you can't find who will respond. That's the problem both of them kept circling back to, and it's where causal AI models trained on real perturbation data might actually move the needle. Marc said nobody's pushing a button for a development candidate anytime soon. But Anthropic went from $1B to $30B in revenue in sixteen months. That kind of resource behind this kind of focus is new. It's fun to think of what R&D can look like in the next few months! #SynBioBeta2026 #SyntheticBiology #Biotech #AIxBio

Hamilton Company has been coming to @SynBioBeta for years. This year, they showed up with something new. Tyler Schweder from Hamilton's process analytics team walked Gary George through their full upstream workflow: pH, dissolved oxygen, viable cell density, total cell density, dissolved CO2... and the one everyone's been waiting for. Glucose for cell culture. Ten years in the making. That's not a feature launch. That's a milestone. Hamilton isn't just sensors. It's syringe pumps, benchtop robotics, and the big liquid handling platforms the industry already knows. Full workflow, one company. They crushed their lead goal on day one. Welcome to #SynBioBeta2026, Hamilton. 🔬

I opened SynBioBeta 2026 this morning in San Jose staring out at the biggest crowd we've ever assembled - and I couldn't stop thinking about a phone call I had last week with Sergiy Velychko, a postdoc in George Church's lab. While we talked about his work editing mouse embryos and human cells at Soxogen, I was literally watching a computer in the corner of my room edit its own code and self-improve in real time. Same decade. Two parallel tracks of self-improving systems - one silicon, one carbon. That's not metaphor. That's Tuesday! The biotech bear market ground people down for four years. Capital dried up. Companies folded. But the people in this room kept building anyway - kept experimenting, kept pushing. That matters more than any funding cycle. We also lost one of the architects of this field. Craig Venter stood on the SynBioBeta stage many times, and this week we honour him with a tribute in the expo hall. If you're at #SynBioBeta, please leave a note. We'll get it to his family. For a long time, it's felt like this cycle has had square wheels. Well, now I think it's finally starting to roll. Design, Build, Test, Learn. Every layer is accelerating. DNA synthesis costs are collapsing. Assembly tech is debuting on this stage today. Testing is scaling with hardware and automation. And AI scientists are transforming the Learn step from bottleneck into engine. #SynBioBeta2026 #SyntheticBiology #Biotech

In memory of the legend. R.I.P. Craig Venter (1946-2026)

“I am interested in deciphering human complexity in terms of wellness and disease. I guess you would describe me as a multi-disciplinary human biologist.” That is Dr. Lee Hood @ISBLeeHood in one quote. We're excited and honored to have Dr. Leroy Hood speaking at SynBioBeta 2026, May 4-7th in San Jose, California, you can learn more about the conference and get your tickets here: syntheticbiologysummit.com/?… For more than six decades, Lee Hood has built the tools that let biology see deeper. At Caltech, he and his collaborators developed the automated DNA sequencer, DNA synthesizer, peptide synthesizer, and gas-phase protein sequencer. Those tools helped make genomics, proteomics, and modern drug discovery possible. Now he is pointing to the next frontier: the dark proteome. This is the vast layer of proteins and proteoforms that conventional methods still cannot fully read. The genome gave us the parts list. The proteome tells us what biology is actually doing, in real time, across wellness, disease, aging, and therapeutic response. That is why protein sequencing matters so much. New platforms are beginning to close the gap. Pumpkinseed is using silicon nanophotonic chips and label-free Raman spectroscopy to read individual peptides. @DARPA PROSE program is pushing toward de novo protein sequencing at massive scale. And Hood is now making the case that comprehensive protein-level data could transform peptide drug discovery. His prediction is bold: peptide drugs could remake the pharmaceutical industry over the next decade. This is exactly the kind of conversation SynBioBeta was built for. You can read about protein sequencing online. But the real outcomes happen in person. Relationships are built in the room. Deals happen in the room. Breakthroughs happen in the room. I’m thrilled that Leroy Hood will be joining @jendionne , @susanklaeger , and @mkoeris on the Main Stage for a session on the dark proteome and the future of biology’s next great readout. Visit the SynBioBeta website to read the full article synbiobeta.com/read/leroy-ho…