Co-Founding Partner @ Lauxera. EU-first healthtech growth (devices, tools, Dx, pharma services, digital health). Minority + majority. SF-based

Mill Valley, CA
Joined June 2011
Two IPF trials this week, one hit and one miss. Takeaway: Biomarker tools and CROs matter! BMS's ALOFT-IPF used SomaLogic proteomics and Brainomix imaging to show the drug was hitting fibrosis and to track progression more sensitively. Syndax YOLO'd straight into Ph2 without proving any impact on disease biology.
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Notes from the field on biotechs selling their data to the labs: ➡️ CRO's have never been able to own any rights to the studies they perform, so the data do indeed sit with the biotechs (and pharmas) ➡️ This idea is no secret. Mercor, micro1, etc are getting involved, but a wide range of HC companies are dabbling here too (even those with core businesses in completely different areas) ➡️ Taste and depth matter. A biodistribution study in AAV obviously doesn't look like a mAb! Could this leave room for specialist RL environment platforms?
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Amazing work from Stanford's @james_y_zou and co developing an AI CSO stack! Now using this tool to accelerate our PET tracer pipeline at @AntarosMedical!
Super excited that #VirtualBiotech is published in @ScienceMagazine today! Tens of thousands of AI scientist agents work together across drug discovery + development, from target discovery to clinical trial design. Our blueprint for agentic R&D 🧵
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HHS and FDA are moving fast to reform clinical trials! Just 3mths from the launch of Operation Trailblazer to pilot. Q427 we could have broad expansion of QRI's to get us ~inline with Australia!
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If internal Pharma data is the *really* good stuff (see below) then they will own the frontier in #AIxBio #Mercor doesn’t sell Cryo-EM data last I checked :). And no one has huge reams of long-cycle animal data except large biopharma In this Nature paper, adding 10% more data from Pharma to an open training set improved relative model performance by 50%! Kudos to @MoAlQuraishi ! Link: nature.com/articles/d41586-0…
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This is spot on! There will be strong pressure for clinical trial reform à la Australia, but also in what passes for pre-IND safety…
In two or three years there will be 10x the number of INDs and the same number of people you can recruit into a clinical trial. I don't understand what people think is going to happen. Everyone is funding molecular design but folks, we've got to also be funding new validation methodologies in a big big way.
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Alex Slack | Lauxera retweeted
I’m calling it now: Big AI will start buying Big Pharma. Not for the drugs. For the data.
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I would buy reams of failed preclinical experiments and full clinical datasets from living and dead biotechs. The frontier AIxBio labs will push the boundary on early discovery, but the rest of the drug development continuum needs more available training data!
🚨 Anthropic is building an acquisition pipeline in AI × biology. A newly posted Corporate Development Lead, Life Sciences role will source and execute acquisitions, investments, and strategic partnerships across: drug discovery, clinical development, regulatory & medical writing, lab automation, and healthcare data infrastructure. The mandate explicitly includes acquihires, tuck-in acquisitions, minority investments, and evaluating build / partner / buy decisions. This looks less like ordinary BD — and more like Anthropic systematically mapping what it may want to buy in life sciences. job-boards.greenhouse.io/ant…
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Lab automation space: 3–4 years watching, no investment yet! Adaptyv’s (@adaptyvbio) $40M raise this week follows those of Medra and Automata (@mostafa_eSayed) + Ginkgo’s (@jrkelly) full pivot. These players sit downstream of AI drug discovery pureplays Isomorphic, Lila, Recursion (etc) and rapidly increasing use of AI in all biopharma. HT demand + newly automated workflows = bigger SAM.
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We are looking for co's which can grow profitably while building AI-relevant datasets to improve moat. So far, we've seen the most revenue traction and margin sustainability at: (1) true cloud labs with differentiated offerings and TAT (2) irreplaceable components / automation-friendly analyzers
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