Co-Founder @ Xaira Therapeutics Former Baker Lab PostDoc at @UWproteindesign. Interested in generative modelling for molecular design. Views my own.

Joined September 2020
When we started @Xaira_Thera we were clear that for molecular AI to make a difference for patients, it had to be able to address the hardest and most clinically relevant problems; those that traditional methods haven't been able to solve. For that, we've been building X-Design, bringing together top-tier research, engineering and wet lab capabilities into a model focused on designing clinically progressible molecules. Today, we showcase just some of that work; designing functional, progressible antibodies for our "undruggable" XA-4 program de novo. bit.ly/4hAOhEW
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Joseph Watson retweeted
We’ve been quiet about protein design at @Xaira_Thera . Here’s what we’ve been building: Introducing X-Design, with results from two active drug programs that show what we think this field needs to deliver: speed to a useful lead, and access to targets that have resisted discovery. → 7 weeks from DNA synthesis to a preclinical lead on an oncology target, with the epitope and reagents already prepared. → A functional antibody antagonist against a challenging GPCR where conventional library screening AND llama immunization had failed. The bar we set for our model goes well beyond binding. The antibodies need to be human-like, functional, cross-reactive across species, and developable. Properties that have to come together in the same molecule for a program to move forward. That’s what makes these results exciting to me: designs tested in the lab, meeting the requirements of real programs in our pipeline. My bet is that the biggest impact of AI protein design will be expanding which diseases and targets we can pursue. We want to choose targets because the biology is compelling and to build the ability to make the right molecules. This is our first look at X-Design. Much more to come. See our blog: xaira.com/news/de-novo-desig…
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I’m excited to share our significantly-updated preprint on de novo antibody design, where we now demonstrate the structurally accurate design of scFvs (in addition to VHHs) with RFdiffusion! biorxiv.org/content/10.1101/…
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In particular, thank you to the other lead authors, @naterbennett0, @RobertRagotte, @AndrewJBorst, @dejsee, Connor Weidle, @wanderingriti and Yutong Yu! And thanks as always to David Baker for the leadership and for creating such a vibrant and exciting scientific environment!
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Finally, for the past year or so, some of us have been working to build the next generation of these tools at Xaira Therapeutics (@Xaira_Thera), with the aim of fully realising the promise of therapeutics design. If you’re interested in being a part of it, do get in touch!
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All the big things happening to all the best Davids! Congratulations David 😍
⚛️ I got a new job ⚛️ After 5 wonderful years at @UWproteindesign and @UWMolES, I’m headed to Palo Alto for a postdoc at @StanfordUChem under Todd Martinez. SUPER excited to dive into deep learning for quantum chemistry and explore the Bay Area!!
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Congratulations to all - incredibly deserved! It was a total and constant honour working with David. His passion for protein design and its applications, as well as his uncanny attention to detail continue to inspire me. And nothing we do today would be possible without AlphaFold
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.”
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Very exciting to see this work out! It still feels quite amazing that you can take three functional bits of protein and bring them all together with novel scaffolds, all while retaining their native function. Congratulations to @karla_mcastro for leading this super cool project!
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A great day for science! Congratulations to the teams at @GoogleDeepMind @IsomorphicLabs!!
Announcing AlphaFold 3: our state-of-the-art AI model for predicting the structure and interactions of all life’s molecules. 🧬 Here’s how we built it with @IsomorphicLabs and what it means for biology. 🧵 dpmd.ai/3URDiNo
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I am pleased to share that I have accepted a position @Stanford to start as an assistant professor in the department of statistics, with an affiliation in @StanfordData, this fall!
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I'm excited to announce that I'm part of the team at Xaira Therapeutics! This project has been some time in the making. I'm convinced that generative modelling, and ML for biology more generally, will play a pivotal role in the next generation of therapeutics. 1/2
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