3/ We only have 8 presentation slots and sign-ups close on November 3rd.

Make sure to RSVP below 👇

RSVP here: luma.com/n47bshdx

2/ We want to connect the people reimagining how drug discovery happens, to share ideas, spark collaborations, and explore ways to build together.

If you want to present a “Show & Tell”, we review submissions on a rolling, first-come, first-served basis.

5/ If you’re attending ICML, make sure to connect with @jhartford.bsky.social and Ihab to learn more about the research happening at Valence Labs and @recursionpharma.bsky.social.

4/ “Towards Scientific Discovery with Dictionary Learning: Extracting Biological Concepts from Microscopy Foundation Models”

Link: arxiv.org/abs/2412.16247

3/ “A Cross Modal Knowledge Distillation & Data Augmentation Recipe for Improving Transcriptomics Representations through Morphological Features”

Link: arxiv.org/abs/2505.21317

2/ ”ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy”

Link: openreview.net/forum?id=niy...

3/ By combining SynFlowNet with Boltz-2, this new release aims to accelerate the design of high-affinity binders for more efficient early-stage drug discovery.

Check out the GitHub repository here: github.com/recursionpha...

Learn more about Boltz-2 here: www.rxrx.ai/boltz-2

2/ Originally introduced by Valence Labs, Recursion’s AI research engine, SynFlowNet helps ensure generative models propose molecules that are not only novel but also synthetically feasible.

Check out some of the early media coverage here: www.forbes.com/sites/alexkn...

3/ MoML is an excellent opportunity to engage with leading minds, explore cutting-edge research, and connect with the community in TechBio.

We encourage everyone to secure their spot before it’s too late!

Register now to be part of MoML 2025: portal.ml4dd.com/events/molec...

2/ Our list of speakers include:
— Aaron Newman (@stanford.edu)
— Smita Krishnaswamy (@yale.edu)
— Gabriele Corso (@mit.edu)
— Kirill Neklyudov (@mila-quebec.bsky.social)
— Emmanuel Noutahi (@valenceai.bsky.social | @recursionpharma.bsky.social)
— Michael LeVine (Genesis Therapeutics)

6/ Learn more

Try the app: txpert.valencelabs.com
Read the blog: www.valencelabs.com/txpert-predi...
Read the paper: arxiv.org/abs/2505.14919
Access the code: github.com/valence-labs...

5/ TxPert addresses the "Predict" capability of our virtual cell framework

This represents an initial, but important, step in a much larger journey: building models that can predict, explain, and eventually discover new therapeutic opportunities

www.valencelabs.com/advancing-dr...

4/ We’re also releasing the TxPert App, a tool that makes the model accessible to researchers

- Select a cell type and gene to perturb
- Visualize the gene interaction networks
- Analyze predicted expression changes

Explore more: txpert.valencelabs.com

3/ TxPert achieves state-of-the-art performance by integrating multiple biological knowledge networks

These include curated public resources like STRINGdb and GO, alongside @recursionpharma.bsky.social proprietary PxMap and TxMap graphs derived from large-scale perturbation screens

2/ Observing how cells respond to perturbations is key to understanding disease and designing more effective therapies

But doing this experimentally across an intractable combination of genes, cell types, and conditions is slow, expensive, and infeasible