Srijit Seal 🇺🇸🇬🇧🇩🇪🇯🇵🇮🇳
Senior Chemøinformatician at Merck | Postdoc@Broad Institute of MIT and Harvard, Cambridge(MA) | PhD@University of Cambridge(UK) | AI, Image Analysis, bioML, -omics data, and Cell Painting for drug discovery. srijitseal.com/tools
- So, you want to replace animal models with AI? We spent the last two years collaboratively exploring AI for toxicology with 33 scientists from 14 leading pharmaceutical companies and 6 research institutes! 🏆 American Chemical Society Editor's Choice! pubs.acs.org/doi/10.1021/...
- It’s a strategic blueprint, introducing pillars for success in the real world, drawing from the expertise of scientists from pharma, including GSK, Novartis, Eli Lilly and Company, Merck, AstraZeneca, Bayer | Crop Science, Pfizer, Recursion, Novo Nordisk, Sanofi, Relay Therapeutics, and others.
- We spoke to government experts from the National Institute of Environmental Health Sciences (NIEHS) and thought leaders from academia, including the University of Cambridge, the Broad Institute of MIT, and Harvard. This unprecedented industry-wide effort outlines a unified framework for adopting AI.
- This initiative aligns with the FDA's recent announcement to phase out traditional animal testing in favor of more human-relevant methods. Our collective work provides a roadmap for integrating AI, ensuring safer and more efficient drug development processes.
- A model evaluated 234 toxic and 596 non-toxic compounds using structural fingerprints and achieved an F1 score of 0.440; what could be wrong? Of course, one answer is that it’s a great model. What’s another possibility?
- Today I learned that Hedwig actually died in Harry Potter? How did I even miss this? 😭😭
- Thank you for highlighting our work! Use DILIpred to figure out if your compounds have any DILI risk, with mechanistic features :D DILIPred was bulit with over 15k compounds and covers a large chemcial space!
- Drug-induced liver injury (DILI) is a significant concern in drug discovery, in particular because it might only be observed late in large clinical studies. Dilipred is an interesting in-silico tool using variety of approaches to identify potential for hepatotoxicity. macinchem.org/2025/03/02/u...
- Excited to join Merck US as a Senior Research Scientist! If you are in Philly area, would be happy to catchup!
- pip install infoalign! Add biological information to your chemcial fingerprints, using only SMILES as input! I'm thrilled to share that our paper "Learning Molecular Representation in a Cell" has been accepted to ICLR 2025! 🎉
- In this work, Gang Liu introduces InfoAlign, a new approach for learning molecular representations from cellular response data, integrating features like cell morphology and gene expression.
- By combining information bottleneck methods with context graphs, we’re able to extract minimal yet sufficient representations of molecules that lead to better predictions and generalization in downstream tasks like molecular property prediction and zero-shot molecule-morphology matching.
- Many thanks to all authors — John Arevalo, Zhenwen Liang, Anne Carpenter, Meng Jiang, and Shantanu Singh! We look forward to continuing to advance the field of molecular representation learning with. -omics datasets! Find out more! github.com/liugangcode/...
- I did the experiment myself! Having an Android phone saves you 25% costs and the phone pays for itself in 10 Uber rides! Uber and other apps cost up to 30% more on iPhones than on Androids for the same orders. Don’t get me wrong, by all means buy an iPhone! Keep an Android on the side for orders 🤪
- An Android phone offers you more discounts than any subscription model 😂
- It’s not that large is it… hmm
- Postdoctoral Opportunity!
- 🎉 I'm starting my own lab at EMBL-EBI (Cambridge, UK; June 2025) 🎉 We will focus on identifying and characterizing chemical hazards to humans and ecosystems using computational biology methods. I am beginning the search for two postdocs now - stay tuned for more details! ewaldlab.org
- Thinking about implementing the Cell Painting assay? Here’s a guide to how it can help in Drug Discovery! t.co/hW1jOhAg7q
- 212e, I won’t miss you! Not at all!
- When the size of test data is 5 compounds and accuracy is 100% 😌
- We’re thrilled to share our Nature Methods review on #CellPainting — your go-to resource for mastering Cell Painting! From MOA and toxicity prediction to contributing to candidate drugs in clinical trials, we’ve distilled 10 years of insights!
- What is Cell Painting? It's a microscopy-based, high-content assay that uses six fluorescent dyes to "paint" cells, capturing thousands of features like size, shape, texture, and intensity. The goal? Reveal cellular responses to perturbations in a target-agnostic way.
- Why it matters: Cell Painting unlocks phenotypic profiling, helping researchers understand drug mechanisms of action (MoA), predict toxicity, and even design safer, more effective compounds. It's cost-effective, scalable, and widely accessible.
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- The JUMP-Cell Painting findings with genetic perturbations are now released!
- Now on biorxiv! The JUMP-Cell Painting Consortium’s paper: “Morphological map of under- and over-expression of genes in human cells” This is the genetic perturbation portion of the JUMP’s dataset; our chemical perturbation paper will come in a few months www.biorxiv.org/content/10.1...
- Join the Cheminformatics, Machine Learning in Chemistry and Drug Discovery Starter Pack!at://did:plc:jbu62p2segkzvnuk3e4h5ga7/app.bsky.graph.starterpack/3lb4lirxegh2d
- Will save more time that asking ChatGPT!
- This is pretty dope. Add pylustrator.start() at the top of a script and your plots are interactively scalable, composable, movable, etc with your mouse www.youtube.com/watch?v=xXPI... pylustrator.readthedocs.io/en/latest/ h/t @tommytang.bsky.social
- Do you want to make biological sense of Cell Painting images? Try BioMorph! BioMorph maps CellProfiler features to a new feature space that’s more interpretable and contains the same signal strength. Try it at broad.io/BioMorph !
