delafuentelab.bsky.social
Presidential Associate Professor @upenn.bsky.social - using AI to reimagine antibiotic discovery and peptide design. Previously @MIT, @UBC
🔗 https://delafuentelab.seas.upenn.edu
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(4/4)It was illuminating to think through these challenges with Henry Skinner of the @amractionfund.bsky.social and Dr. Christina Yen in a new paper for @bulletinatomic.bsky.social. As we note, to fully reap the benefits of AI, antibiotic policies and market dynamics must evolve alongside AI.
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(3/4) But the market for antibiotics is broken and private investment is sorely lacking, making it exceedingly difficult to advance even the most-promising candidates through clinical development and to patients.
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(2/4) AI allow us to probe DNA and proteins from both extinct and living organisms for new and optimal antibiotics far more efficiently than any human-led research team ever could.
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Thank you!
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(5/5)And a brilliant team: Angela Cesaro, Fangping Wan, Haoyuan Shi, Kaiyang Wang, C. Mark Maupin, Matt L. Barker, Jiqian Liu, Stephen J. Fox, @jingjieyeo.bsky.social .
Link to paper: www.cell.com/cell-reports...
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(4/5) This work is a testament to what’s possible when deep learning and experiment move in lock-step. Thanks to the collaboration between #ProcterGamble, @cornelluniversity.bsky.social
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(3/5)EV71, the main cause of hand-foot-mouth disease, can lead to severe neurological complications and still lacks an approved therapy. By binding conserved viral pockets, these compounds suggest routes to both potent inhibition and reduced escape.
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(2/5)With only 36 training molecules, our model proposed 8 inhibitors against enterovirus 71. Bench assays confirmed 5, which is ~10× the hit-rate of classical screens, compressing months of iteration into days.
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(2/2) I’m incredibly grateful to my brilliant team, collaborators, and family; your support makes every breakthrough possible. Onward! #YGL25 #WEF25
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Wow! Beautiful!
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The Symposium will explore recent advancements in generative AI models for molecule discovery, with a focus on applications in health and drug development. Topics include AI-driven design of small molecules, peptides, and proteins, drug repurposing, and AI-based modelling of DNA and RNA sequences.
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Thanks so much!
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(2/2) Today, thanks to AI, we can explore and discover new antibiotics at digital speed, carrying on Fleming’s incredible legacy. I am truly grateful for my amazing team and collaborators who make this work possible!
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Thanks!
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Thanks!