Alex Zhavoronkov

Johns Hopkins University, Abu Dhabi University

Papers

2

Total Citations

611

H-Index

2

About

Alex Zhavoronkov is a pioneering figure at the intersection of artificial intelligence and longevity science. His research focuses on applying deep learning to drug discovery, drug repurposing, and the biology of aging—particularly through the lens of cellular senescence. In his highly cited 2016 paper (600+ citations), Zhavoronkov demonstrated how deep neural networks trained on large transcriptomic datasets can predict pharmacological properties of drugs, opening new avenues for repurposing existing compounds. More recently, his 2024 work introduced an AI-driven robotics laboratory that identified TNIK inhibition as a potent senomorphic agent—a breakthrough in targeting the hallmarks of aging. This study highlights his commitment to developing dual-purpose therapeutics that simultaneously address aging and disease. As the founder of Insilico Medicine, Zhavoronkov has been instrumental in advancing AI-powered drug discovery, with multiple pipeline candidates entering clinical trials. His work bridges computational biology, geroscience, and translational medicine, earning him recognition as a visionary in the longevity biotech space.

Research Focus

Key Achievements

2
H-Index
2
Papers
611
Total Citations
306
Avg Citations/Paper
🏆 Most Cited Paper
Deep Learning Applications for Predicting Pharmacological Properties of Drugs and Drug Repurposing Using Transcriptomic Data
600 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Johns Hopkins University, Abu Dhabi University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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