Post by S ABDUL KARIM

🚀 The $2.6B drug discovery equation is being rewritten by AI. I just published a deep technical analysis of the de novo drug discovery landscape in 2026 — from generative diffusion models to clinical trial translation. Key insight: We're 12–18 months away from the first FDA approval of an AI-discovered drug. When rentosertib (or a peer) crosses that finish line, every pharma R&D strategy on the planet changes. The article covers: ✅ Technology comparison: Insilico vs. Schrödinger vs. Recursion vs. Isomorphic vs. Xaira ✅ The "bits to atoms" pipeline: how in silico molecules become in vivo therapies ✅ Clinical reality: what's working, what's failing, and why ✅ The future: autonomous labs, multimodal foundation models, and personalized drug design As someone building these systems at TCS Research Lab, I can tell you: the gap between computational possibility and clinical reality is closing faster than most realize. Full analysis: https://lnkd.in/edXRf5Wg What's the biggest bottleneck you see in AI drug discovery right now — biology, chemistry, regulation, or data? Sarang Puranik Navneet Bung Amit Saxena Sukesh Kalva Kapil Upadhyay #AIDrugDiscovery #PharmaInnovation #GenerativeAI #ComputationalBiology #BiotechTrends #DeepLearning #DrugDesign #FutureOfMedicine