Uploaded September 2026 | Updated September 2026, 1 week ago
🚀 Insilico Medicine announces 5 new frontier chemistry and biology Specialist Language Models trained through MMAI Gym for Science.
📊 The models deliver SOTA-level performance across 70+ benchmark tasks spanning drug safety, potency prediction, chemical synthesis, and biology.
🧠 How MMAI Gym works: compact language models are trained across related scientific tasks and evaluated directly against established computational methods using the same datasets and train/test splits.
🧪 Chemistry specialists:
🔹 ADMET: 28 tasks, with SOTA performance across 7 tasks, including drug-drug interaction risk, cytotoxicity, and pharmacokinetic properties.
🔹 GPCR activity: 44 receptors, with SOTA performance across 11.
🔹 Kinase activity: 67 enzymes, with SOTA performance across 30.
🔹 Single-step retrosynthesis: built on a 2.6B-parameter architecture, with strong results on both standard and out-of-distribution benchmarks.
🔬 MMAI Gym also supports specialist models for clinical, omics, and molecular biology tasks. On selected benchmarks, these models outperform substantially larger general-purpose frontier models.
🎯 The focus is straightforward: build specialized models that perform well on real drug discovery tasks and compare them rigorously against established methods.
📚 This work builds on research presented at NeurIPS 2025, ICLR 2026, and ICML 2026.
🧬 Another step forward for specialist models in drug discovery.
#insilicoSOTAFM #InsilicoMedicine #MMAIGym #DDDBenchmark
🚀 Insilico Medicine announces 5 new frontier chemistry and biology Specialist Language Models trained through MMAI Gym for Science.
📊 The models deliver SOTA-level performance across 70+ benchmark tasks spanning drug safety, potency prediction, chemical synthesis, and biology.
🧠 How MMAI Gym works: compact language models are trained across related scientific tasks and evaluated directly against established computational methods using the same datasets and train/test splits.
🧪 Chemistry specialists:
🔹 ADMET: 28 tasks, with SOTA performance across 7 tasks, including drug-drug interaction risk, cytotoxicity, and pharmacokinetic properties.
🔹 GPCR activity: 44 receptors, with SOTA performance across 11.
🔹 Kinase activity: 67 enzymes, with SOTA performance across 30.
🔹 Single-step retrosynthesis: built on a 2.6B-parameter architecture, with strong results on both standard and out-of-distribution benchmarks.
🔬 MMAI Gym also supports specialist models for clinical, omics, and molecular biology tasks. On selected benchmarks, these models outperform substantially larger general-purpose frontier models.
🎯 The focus is straightforward: build specialized models that perform well on real drug discovery tasks and compare them rigorously against established methods.
📚 This work builds on research presented at NeurIPS 2025, ICLR 2026, and ICML 2026.
🧬 Another step forward for specialist models in drug discovery.
#insilicoSOTAFM #InsilicoMedicine #MMAIGym #DDDBenchmark
