Five pharma firms federated-finetune OpenFold3 on 20,000+ private structures, lifting ligand-pose accuracy from 29% to 47%
AllThingsApx · x · 2026-09-14
Five pharmaceutical companies fine-tuned OpenFold3 in a federated setting across 20,000+ private structures, with no data leaving their local environments, raising correct ligand-pose predictions from 29% to 47%.
It's a landmark use of federated learning in drug discovery: companies improve a shared protein-ligand co-folding model without exposing sensitive proprietary data.
More from Research
- Google DeepMind releases ForTy, a 10m global forest-type map with ~95% natural-forest accuracy — anselm · 2026-10-31
- Tversky branch inside RNN cells: half the depth matches full xLSTM with 2x faster training — stanfordnlp · 2026-10-31
- AI pushes circuit lower bound from 3.1n to 3.5n as UCLA-backed challenge aims at P vs NP — soumitrashukla9 · 2026-10-31
- Qwenputer: a full RISC-V CPU inside Qwen3.5-4B weights, running C in forward passes — armand_ruiz · 2026-10-31
- What is work for? Cross-national survey of 8,234 adults on meaning in the AI age — soumitrashukla9 · 2026-10-31
- Paper: benchmark difficulty coverage is skewed, leaderboard conclusions need caution — Miserable-Dare5090 · 2026-10-31