Customized Amazon Nova models improve molecular-property prediction in drug discovery
Amazon Science
Amazon and Nimbus Therapeutics fine-tuned Amazon Nova LLMs to predict molecular properties in drug discovery, matching the accuracy of specialized graph neural networks. Fine-tuned Nova 2 Lite achieved 5% lower average error than baseline GNNs while matching or exceeding them on 7 of 11 molecular properties tested. The approach reduces operational complexity by replacing multiple separately-trained models with a single model that chemists can query conversationally for predictions and reasoning.
Why it matters
A single, optimized LLM unifies what previously required multiple models and can serve as a reasoning partner for medical chemists.
