Saturn: Sample-efficient Generative Molecular Design using Memory Manipulation

Understand

Generative molecular design for drug discovery has very recently achieved a wave of experimental validation, with language-based backbones being the most common architectures employed.

• The most important factor for downstream success is whether an in silico oracle is well correlated with the desired end-point.
• To this end, current methods use cheaper proxy oracles with higher throughput before evaluating the most promising subset with high-fidelity oracles.
• The ability to directly optimize high-fidelity oracles would greatly enhance generative design and be expected to improve hit rates.