Incremental training allows language models to optimize drug candidates for potency without external scoring functions. Researchers used this approach to refine molecular structures directly within the model's latent space. This method reduces reliance on traditional medicinal chemistry heuristics. Practitioners can now accelerate lead optimization by treating chemical structures as evolving sequences.