The platform, called MAESTRO and described in Advanced Science, uses large language models, or LLMs, to analyze scientific knowledge about how drugs work and the biological pathways cancer cells use to survive treatment. The system evaluates potential drug combinations, ranks the most promising candidates and generates biological explanations that researchers can test in the laboratory.
To identify drugs that could help overcome treatment resistance in prostate cancer, the researchers used MAESTRO, short for Mechanistic Augmentation and Ensemble Selection for Therapeutic Ranking Optimization, to evaluate thousands of natural products.