Researchers from The Ohio State University and the Indian Institute of Technology Madras have developed an artificial intelligence framework to rapidly generate drug-like molecules that are easier to synthesize in real-world laboratory settings. The new system, called PURE (Policy-guided Unbiased REpresentations for Structure-Constrained Molecular Generation), promises to significantly cut down the early-stage timelines of drug development—currently a billion-dollar, decade-long process—and could play a crucial role in addressing drug resistance in cancer and infectious diseases. It stands apart from existing molecule-generation AI tools that rely on rigid scoring mechanisms or statistical optimization.
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