Inside Precision Medicine May 8, 2024
Researchers from the University of California (UC), San Diego, have developed a novel AI platform that can generate individual drug compounds capable of inhibiting multiple molecular targets at once. They used it to synthesize 32 new drug candidates for cancer.
The POLYGON platform, short for POLYpharmacology Generative Optimization Network, uses a deep machine learning model based on generative AI and reinforcement learning.
It works by embedding chemical space, in this case, target proteins, and repeatedly sampling them to generate new molecular structures to inhibit those proteins each time. The process simulates the time-consuming chemistry involved in the earliest phases of traditional drug discovery, substantially streamlining the process.
The output is optimized by reinforcement learning, a powerful machine learning strategy in...
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