Researchers at Duke University have developed a new machine learning-powered system to speed up the design of drug-delivering nanoparticles in the human body, according to their recent paper.
These infinitesimal particles can more directly target ailments, though their size makes creating therapies incredibly difficult. Researchers used a chemical-mixing lab robot and machine learning to test formulas, and their proprietary AI accurately predicted which combinations would succeed, outperforming existing deep neural networks.
They used this approach to improve two cancer drugs — making one with 75% fewer active ingredients, and boosting the efficacy of another against leukemia cells. The system could help create new treatments and make existing ones easier to produce.