首页|University of Helsinki Reports Findings in Machine Learning (POxload: Machine Le arning Estimates Drug Loadings of Polymeric Micelles)
University of Helsinki Reports Findings in Machine Learning (POxload: Machine Le arning Estimates Drug Loadings of Polymeric Micelles)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating in Helsinki, Finl and, by NewsRx journalists, research stated, “Block copolymers, composed of poly (2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they fo rm micelles that carry poorly water-soluble drugs. Many recent studies have inve stigated the effects of structural changes of the polymer and the hydrophobic ca rgo on drug loading.” The news reporters obtained a quote from the research from the University of Hel sinki, “In this work, we combine these data to establish an extended formulation database. Different molecular properties and fingerprints are tested for their applicability to serve as formulation-specific mixture descriptors. A variety of classification and regression models are built for different descriptor subsets and thresholds of loading efficiency and loading capacity, with the best models achieving overall good statistics for both cross- and external validation (bala nced accuracies of 0.8). Subsequently, important features are dissected for inte rpretation, and the DrugBank is screened for potential therapeutic use cases whe re these polymers could be used to develop novel formulations of hydrophobic dru gs.”
HelsinkiFinlandEuropeCyborgsDrug s and TherapiesEmerging TechnologiesMachine Learning
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