POxload: Machine Learning Estimates Drug Loadings of Polymeric Micelles.

ABSTRACT: Block copolymers, composed of poly(2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they form micelles that carry poorly water-soluble drugs. Many recent studies have investigated the effects of structural changes of the polymer and the hydrophobic cargo on drug loading. 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 (balanced accuracies of 0.8). Subseque

SUBMITTER: Kehrein J 

PROVIDER: S-EPMC11394009 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature