Many drugs fail therapeutic development because of poor aqueous solubility. Polymeric micelle formulations were shown to alleviate this problem for some but not all such drugs. We conceived a novel computer-aided strategy for rational design of formulations for poorly soluble drugs. Novel descriptors of drug-polymer complexes were developed and employed to build models predicting drug loading efficiency (LE) and loading capacity (LE). Using these models for virtual screening of drug libraries, we selected eight drugs (four positive and four negative hits). Three positive and three negative hits were confirmed experimentally (75% prediction accuracy). Ironically, the negative hit in this context also had the desired micelle solubility. Podophyllotoxin and simvastatin, with LE of 95 and 87 and LC of 43 and 41, respectively, were among the top five compounds ever studied by us. The success of the strategy described herein suggests its broad utility for designing other drug delivery systems.

Cheminformatics-driven discovery of polymeric micelle formulations of poorly soluble drugs

255th National Meeting (2018)

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