Predicting Bile and Lipid Interaction for Drug Substances.

Jonas Schlauersbach, Josef Kehrein, Simon Hanio, Bruno Galli, Cornelius Harlacher, Christopher Heidenreich, Bettina Lenz, Christoph Sotriffer, Lorenz Meinel

Molecular pharmaceutics 2022 Aug 01

filter terms:

Predicting biopharmaceutical characteristics and food effects for drug substances may substantially leverage rational formulation outcomes. We established a bile and lipid interaction prediction model for new drug substances and further explored the model for the prediction of bile-related food effects. One hundred and forty-one drugs were categorized as bile and/or lipid interacting and noninteracting drugs using 1H nuclear magnetic resonance (NMR) spectroscopy. Quantitative structure-property relationship modeling with molecular descriptors was applied to predict a drug's interaction with bile and/or lipids. Bile interaction, for example, was indicated by two descriptors characterizing polarity and lipophilicity with a high balanced accuracy of 0.8. Furthermore, the predicted bile interaction correlated with a positive food effect. Reliable prediction of drug substance interaction with lipids required four molecular descriptors with a balanced accuracy of 0.7. These described a drug's shape, lipophilicity, aromaticity, and hydrogen bond acceptor capability. In conclusion, reliable models might be found through drug libraries characterized for bile interaction by NMR. Furthermore, there is potential for predicting bile-related positive food effects.

Citation

Jonas Schlauersbach, Josef Kehrein, Simon Hanio, Bruno Galli, Cornelius Harlacher, Christopher Heidenreich, Bettina Lenz, Christoph Sotriffer, Lorenz Meinel. Predicting Bile and Lipid Interaction for Drug Substances. Molecular pharmaceutics. 2022 Aug 01;19(8):2868-2876