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Bile colloids containing taurocholate and lecithin are essential for the solubilization of hydrophobic molecules including poorly water-soluble drugs such as Perphenazine. We detail the impact of Perphenazine concentrations on taurocholate/lecithin colloids using analytical ultracentrifugation, dynamic light scattering, small-angle neutron scattering, nuclear magnetic resonance spectroscopy, coarse-grained molecular dynamics simulations, and isothermal titration calorimetry. Perphenazine impacted colloidal molecular arrangement, structure, and binding thermodynamics in a concentration-dependent manner. At low concentration, Perphenazine was integrated into stable and large taurocholate/lecithin colloids and close to lecithin. Integration of Perphenazine into these colloids was exothermic. At higher Perphenazine concentration, the taurocholate/lecithin colloids had an approximately 5-fold reduction in apparent hydrodynamic size, heat release was less exothermic upon drug integration into the colloids, and Perphenazine interacted with both lecithin and taurocholate. In addition, Perphenazine induced a morphological transition from vesicles to wormlike micelles as indicated by neutron scattering. Despite these surprising colloidal dynamics, these natural colloids successfully ensured stable relative amounts of free Perphenazine throughout the entire drug concentration range tested here. Future studies are required to further detail these findings both on a molecular structural basis and in terms of in vivo relevance.

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.

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