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.