The qualitative relationship between in vitro Caco-2 cellular transport and in vivo drug permeability allow using
Caco-2 cell assay for intestinal absorption studies. In this work, atom-based bilinear indices and multiple linear regression
(MLR) are applied to obtain models useful for the prediction of Caco-2 cell absorption. Making use of a previously
reported database, we obtain four statistically significant MLR models, the best models shown R2=0.72 (s=0.435) for nonstochastic
indices and R2=0.66 (s=0.464) for stochastic indices. No significant difference was found when comparing to
previous reported studies. The models were internally validated using leave-one-out cross-validation, bootstrapping, as
well as Y-scrambling experiments. Additionally, we performed an external validation using a test set, which yields significant
values of R2
ext of 0.70 and 0.72 for stochastic models, showing a better predictive power. Furthermore, we define a
domain of applicability for our models. These results suggest that our approach could offer an appropriate tool as an alternative
to predict the absorption in Caco-2 cells in a short time and decrease experimental costs.
Keywords: Bilinear indices, TOMOCOMD-CARDD, ADME, Caco-2 cell, QSAR.
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