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Updated: Jul 19, 2026

An All-Human Hepatic Culture System for Drug Development Applications
Published on: October 20, 2023
Improved naïve Bayesian modeling of numerical data for absorption, distribution, metabolism and excretion (ADME)
Anthony E Klon1, Jeffrey F Lowrie, David J Diller
1Department of Molecular Modeling, Pharmacopeia Drug Discovery, Inc., P.O. Box 5350, Princeton, New Jersey 08543-5350, USA. aklon@pcop.com
Abstract:
We have implemented a naïve Bayesian classifier which models continuous numerical data using a Gaussian distribution. Several cases of interest in the area of absorption, distribution, metabolism, and excretion prediction are presented which demonstrate that this approach is superior to the implementation of naïve Bayesian classifiers in which continuous chemical descriptors are modeled as binary data. We demonstrate that this enhanced performance, upon comparison with other implementations, is independent of the descriptor sets chosen. We also compare the performance of three implementations of naïve Bayesian classifiers with other previously described models.
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