In Silico Prediction of PAMPA Effective Permeability Using a Two-QSAR Approach.

ABSTRACT: Oral administration is the preferred and predominant route of choice for medication. As such, drug absorption is one of critical drug metabolism and pharmacokinetics (DM/PK) parameters that should be taken into consideration in the process of drug discovery and development. The cell-free in vitro parallel artificial membrane permeability assay (PAMPA) has been adopted as the primary screening to assess the passive diffusion of compounds in the practical applications. A classical quantitative structure-activity relationship (QSAR) model and a machine learning (ML)-based QSAR model were derived using the partial least square (PLS) scheme and hierarchical support vector regression (HSVR) scheme to elucidate the underlying passive diffusion mechanism and to predict the PAMPA effective permeabi

SUBMITTER: Chi CT 

PROVIDER: S-EPMC6651837 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature