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Orthogonal chromatographic descriptors for modelling Caco-2 drug permeability
E Deconinck1, T Verstraete, E Van Gyseghem
1Department of Analytical Chemistry and Pharmaceutical Technology, Pharmaceutical Institute, Vrije Universiteit Brussel-VUB, Brussels, Belgium. Eric.Deconinck@wiv-isp.be
Chromatographic descriptors offer a viable alternative to Caco-2 permeability assays for drug absorption screening. This study developed a predictive model using limited chromatographic systems and physicochemical properties.
Area of Science:
- Pharmacokinetics and Drug Metabolism
- Computational Chemistry
- Analytical Chemistry
Background:
- Caco-2 permeability assays are standard for predicting oral drug absorption but are time-consuming and resource-intensive.
- Chromatographic descriptors offer a potential high-throughput alternative for early-stage drug absorption screening.
- Developing robust quantitative structure-activity relationship (QSAR) models requires careful selection of orthogonal chromatographic systems.
Purpose of the Study:
- To evaluate the utility of chromatographic descriptors as surrogates for Caco-2 permeability in drug absorption screening.
- To develop and validate a QSAR model for predicting drug absorption using chromatographic data.
- To identify optimal chromatographic systems and physicochemical parameters for accurate prediction.
Main Methods:
- Measured retentions on 17 orthogonal Reversed-Phase Liquid Chromatography (RPLC) systems and one Immobilized Artificial Membrane (IAM) system.
- Utilized literature data for retentions on a Micellar Liquid Chromatography (MLC) system.
- Selected dissimilar chromatographic systems and employed retention factors as descriptors in Stepwise Multiple Linear Regression (SMLR) for QSAR modeling.
- Incorporated lipophilicity (Moriguchi n-octanol/water partition coefficient) and molecular volume into the final QSAR model.
Main Results:
- A QSAR model was developed using retention data from only two selected chromatographic systems, demonstrating good descriptive and acceptable predictive performance.
- The final, high-quality model integrated two chromatographic systems with lipophilicity and molecular volume.
- The combined model achieved superior predictive accuracy for drug absorption compared to models based solely on chromatographic data.
Conclusions:
- Chromatographic descriptors, particularly when combined with physicochemical parameters, can effectively predict drug absorption.
- A minimal set of orthogonal chromatographic systems, coupled with molecular descriptors, can replace traditional Caco-2 permeability assays for initial drug screening.
- This approach offers a more efficient and cost-effective strategy for early-stage drug development and pharmacokinetic profiling.
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