Literature DB >> 17097093

Evaluation of chromatographic descriptors for the prediction of gastro-intestinal absorption of drugs.

E Deconinck1, H Ates, N Callebaut, E Van Gyseghem, Y Vander Heyden.   

Abstract

The use of chromatographic descriptors in QSAR was evaluated. Therefore, retentions were measured on an immobilized artificial membrane system, 2 micellar liquid chromatography systems and 17 orthogonal or disimilar reversed-phase liquid chromatographic systems. It was investigated whether it was possible to model gastro-intestinal absorption as a function of chromatographic retentions applying two linear and one non-linear multivariate modeling technique. In a second step it was evaluated if models built with theoretical descriptors could be improved by adding the measured retention factors to the data set of descriptive variables. It was seen that gastro-intestinal absorption could be modelled in function of chromatographic retention using the non-linear modeling technique multivariate adaptive regression splines (MARS). The best models were obtained using a combination of theoretical and chromatographic descriptors with MARS as modeling technique.

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Year:  2006        PMID: 17097093     DOI: 10.1016/j.chroma.2006.10.068

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  3 in total

Review 1.  Drug absorption modeling as a tool to define the strategy in clinical formulation development.

Authors:  Martin Kuentz
Journal:  AAPS J       Date:  2008-08-27       Impact factor: 4.009

2.  Problems with molecular mechanics implementations on the example of 4-benzoyl-1-(4-methyl-imidazol-5-yl)-carbonylthiosemicarbazide.

Authors:  Agata Siwek; Katarzyna Swiderek; Stefan Jankowski
Journal:  J Mol Model       Date:  2011-05-28       Impact factor: 1.810

Review 3.  Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction.

Authors:  Haiyan Li; Jin Sun; Xiaowen Fan; Xiaofan Sui; Lan Zhang; Yongjun Wang; Zhonggui He
Journal:  J Comput Aided Mol Des       Date:  2008-06-24       Impact factor: 3.686

  3 in total

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