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A Fully Computational Model for Predicting Percutaneous Drug Absorption

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44815

Kohlbacher,  Oliver
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45028

Merkwirth,  Christian
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44907

Lengauer,  Thomas
Computational Biology and Applied Algorithmics, MPI for Informatics, Max Planck Society;

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Zitation

Neumann, D., Kohlbacher, O., Merkwirth, C., & Lengauer, T. (2006). A Fully Computational Model for Predicting Percutaneous Drug Absorption. Journal of Chemical Information and Modeling, 1, 424-429.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-21E1-E
Zusammenfassung
The prediction of transdermal absorption for arbitrary penetrant structures has several important applications in the pharmaceutical industry. We propose a new data-driven, predictive model for skin permeability coefficients kp based on an ensemble model using k-nearest-neighbor models and ridge regression. The model was trained and validated with a newly assembled data set containing experimental data and structures for 110 compounds. On the basis of three purely computational descriptors (molecular weight, calculated octanol/water partition coefficient, and solvation free energy), we have developed a model allowing for the reliable, purely computational prediction of skin permeability coefficients. The model is both accurate and robust, as we showed in an extensive validation (correlation coefficient for leave-one-out cross validation: Q = 0.948, mean standard error: 0.2 for log kp).