The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure
Abstract
The absorption of a drug compound through the human intestinal cell lining is an important property for potential drug candidates. Measuring this property, however, can be costly and time-consuming. The use of quantitative structure-property relationships (QSPRs) to estimate percent human intestinal absorption (%HIA) is an attractive alternative to experimental measurements. A data set of 86 drug and drug-like compounds with measured values of %HIA taken from the literature was used to develop and test a QSPR mode. The compounds were encoded with calculated molecular structure descriptors. A nonlinear computational neural network model was developed by using the genetic algorithm with a neural network fitness evaluator. The calculated %HIA (cHIA) model performs wells, with root-mean-square (rms) errors of 9.4%HIA units for the training set, 19.7%HIA units for the cross-validation (CV) set, and 16.0%HIA units for the external prediction set.
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Cites
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
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The absolute bioavailability of caffeine in man
Blanchard, J., & Sawers, S. J. A. (1983) · European Journal of Clinical Pharmacology · doi:10.1007/bf00613933 · Cited by 378
Hopfinger, A. J. (1985) · Journal of Medicinal Chemistry · doi:10.1021/jm00147a001 · Cited by 212
Quantitative structure-activity relationships and the unnamed science
Hansch, C. (1993) · Accounts of Chemical Research · doi:10.1021/ar00028a003 · Cited by 172
Cited by
Martin, Y. C. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm0492002 · Cited by 1,020
Zhu, C., Jiang, L., Chen, T.-M., & Hwang, K.-K. (2002) · European Journal of Medicinal Chemistry · doi:10.1016/s0223-5234(02)01360-0 · Cited by 351
Prediction of intestinal absorption: comparative assessment of gastroplus™ and idea™
Parrott, N., & Lavé, T. (2002) · European Journal of Pharmaceutical Sciences · doi:10.1016/s0928-0987(02)00132-x · Cited by 170
Physiologically-based pharmacokinetic simulation modelling
Grass, G. M., & Sinko, P. J. (2002) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(02)00013-3 · Cited by 160
Thelen, K., Coboeken, K., Willmann, S., Burghaus, R., Dressman, J. B., & Lippert, J. (2011) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.22726 · Cited by 139
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Metadata
- Authors
- Wessel, M. D., Jurs, P. C., Tolan, J. W., & Muskal, S. M.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 1998-06-19
- Volume
- 38
- Issue
- 4
- Pages
- 726-735
- ISSN
- 0095-2338 (ISSN-L)
- 1520-5142
- OpenAlex
- W2003873735
- Cited by
- 365
- References
- 6
- FWCI
- 29.13
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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