Geerts Tessy, Vander Heyden Yvan
Department of Analytical Chemistry and Pharmaceutical Technology, Center for Pharmaceutical Research, Vrije Universiteit Brussel, Belgium.
Comb Chem High Throughput Screen. 2011 Jun 1;14(5):339-61. doi: 10.2174/138620711795508359.
The accurate prediction of the in-vivo pharmacokinetics of a new potential drug compound based on only its virtual structure is the ultimate goal of in-silico ADME-Tox property modeling. A comprehensive review is made on recent studies concerning the A (absorption) in ADME-Tox, i.e. the in-silico modeling of both Caco-2 permeability and human intestinal absorption. The data sets used, the descriptors selected to build the models, the variable selection methods, the modeling techniques and the performed model validation are critically discussed. It was concluded that reliable models which improve the success rate of compound selection and drug development are still lacking. Limiting the quality of the models are, for instance, inappropriate compilation of data sets, lack of an appropriate outlier detection and unrepresentativeness of training and test sets for the data population. The definition of some best practices or guidelines for the different steps of the modeling procedure might improve the predictions and make the procedure uniform, i.e. "standard tools" in drug development would become available.
仅基于新的潜在药物化合物的虚拟结构准确预测其体内药代动力学是计算机辅助ADME-Tox性质建模的最终目标。本文对近期有关ADME-Tox中A（吸收）的研究进行了全面综述，即Caco-2通透性和人体肠道吸收的计算机模拟建模。对所使用的数据集、构建模型所选的描述符、变量选择方法、建模技术以及所进行的模型验证进行了批判性讨论。得出的结论是，仍然缺乏能够提高化合物筛选和药物开发成功率的可靠模型。例如，数据集汇编不当、缺乏适当的异常值检测以及训练集和测试集对于数据总体缺乏代表性等因素限制了模型的质量。为建模过程的不同步骤定义一些最佳实践或指导方针可能会改善预测并使该过程统一，即药物开发中会出现“标准工具”。
