In Silico Predictions of ADME-Tox Properties: Drug Absorption

被引:34
|
作者
Geerts, Tessy [1 ]
Heyden, Yvan Vander [1 ]
机构
[1] Vrije Univ Brussel, Pharmaceut Res Ctr CePhaR, Dept Analyt Chem & Pharmaceut Technol FABI, B-1090 Brussels, Belgium
关键词
ADME-tox; Caco-2; drug absorption; human intestinal absorption; in silico methods; QSAR; ADAPTIVE REGRESSION SPLINES; HUMAN INTESTINAL-ABSORPTION; CACO-2; CELL-PERMEABILITY; GASTROINTESTINAL ABSORPTION; MOLECULAR DESCRIPTORS; COMPUTATIONAL PREDICTION; MEMBRANE-PERMEABILITY; FEATURE-SELECTION; DISCOVERY; TRANSPORT;
D O I
10.2174/138620711795508359
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:339 / 361
页数:23
相关论文
共 50 条
  • [31] In silico ADME/Tox:: why models fail
    Stouch, TR
    Kenyon, JR
    Johnson, SR
    Chen, XQ
    Doweyko, A
    Li, Y
    [J]. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2003, 17 (02) : 83 - 92
  • [32] Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach
    Daoui, Ossama
    Elkhattabi, Souad
    Bakhouch, Mohamed
    Belaidi, Salah
    Bhandare, Richie R.
    Shaik, Afzal B.
    Mali, Suraj N.
    Chtita, Samir
    [J]. ACS OMEGA, 2023,
  • [33] ABC Transporters in Multi-Drug Resistance and ADME-Tox of Small Molecule Tyrosine Kinase Inhibitors
    Deng, Jiexin
    Shao, Jie
    Markowitz, John S.
    An, Guohua
    [J]. PHARMACEUTICAL RESEARCH, 2014, 31 (09) : 2237 - 2255
  • [34] In Silico Studies in ADME/Tox: Caveat Emptor
    Franklin, Ronald B.
    [J]. CURRENT COMPUTER-AIDED DRUG DESIGN, 2009, 5 (02) : 128 - 138
  • [35] In silico ADME/Tox: why models fail
    Terry R. Stouch
    James R. Kenyon
    Stephen R. Johnson
    Xue-Qing Chen
    Arthur Doweyko
    Yi Li
    [J]. Journal of Computer-Aided Molecular Design, 2003, 17 : 83 - 92
  • [36] Better, Earlier ADME/Tox Predictions in Cells
    Labant, MaryAnn
    [J]. GENETIC ENGINEERING & BIOTECHNOLOGY NEWS, 2012, 32 (21): : 20 - 21
  • [37] In Silico ADME/Tox Models: Progress and Challenges
    DeLisle, Robert Kirk
    Diller, David J.
    [J]. CURRENT COMPUTER-AIDED DRUG DESIGN, 2009, 5 (02) : 69 - 70
  • [38] In Silico Predictions of ADME/T Properties: Progress and Challenges
    Hou, Tingjun
    [J]. COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2011, 14 (05) : 306 - 306
  • [39] ABC Transporters in Multi-Drug Resistance and ADME-Tox of Small Molecule Tyrosine Kinase Inhibitors
    Jiexin Deng
    Jie Shao
    John S. Markowitz
    Guohua An
    [J]. Pharmaceutical Research, 2014, 31 : 2237 - 2255
  • [40] Applications of the microphysiology systems database for experimental ADME-Tox and disease models
    Schurdak, Mark
    Vernetti, Lawrence
    Bergenthal, Luke
    Wolter, Quinn K.
    Shun, Tong Ying
    Karcher, Sandra
    Taylor, D. Lansing
    Gough, Albert
    [J]. LAB ON A CHIP, 2020, 20 (08) : 1472 - 1492