Pharmacokinetics in Drug Discovery

Ruiz-Garcı́a, Ana; Bermejo, Marival; Moss, Aaron M.; Casabó, V.G.

doi:10.1002/jps.21009

Cited by 149 publications

(100 citation statements)

References 256 publications

(226 reference statements)

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“…Due to the great efforts made by researchers and the pharmaceutical industry involving in-depth study of pharmacokinetic performance between 1991 and 2000, the percentage of drug development failures due to pharmacokinetic and bioavailability problems has fallen markedly from 40% (in 1991) to 10% (in 2000) [3]. In 2005, three main reasons for terminating development of new drugs were safety, efficacy and cost [4]. However, the combination of activity, safety, and acceptable ADME/T properties, rather than one specific factor, will dictate the overall success of drug discovery and development [4].…”

Section: Introductionmentioning

confidence: 99%

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

Sun

Fan

et al. 2008

J Comput Aided Mol Des

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Quantitative structure-activity relationships (QSAR) methods are urgently needed for predicting ADME/T (absorption, distribution, metabolism, excretion and toxicity) properties to select lead compounds for optimization at the early stage of drug discovery, and to screen drug candidates for clinical trials. Use of suitable QSAR models ultimately results in lesser time-cost and lower attrition rate during drug discovery and development. In the case of ADME/T parameters, drug metabolism is a key determinant of metabolic stability, drug-drug interactions, and drug toxicity. QSAR models for predicting drug metabolism have undergone significant advances recently. However, most of the models used lack sufficient interpretability and offer poor predictability for novel drugs. In this review, we describe some considerations to be taken into account by QSAR for modeling drug metabolism, such as the accuracy/consistency of the entire data set, representation and diversity of the training and test sets, and variable selection. We also describe some novel statistical techniques (ensemble methods, multivariate adaptive regression splines and graph machines), which are not yet used frequently to develop QSAR models for drug metabolism. Subsequently, rational recommendations for developing predictable and interpretable QSAR models are made. Finally, the recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction, including in vivo hepatic clearance, in vitro metabolic stability, inhibitors and substrates of cytochrome P450 families, are briefly summarized.

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Section: Introductionmentioning

confidence: 99%

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

Sun

Fan

et al. 2008

J Comput Aided Mol Des

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“…The subject areas covered by this process mainly include bioinformatics [33], cheminformatics [34], pharmacokinetics [35] and pharmacodynamics [36].…”

Section: Contribution Of Different Disciplines In Caddmentioning

confidence: 99%

Search for in-Silico Applications in Drug Discovery and Applications of Different Disciplines in It: A Survey

Roy

2018

ijarcs

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“…Biological processing of xenobiotics via ADME determines the feasibility of medicinal substances to become effective therapeutic agents (Eddershaw et al, 2000;Ekins et al, 2010;Lombardo & Waters, 2011;Ruiz-Garcia et al, 2008). Factors affecting the fate of xenobiotics may exist anywhere along the ADME process and may lead to a change of well designed and documented pharmacokinetic profiles of registered pharmaceuticals (Harris et al, 2003;.…”

Section: The Beauty and Odds Of Xenobiotics In The Biological Systemmentioning

confidence: 99%

System Building For Safe Medication

Wang¹,

Lian²,

Wang³

2011

Risk Management Trends

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Pharmacokinetics in Drug Discovery

Cited by 149 publications

References 256 publications

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

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

Search for in-Silico Applications in Drug Discovery and Applications of Different Disciplines in It: A Survey

System Building For Safe Medication

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