Rationalizing underprediction of drug clearance from enzyme and transporter kinetic data: From in vitro tools to mechanistic modeling
Methods in Molecular Biology, ISSN: 1064-3745, Vol: 1113, Page: 255-288
2014
- 22Citations
- 20Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations22
- Citation Indexes22
- 22
- CrossRef15
- Captures20
- Readers20
- 20
Book Chapter Description
Over the years, there has been an increase in the number and quality of available in vitro tools for the assessment of clearance. Complexity of data analysis and modelling of corresponding in vitro data has increased in an analogous manner, in particular for the simultaneous characterization of transporter and metabolism kinetics, together with intracellular binding and passive diffusion. In the current chapter, the impact of different factors on the in vitro-in vivo extrapolation of clearance will be addressed in a stepwise manner, from the selection of the most adequate in vitro system and experimental design/condition to the corresponding modelling of data generated. The application of static or physiologically based pharmacokinetic models in the prediction of clearance will be discussed, highlighting limitations and current challenges of some of the approaches. Particular focus will be on the ability of in vitro and in silico predictive tools to overcome the trend of clearance underprediction. Improvements made as a result of inclusion of extrahepatic metabolism and consideration of transporter-metabolism interplay across different organs will be discussed. © Springer Science+Business Media, LLC 2014.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84934440063&origin=inward; http://dx.doi.org/10.1007/978-1-62703-758-7_13; http://www.ncbi.nlm.nih.gov/pubmed/24523117; https://link.springer.com/10.1007/978-1-62703-758-7_13; https://dx.doi.org/10.1007/978-1-62703-758-7_13; https://link.springer.com/protocol/10.1007/978-1-62703-758-7_13
Springer Science and Business Media LLC
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