Literature DB >> 19138063

Predicting circulating human metabolites: how good are we?

Shelby Anderson1, Debra Luffer-Atlas, Mary Pat Knadler.   

Abstract

The FDA issued a guidance on the safety testing of metabolites in February 2008, in which they stated that metabolites of concern are those that are detected at levels greater than 10% of the systemic exposure of the parent at steady state. This has presented many challenges in determining the circulating human metabolites at an early stage of development. The intention of this perspective is to address the question of how effective in vitro metabolism and early exploratory clinical data are in predicting the circulating metabolites from both a qualitative and a quantitative perspective. To this end, data were reviewed from 17 molecules in the Lilly portfolio for which there were in vitro data and a radiolabeled study in humans. Twelve example cases are presented in detail to demonstrate trends for when in vitro data adequately predicted in vivo (41%), when in vitro data underpredicted the circulating metabolites (35%), and when in vitro data overpredicted the circulating metabolites (24%). In addition, cases that present special challenges due to very low levels of the circulating parent or long half-lives of the parent and/or metabolites are presented. The trends indicate that the more complex the metabolism, the less likely the in vitro data were to predict the circulating metabolites. The in vitro data were also less predictive for N-glucuronidations and non-P450-mediated cleavage reactions. Although the in vitro data were better at predicting clearance pathways, the data set often failed to predict the quantity of metabolites, which is needed in consideration of whether or not a "disproportionate" metabolite may be circulating in human plasma.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19138063     DOI: 10.1021/tx8004086

Source DB:  PubMed          Journal:  Chem Res Toxicol        ISSN: 0893-228X            Impact factor:   3.739


  17 in total

1.  In vitro glucuronidation of the antibacterial triclocarban and its oxidative metabolites.

Authors:  N H Schebb; B Franze; R Maul; A Ranganathan; B D Hammock
Journal:  Drug Metab Dispos       Date:  2011-09-27       Impact factor: 3.922

2.  Prediction of relative in vivo metabolite exposure from in vitro data using two model drugs: dextromethorphan and omeprazole.

Authors:  Justin D Lutz; Nina Isoherranen
Journal:  Drug Metab Dispos       Date:  2011-10-18       Impact factor: 3.922

Review 3.  Cardioprotection in ischaemia-reperfusion injury: novel mechanisms and clinical translation.

Authors:  Francisco Altamirano; Zhao V Wang; Joseph A Hill
Journal:  J Physiol       Date:  2015-08-02       Impact factor: 5.182

4.  Sprague Dawley Rag2-Null Rats Created from Engineered Spermatogonial Stem Cells Are Immunodeficient and Permissive to Human Xenografts.

Authors:  Fallon K Noto; Valeriya Adjan-Steffey; Goutham Narla; Tseten Y Jamling; Min Tong; Kameswaran Ravichandran; Wei Zhang; Angela Arey; Christopher B McClain; Eric Ostertag; Sahar Mazhar; Jaya Sangodkar; Analisa DiFeo; Jack Crawford
Journal:  Mol Cancer Ther       Date:  2018-09-11       Impact factor: 6.261

5.  Using chimeric mice with humanized livers to predict human drug metabolism and a drug-drug interaction.

Authors:  Toshihiko Nishimura; Toshiko Nishimura; Yajing Hu; Manhong Wu; Edward Pham; Hiroshi Suemizu; Menashe Elazar; Michael Liu; Ramazan Idilman; Cihan Yurdaydin; Peter Angus; Catherine Stedman; Brian Murphy; Jeffrey Glenn; Masato Nakamura; Tatsuji Nomura; Yuan Chen; Ming Zheng; William L Fitch; Gary Peltz
Journal:  J Pharmacol Exp Ther       Date:  2012-11-08       Impact factor: 4.030

6.  Functional muscle analysis of the Tcap knockout mouse.

Authors:  C D Markert; M P Meaney; K A Voelker; R W Grange; H W Dalley; J K Cann; M Ahmed; B Bishwokarma; S J Walker; S X Yu; M Brown; M W Lawlor; A H Beggs; M K Childers
Journal:  Hum Mol Genet       Date:  2010-03-16       Impact factor: 6.150

7.  Chimeric TK-NOG mice: a predictive model for cholestatic human liver toxicity.

Authors:  Dan Xu; Manhong Wu; Sachiko Nishimura; Toshihiko Nishimura; Sara A Michie; Ming Zheng; Zicheng Yang; Alexander John Yates; Jeffrey S Day; Kathleen M Hillgren; Saori Takedai Takeda; Yuan Guan; Yingying Guo; Gary Peltz
Journal:  J Pharmacol Exp Ther       Date:  2014-11-25       Impact factor: 4.030

Review 8.  Rationalization and prediction of in vivo metabolite exposures: the role of metabolite kinetics, clearance predictions and in vitro parameters.

Authors:  Justin D Lutz; Yasushi Fujioka; Nina Isoherranen
Journal:  Expert Opin Drug Metab Toxicol       Date:  2010-09       Impact factor: 4.481

9.  Can 'humanized' mice improve drug development in the 21st century?

Authors:  Gary Peltz
Journal:  Trends Pharmacol Sci       Date:  2013-04-19       Impact factor: 14.819

Review 10.  Pharmacology of Pimasertib, A Selective MEK1/2 Inhibitor.

Authors:  Nuggehally R Srinivas
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2018-08       Impact factor: 2.441

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.