Differences in Cytochrome P450-Mediated Pharmacokinetics Between Chinese and Caucasian Populations Predicted by Mechanistic Physiologically Based Pharmacokinetic Modelling

Barter, Zoe; Tucker, Geoffrey T.; Rowland‐Yeo, K

doi:10.1007/s40262-013-0089-y

Cited by 109 publications

(116 citation statements)

References 64 publications

Supporting

Mentioning

109

Contrasting

Order By: Relevance

“…This information facilitates prediction of complex DDI situations, allowing simultaneous evaluation of competitive inhibition, time-dependent inhibition or auto-inhibition, enzyme-induction or auto-induction, and transporter-mediated DDI with multiple co-administered perpetrator drugs (Varma et al, 2013b;. It is also possible to simultaneously evaluate the impact of metabolites contributing to DDI or population extremes with respect to enzyme or transporter expression levels, ethnicity, or pharmacogenetic variability in enzyme or transporter expression (Inoue et al, 2006;Jamei et al, 2009c;Barter et al, 2013;Dumont et al, 2013). The utility of PBPK models are further realized in the potential financial savings during drug development since appropriately calibrated models reduce development cost by avoiding the conduct of additional or unnecessary clinical DDI studies when used to simulate "what-if" scenarios.…”

Section: Predicting Drug-drug Interactionsmentioning

confidence: 99%

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

Feng

Goosen

et al. 2013

Drug Metab Dispos

View full text Add to dashboard Cite

Prediction of human pharmacokinetics of new drugs, as well as other disposition attributes, has become a routine practice in drug research and development. Prior to the 1990s, drug disposition science was used in a mostly descriptive manner in the drug development phase. With the advent of in vitro methods and availability of human-derived reagents for in vitro studies, drugdisposition scientists became engaged in the compound design phase of drug discovery to optimize and predict human disposition properties prior to nomination of candidate compounds into the drug development phase. This has reaped benefits in that the attrition rate of new drug candidates in drug development for reasons of unacceptable pharmacokinetics has greatly decreased. Attributes that are predicted include clearance, volume of distribution, halflife, absorption, and drug-drug interactions. In this article, we offer our experience-based perspectives on the tools and methods of predicting human drug disposition using in vitro and animal data.

show abstract

Section: Predicting Drug-drug Interactionsmentioning

confidence: 99%

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

Feng

Goosen

et al. 2013

Drug Metab Dispos

View full text Add to dashboard Cite

show abstract

“…It is well-recognized that PBPK modeling can assess ethnicity sensitivity in virtual populations, thereby informing the need for and design of real studies. Currently, PBPK models have been widely applied to the prediction of pharmacokinetics and drug-drug interactions in healthy subjects [11][12][13][14][15] and in specific populations (eg, cancer patients) in China [16][17][18] ; however, limited demographic and physiological knowledge (eg, liver weight, cardiac output, and enzyme abundance, etc) impede the development of the PBPK approach in the Chinese population. Presently, commercially available PBPK software (eg, SimCYP and Gastroplus) affords the opportunity to predict drug exposure and disposition in different ethnic groups.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the FDA has recommended midazolam for use as a typical substrate to characterize the CYP3A metabolic pathway [24] . Recently, Barter et al developed an ethnicity population database for the prediction of differences in cytochrome P450 (CYP)-mediated pharmacokinetics between Chinese and Caucasians using alprazolam and midazolam as probe drugs for the CYP3A metabolic pathway [11] . This study was the first systematic attempt at investigating inter-ethnic differences in the Chinese population using mechanistic PBPK modeling.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, the predicted oral clearance of midazolam in Chinese was 2-fold higher than previously reported, while the prediction for alprazolam was in good agreement with observed data. with the limitations to the gut physiology and enzymology of the Chinese population model [11,12] , the scarcity of quality of clinical data and appreciable inter-study variability may account for the overprediction [11] . Moreover, the PK data used for model verification were mostly acquired from young Chinese male subjects (19-31 years) with homogeneous demographics [25][26][27] and special populations such as the elderly were not involved.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating a physiologically based pharmacokinetic model for predicting the pharmacokinetics of midazolam in Chinese after oral administration

et al. 2015

View full text Add to dashboard Cite

Aim: To evaluate the SimCYP simulator ethnicity-specific population model for predicting the pharmacokinetics of midazolam, a typical CYP3A4/5 substrate, in Chinese after oral administration. Methods: The physiologically based pharmacokinetic (PBPK) model for midazolam was developed using a SimCYP population-based simulator incorporating Chinese population demographic, physiological and enzyme data. A clinical trial was conducted in 40 Chinese subjects (the half was females) receiving a single oral dose of 15 mg midazolam. The subjects were separated into 4 groups based on age (20-50, 51-65, 66-75, and above 76 years), and the pharmacokinetics profiles of each age-and gender-group were determined, and the results were used to verify the PBPK model. Results: Following oral administration, the simulated profiles of midazolam plasma concentrations over time in virtual Chinese were in good agreement with the observed profiles, as were AUC and C max . Moreover, for subjects of varying ages (20-80 years), the ratios of predicted to observed clearances were between 0.86 and 1.12. Conclusion: The SimCYP PBPK model accurately predicted the pharmacokinetics of midazolam in Chinese from youth to old age. This study may provide novel insight into the prediction of CYP3A4/5-mediated pharmacokinetics in the Chinese population relative to Caucasians and other ethnic groups, which can support the rational design of bridging clinical trials.

show abstract

“…The LY2090314 model was constructed using previously reported human intravenous pharmacokinetic parameters (Zamek-Gliszczynski et al, 2013) and in vitro CYP2B6 suppression parameters from the present study (Supplemental Table 2). A Simcyp default bupropion model [Supplemental Table 3 (Barter et al, 2013)] was used to simulate pharmacokinetics of the hydroxybupropion metabolite, which is a more sensitive marker of CYP2B6 activity than parent (Loboz et al, 2006). LY2090314 suppression of CYP2B6, and its impact on hydroxybupropion exposure, was simulated using the default Simcyp induction module.…”

Section: Methodsmentioning

confidence: 99%

Investigational Small-Molecule Drug Selectively Suppresses Constitutive CYP2B6 Activity at the Gene Transcription Level: Physiologically Based Pharmacokinetic Model Assessment of Clinical Drug Interaction Risk

et al. 2014

View full text Add to dashboard Cite

The glycogen synthase kinase-3 inhibitor LY2090314 specifically impaired CYP2B6 activity during in vitro evaluation of cytochrome P450 (P450) enzyme induction in human hepatocytes. CYP2B6 catalytic activity was significantly decreased following 3-day incubation with 0.1-10 mM LY2090314, on average by 64.3% 6 5.0% at 10 mM. These levels of LY2090314 exposure were not cytotoxic to hepatocytes and did not reduce CYP1A2 and CYP3A activities. LY2090314 was not a time-dependent CYP2B6 inhibitor, did not otherwise inhibit enzyme activity at concentrations £10 mM, and was not metabolized by CYP2B6. Thus, mechanism-based inactivation or other direct interaction with the enzyme could not explain the observed reduction in CYP2B6 activity. Instead, LY2090314 significantly reduced CYP2B6 mRNA levels (I max = 61.9% 6 1.4%; IC 50 = 0.049 6 0.043 mM), which were significantly correlated with catalytic activity (r 2 = 0.87, slope = 0.77; I max = 57.0% 6 10.8%, IC 50 = 0.057 6 0.027 mM). Direct inhibition of constitutive androstane receptor by LY2090314 is conceptually consistent with the observed CYP2B6 transcriptional suppression (I max = 100.0% 6 10.8% and 57.1% 6 2.4%; IC 50 = 2.5 6 1.2 and 2.1 6 0.4 mM for isoforms 1 and 3, respectively) and may be sufficiently extensive to overcome the weak but potent activation of pregnane X receptor by £10 mM LY2090314 (19.3% 6 2.2% of maximal rifampin response, apparent EC 50 = 1.2 6 1.1 nM). The clinical relevance of these findings was evaluated through physiologically based pharmacokinetic model simulations. CYP2B6 suppression by LY2090314 is not expected clinically, with a projected <1% decrease in hepatic enzyme activity and <1% decrease in hydroxybupropion exposure following bupropion coadministration. However, simulations showed that observed CYP2B6 suppression could be clinically relevant for a drug with different pharmacokinetic properties from LY2090314.

show abstract

Differences in Cytochrome P450-Mediated Pharmacokinetics Between Chinese and Caucasian Populations Predicted by Mechanistic Physiologically Based Pharmacokinetic Modelling

Cited by 109 publications

References 64 publications

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

A Perspective on the Prediction of Drug Pharmacokinetics and Disposition in Drug Research and Development

Evaluating a physiologically based pharmacokinetic model for predicting the pharmacokinetics of midazolam in Chinese after oral administration

Investigational Small-Molecule Drug Selectively Suppresses Constitutive CYP2B6 Activity at the Gene Transcription Level: Physiologically Based Pharmacokinetic Model Assessment of Clinical Drug Interaction Risk

Contact Info

Product

Resources

About