Janak R. Wedagedera (1), Khaled Abduljalil (1), Theresa Cain (1), Masoud Jamei (1) and Amin Rostami-Hodjegan (1)(2)
(1) Simcyp (a Certara Company), Sheffield, United Kingdom (2) Manchester Pharmacy School, University of Manchester, Manchester, United Kingdom.
Objectives: We have previously compared the marginal distribution of 13 hepatic CYP450 enzymes with and without considering inter-correlations of absolute abundances using a PBPK modelling approach. The analyses revealed that CYP2D6 and CYP3A4 are moderately correlated enzymes in the liver. In present study we extend that work to assess the impact of these correlations when predicting drug-drug-interactions (DDI) using a model compound substrate of the above enzymes.
Methods: Using the Simcyp Simulator V15R1, simulations were performed for a drug not considering correlations between the CYP enzymes to obtain a control arm in a virtual population. The model compound is a substrate of both CYP2D6 and CYP3A4. Hepatic clearance values of this drug and its distributions are calculated assuming no other elimination route. In a second simulation, a DDI scenario was mimicked by reducing the hepatic clearance by 70% via inhibition of CYP2D6. The same scenario was repeated applying inter-correlation of CYP2D6 and CYP3A4. Finally, distributions of hepatic clearance values of the correlated and uncorrelated cases have been compared by calculating the Cramer statistic [2] for multivariate distributions.
Results: The population distribution of the hepatic clearance of the drug metabolised by CYP enzymes show significant differences between the mean, standard deviation and overall similarity of the correlated and uncorrelated samples assessed via Cramer statistic. When 70% of CYP2D6 mediated clearance is inhibited in both correlated and uncorrelated cases, the population mean in these two cases were significantly different.
Conclusions: The simulation results in this study indicate that incorporating the correlations between the abundance of the hepatic CYP450 enzymes can have an important impact on the prediction of hepatic clearance of drugs and the DDI level. It also highlights the importance of mechanistic incorporation of relevant covariates when developing population-based PBPK frameworks to generate more realistic virtual populations and conduct virtual clinical trials to assess drug safety and efficacy.
References:
[1] Brahim Achour, Matthew R. Russel, Jill Barber, and Amin Rostami-Hodjegan, Simultaneous Quantification of the Abundance of Several Cytochrome P450 and Uridine 59-Diphospho-Glucuronosyltransferase Enzymes in Human Liver Microsomes Using Multiplexed Targeted Proteomics, Drug Metab Dispos 42:500–510 (2014)
[2] Baringhaus, L. and Franz, C. (2004) On a new multivariate two-sample test, Journal of Multivariate Analysis, 88, p. 190-206
Reference: PAGE 25 (2016) Abstr 6016 [www.page-meeting.org/?abstract=6016]
Poster: Methodology - Covariate/Variability Models