Nikolaos Tsamandouras (1), Aleksandra Galetin (1), Gemma Dickinson (2), Stephen Hall (2), Amin Rostami-Hodjegan (1,3) and Leon Aarons (1)
(1) Centre for Applied Pharmacokinetic Research, University of Manchester, UK, (2) Eli Lilly and Company, Indianapolis, IN, USA, (3) Simcyp Ltd, Sheffield, UK
Objectives: Simvastatin (SV), a commonly used HMG-CoA reductase inhibitor, is a prodrug with complex pharmacokinetics due to the interconversion between the parent drug and its main active metabolite, simvastatin acid (SVA) [1]. In addition both SV and SVA are subject to drug-drug interactions and are affected differentially by genetic variation in enzyme/transporter proteins relevant for their disposition [2,3]. An operating model that mechanistically describes the disposition of both these forms can have many applications. Therefore, this study aims to develop a mechanistic joint pharmacokinetic model for both SV and SVA.
Methods: SV and SVA plasma concentrations from 34 healthy volunteers derived from two clinical studies with intensive sampling were analysed. Population pharmacokinetic modelling was performed using nonlinear mixed effects software (NONMEM 7.2) and the prior functionality [4]. A mechanistic model was implemented with a physiologically based compartmental structure that allows interconversion between the lactone and acid form of the drug. Prior information for model parameters and (when available) their variability was extracted from physiology literature, in vitro experiments and in silico methods. An independent dataset was used for the external validation of the mechanistic model. The developed model was finally employed to simulate concentration profiles in plasma, liver and muscle and investigate the impact of different scenarios.
Results: The mechanistic model provided a good fit to the plasma concentration data for both SV and SVA, while the model predictions were also in close agreement with the observed data used for external validation. Additionally, the model provides a mechanistic basis for the interconversion between the two forms in different tissues and quantifies this process. Simulations with the developed model using reduced hepatic uptake of SVA (representing the scenario of a SLCO1B1 polymorphism) recovered the reported increase in exposure of SVA in plasma [5]; comparable increased fold-exposure was simulated in the muscle, consistent with the risk of toxicity in this tissue; whereas impact on liver exposure was minimal.
Conclusion: The developed mechanistic model successfully describes the pharmacokinetics of both SV and SVA. Its main advantage is that it allows extrapolation and predictions of different scenarios, such as the impact of genetic polymorphisms or potential drug-drug interactions.
References:
[1] Prueksaritanont T., et al., Interconversion pharmacokinetics of simvastatin and its hydroxy acid in dogs: Effects of gemfibrozil. Pharm Res, 2005. 22(7): p. 1101-1109
[2] Wilke R.A., et al., The clinical pharmacogenomics implementation consortium: CPIC guideline for SLCO1B1 and simvastatin-induced myopathy. Clin Pharmacol Ther, 2012. 92(1): p. 112-117.
[3] Elsby R., et al., Understanding the critical disposition pathways of statins to assess drug-drug interaction risk during drug development: It's not just about OATP1B1. Clin Pharmacol Ther, 2012. 92(5): p. 584-598.
[4] Langdon G., et al., Linking preclinical and clinical whole-body physiologically based pharmacokinetic models with prior distributions in NONMEM. Eur J Clin Pharmacol, 2007. 63(5): p. 485-498
[5] Pasanen M.K., et al., SLCO1B1 polymorphism markedly affects the pharmacokinetics of simvastatin acid. Pharmacogenet Genomics, 2006. 16(12): p. 873-879.
Reference: PAGE 22 (2013) Abstr 2739 [www.page-meeting.org/?abstract=2739]
Poster: Absorption and Physiology-Based PK