In vitro studies and in silico predictions of fluconazole and CYP2C9 genetic polymorphism impact on siponimod metabolism and pharmacokinetics

Abstract

PurposeThe purpose of the study is to investigate the enzyme(s) responsible for siponimod metabolism and to predict the inhibitory effects of fluconazole as well as the impact of cytochrome P450 (CYP) 2C9 genetic polymorphism on siponimod pharmacokinetics (PK) and metabolism.MethodsIn vitro metabolism studies were conducted using human liver microsomes (HLM), and enzyme phenotyping was assessed using a correlation analysis method. SimCYP, a physiologically based PK model, was developed and used to predict the effects of fluconazole and CYP2C9 genetic polymorphism on siponimod metabolism. Primary PK parameters were generated using the SimCYP and WinNonlin software.ResultsCorrelation analysis suggested that CYP2C9 is the main enzyme responsible for siponimod metabolism in humans. Compared with the CYP2C9*1/*1 genotype, HLM incubations from CYP2C9*3/*3 and CYP2C9*2/*2 donors showed ~ 10- and 3-fold decrease in siponimod metabolism, respectively. Simulations of enzyme contribution predicted that in the CYP2C9*1/*1 genotype, CYP2C9 is predominantly responsible for siponimod metabolism (~ 81%), whereas in the CYP2C9*3/*3 genotype, its contribution is reduced to 11%. The predicted exposure increase of siponimod with fluconazole 200 mg was 2.0–2.4-fold for CYP2C9*1/*1 genotype. In context of single dosing, the predicted mean area under the curve (AUC) is 2.7-, 3.0- and 4.5-fold higher in the CYP2C9*2/*2, CYP2C9*2/*3 and CYP2C9*3/*3 genotypes, respectively, compared with the CYP2C9*1/*1 genotype.Conclusion.Enzyme phenotyping with correlation analysis confirmed the predominant role of CYP2C9 in the biotransformation of siponimod and demonstrated the functional consequence of CYP2C9 genetic polymorphism on siponimod metabolism. Simulation of fluconazole inhibition closely predicted a 2-fold AUC change (ratio within ~ 20% deviation) to the observed value. In silico simulation predicted a significant reduction in siponimod clearance in the CYP2C9*2/*2 and CYP2C9*3/*3 genotypes based on the in vitro metabolism data; the predicted exposure was close (within 30%) to the observed results for the CYP2C9*2/*3 and CYP2C9*3/*3 genotypes.Electronic supplementary materialThe online version of this article (10.1007/s00228-017-2404-2) contains supplementary material, which is available to authorized users.

Metabolism and Disposition of Siponimod, a Novel Selective S1P1/S1P5 Agonist, in Healthy Volunteers and In Vitro Identification of Human Cytochrome P450 Enzymes Involved in Its Oxidative Metabolism

“…As both metabolites were produced mainly by CYP2C9 and only to a small extent by other enzymes, M5 and M7 could therefore be considered as CYP2C9-selective or specific metabolites of siponimod. The enzyme phenotyping experiments using both the chemical inhibition and recombinant P450 enzymes methods confirmed the results of additional phenotyping approaches with correlation analysis and CYP2C9-genotype sensitivity analysis (Jin et al, 2018). These experiments demonstrated the predominant contribution of CYP2C9 in the in vitro metabolism, accurately predicting the in vivo pharmacogenetic effect on siponimod clearance.…”

“…CYP2C9 is subject to significant genetic polymorphism (CYP2C9*1, CYP2C9*2, and CYP2C9*3), varying largely between different ethnic populations. Because the biotransformation of siponimod to its hydroxylated metabolites was mainly catalyzed by CYP2C9, a significant effect of genetic polymorphism of this isoenzyme on human metabolism could be anticipated (Jin et al, 2018). To reduce the variability due to genetic polymorphism, only four men with the wide-type CYP2C9*1/*1 genotype were selected for the current human ADME study.…”

Prediction of the Impact of Cytochrome P450 2C9 Genotypes on the Drug–Drug Interaction Potential of Siponimod With Physiologically‐Based Pharmacokinetic Modeling: A Comprehensive Approach for Drug Label Recommendations

“…A siponimod PBPK model was established, in alignment with a drug disposition scheme of siponimod ( Figure ), using a mixed approach combining in vitro data, physicochemical parameters, and PK parameters derived from clinical studies. The clinical PK data from the single ascending dose ( Table ), multiple‐ascending dose ( Table ), absolute bioavailability ( Table ), human absorption, distribution, metabolism, and excretion, and fluconazole DDI study results were used for building of the PBPK model. This model was verified for its PK and the fraction metabolized via CYP2C9 (f m,CYP2C9 ) by the genotype PK data ( Table ) and by clinical siponimod PK and DDI data in the absence and presence of rifampicin verifying the fraction metabolized via CYP3A4 (f m,CYP3A4 ) .…”

Effect of Fluconazole Coadministration and CYP2C9 Genetic Polymorphism on Siponimod Pharmacokinetics in Healthy Subjects

“…Cytochrome P450 (CYP) 2C9 is the major enzyme responsible for the clearance of siponimod [ 3 , 4 ]. Siponimod is eliminated from the systemic circulation mainly due to metabolism and subsequent biliary/faecal excretion [ 4 – 6 ].…”

“…Siponimod is eliminated from the systemic circulation mainly due to metabolism and subsequent biliary/faecal excretion [ 4 – 6 ]. Metabolite M3 is one of the main circulating metabolites of siponimod in humans; it is formed by glucuronidation of the hydroxylated M5 metabolite that results from metabolism primarily via CYP2C9 (79.2%), with a minor contribution from CYP3A4 (18.5%) [ 3 , 6 , 7 ].…”