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

ABSTRACT: PURPOSE:The 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. METHODS:In 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. RESULTS:Correlation 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.

SUBMITTER: Jin Y

PROVIDER: S-EPMC5849655 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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

Jin Yi Y Borell Hubert H Gardin Anne A Ufer Mike M Huth Felix F Camenisch Gian G

European journal of clinical pharmacology 20171222 4

<h4>Purpose</h4>The 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.<h4>Methods</h4>In 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 d ...[more]

PMID: 29273968

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Project description:ObjectivesThe aim of this study was to assess the pharmacokinetics (PK) and safety/tolerability of siponimod in healthy subjects when coadministered with (1) the moderate cytochrome P450 (CYP) 2C9 and CYP3A inhibitor fluconazole (Study A), and (2) with three different CYP2C9 genotype variants (Study B).MethodsStudy A was an open-label, single-dose study comprising periods 1 (14 days; day 1: siponimod 4 mg) and 2 (20 days; day 1: fluconazole 200 mg twice daily; days 2-19: fluconazole 200 mg once daily; day 3: siponimod 4 mg) in healthy subjects (n = 14) with the wild-type CYP2C9 genotype (CYP2C9*1/*1). Study B was a multicentre, open-label study comprising parts 1 (day 1: siponimod 0.25 mg once daily in the CYP2C9*1/*1, CYP2C9*2/*3 and CYP2C9*3/*3 genotypes) and 2 (days 1-2: 0.25 mg once daily; day 3: 0.5 mg once daily in the CYP2C9*2/*3 and CYP2C9*3/*3 genotypes only) in healthy subjects with polymorphic variants of CYP2C9 (n = 24). Pharmacokinetic parameters were calculated using noncompartmental methods.ResultsIn Study A, coadministration with fluconazole produced an approximately twofold increase in mean area under the curve (AUC) versus siponimod alone (from 1110 to 2160 h*ng/mL), and an increase in maximum plasma concentration (Cmax; from 31.2 to 34.0 ng/mL) and elimination half-life (T½; from 40.6 to 61.6 h). In Study B, the AUCs of siponimod were approximately two to fourfold greater in subjects with the CYP2C9*2/*3 and CYP2C9*3/*3 genotypes, with a minor increase in Cmax versus the CYP2C9*1/*1 genotype. The mean T½ was prolonged in the CYP2C9*2/*3 (51 h) and CYP2C9*3/*3 (126 h) genotypes versus the CYP2C9*1/*1 (28 h) genotype. Siponimod did not result in increased adverse events in healthy subjects in both studies.ConclusionsChanges in siponimod PK, when coadministered with fluconazole at steady-state and in subjects with different CYP2C9 genotypes, indicate that the reduced CYP2C9 enzymatic activity does not affect the absorption phase of siponimod but prolongs the elimination phase. These results confirm the relevance of CYP2C9 activity on siponimod metabolism in humans.

Project description:The Biopharmaceutics Drug Disposition Classification System (BDDCS) can be utilized to predict drug disposition, including interactions with other drugs and transporter or metabolizing enzyme effects based on the extent of metabolism and solubility of a drug. However, defining the extent of metabolism relies upon clinical data. Drugs exhibiting high passive intestinal permeability rates are extensively metabolized. Therefore, we aimed to determine if in vitro measures of permeability rate or in silico permeability rate predictions could predict the extent of metabolism, to determine a reference compound representing the permeability rate above which compounds would be expected to be extensively metabolized, and to predict the major route of elimination of compounds in a two-tier approach utilizing permeability rate and a previously published model predicting the major route of elimination of parent drug. Twenty-two in vitro permeability rate measurement data sets in Caco-2 and MDCK cell lines and PAMPA were collected from the literature, while in silico permeability rate predictions were calculated using ADMET Predictor or VolSurf+. The potential for permeability rate to differentiate between extensively and poorly metabolized compounds was analyzed with receiver operating characteristic curves. Compounds that yielded the highest sensitivity-specificity average were selected as permeability rate reference standards. The major route of elimination of poorly permeable drugs was predicted by our previously published model, and the accuracies and predictive values were calculated. The areas under the receiver operating curves were >0.90 for in vitro measures of permeability rate and >0.80 for the VolSurf+ model of permeability rate, indicating they were able to predict the extent of metabolism of compounds. Labetalol and zidovudine predicted greater than 80% of extensively metabolized drugs correctly and greater than 80% of poorly metabolized drugs correctly in Caco-2 and MDCK, respectively, while theophylline predicted greater than 80% of extensively and poorly metabolized drugs correctly in PAMPA. A two-tier approach predicting elimination route predicts 72 ± 9%, 49 ± 10%, and 66 ± 7% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is predicted in silico and 74 ± 7%, 85 ± 2%, and 73 ± 8% of extensively metabolized, biliarily eliminated, and renally eliminated parent drugs correctly when the permeability rate is determined in vitro.

Project description:PurposeThis study was conducted to determine the effect of UGT1A9 98T>C, CYP2B6 516G>T and CYP2C9 430C>T genetic polymorphisms on the pharmacokinetics of propofol in children of different sexes and ages who undergone total intravenous anesthesia (ТIVA) and deep sedation during diagnostic and therapeutic procedures.Patients and methodsThe prospective study included 94 children, ASA I-II status, 1 to 17 years of age, who undergone standard anesthetic protocol for TIVA, which implied the continuous use of propofol. Before the administration of propofol, venous blood was sampled to determine the presence of genetic variations in UGT1A9, CYP2B6 and CYP2C9 gene using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). From each patient included in the study blood samples were taken: 10 mins after the induction of anesthesia, immediately before the discontinuation of the propofol infusion, 10 mins after discontinuation of the propofol infusion and 20 mins after discontinuation of the propofol infusion to determine the pharmacokinetics of the drug in the plasma of the subjects The plasma propofol concentration was determined by HPLC analytical technique.ResultsUGT1A9 genotype is an independent predictor of the propofol concentration in children immediately after the end of the continuous infusion and 10 mins afterwards. In the carriers of the polymorphic UGT1A9 C allele, the propofol distribution constant was higher. The carriers of the polymorphic CYP2B6 T allele received a significantly lower overall and initial dose of propofol. Unlike polymorphism of the UGT1A9 gene, the tested CYP2C9 and CYP2B6 gene polymorphisms are not independent predictors of the pharmacokinetics of propofol.ConclusionFurther investigations of UGT1A9, CYP2B6 and CYP2C9 and other genes that participate in propofol metabolism as well as detailed analyses of the general conditions, administered therapies and associated diseases could explain the large interindividual variability of propofol metabolism in children.

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

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

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