Development of an in vitro system with human liver microsomes for phenotyping of CYP2C9 genetic polymorphisms with a mechanism-based inactivator

The Utility of Mixed Effects Models in the Evaluation of Complex Genomic Traits In Vitro

In pharmacogenomic studies, the use of human liver microsomes as a model system to evaluate the impact of complex genomic traits (i.e., linkage-disequilibrium patterns, coding, and non-coding variation, etc.) on efficiency of drug metabolism is challenging. To accurately predict the true effect size of genomic traits requires large richly sampled datasets representative of the study population. Moreover, the acquisition of this data can be labor-intensive if the study design or bioanalytical methods are not high throughput, and it is potentially unfeasible if the abundance of sample needed for experiments is limited. To overcome these challenges, we developed a novel strategic approach using non-linear mixed effects models (NLME) to determine enzyme kinetic parameters for individual liver specimens using sparse data. This method can facilitate evaluation of the impact that complex genomic traits have on the metabolism of xenobiotics in vitro when tissue and other resources are limited. In addition to facilitating the accrual of data, it allows for rigorous testing of covariates as sources of kinetic parameter variability. In this in silico study, we present a practical application of such an approach using previously published in vitro cytochrome P450 (CYP) 2D6 data and explore the impact of sparse sampling, and experimental error on known kinetic parameter estimates of CYP2D6 mediated formation of 4-hydroxy-atomoxetine in human liver microsomes. SIGNIFICANCE STATEMENT: This study presents a novel non-linear mixed effects model (NLME)-based framework for evaluating the impact of complex genomic traits on saturable processes described by a Michaelis-Menten kinetics in vitro using sparse data. The utility of this approach extends beyond gene variant associations, including determination of covariate effects on in vitro kinetic parameters and reduced demand for precious experimental material.

An automated cocktail method for in vitro assessment of direct and time-dependent inhibition of nine major cytochrome P450 enzymes - application to establishing CYP2C8 inhibitor selectivity

We developed an in vitro high-throughput cocktail assay with nine major drug-metabolizing CYP enzymes, optimized for screening of time-dependent inhibition. The method was applied to determine the selectivity of the time-dependent CYP2C8 inhibitors gemfibrozil 1-O-β-glucuronide and clopidogrel acyl-β-D-glucuronide. In vitro incubations with CYP selective probe substrates and pooled human liver microsomes were conducted in 96-well plates with automated liquid handler techniques and metabolite concentrations were measured with quantitative UHPLC-MS/MS analysis. After determination of inter-substrate interactions and K_m values for each reaction, probe substrates were divided into cocktails I (tacrine/CYP1A2, bupropion/CYP2B6, amodiaquine/CYP2C8, tolbutamide/CYP2C9 and midazolam/CYP3A4/5) and II (coumarin/CYP2A6, S-mephenytoin/CYP2C19, dextromethorphan/CYP2D6 and astemizole/CYP2J2). Time-dependent inhibitors (furafylline/CYP1A2, selegiline/CYP2A6, clopidogrel/CYP2B6, gemfibrozil 1-O-β-glucuronide/CYP2C8, tienilic acid/CYP2C9, ticlopidine/CYP2C19, paroxetine/CYP2D6 and ritonavir/CYP3A) and direct inhibitor (terfenadine/CYP2J2) showed similar inhibition with single substrate and cocktail methods. Established time-dependent inhibitors caused IC₅₀ fold shifts ranging from 2.2 to 30 with the cocktail method. Under time-dependent inhibition conditions, gemfibrozil 1-O-β-glucuronide was a strong (>90% inhibition) and selective (<< 20% inhibition of other CYPs) inhibitor of CYP2C8 at concentrations ranging from 60 to 300 μM, while the selectivity of clopidogrel acyl-β-D-glucuronide was limited at concentrations above its IC₈₀ for CYP2C8. The time-dependent IC₅₀ values of these glucuronides for CYP2C8 were 8.1 and 38 µM, respectively. In conclusion, a reliable cocktail method including the nine most important drug-metabolizing CYP enzymes was developed, optimized and validated for detecting time-dependent inhibition. Moreover, gemfibrozil 1-O-β-glucuronide was established as a selective inhibitor of CYP2C8 for use as a diagnostic inhibitor in in vitro studies.

Influence of CYP2C9 and COX-2 Genetic Polymorphisms on Clinical Efficacy of Non-Steroidal Anti-Inflammatory Drugs in Treatment of Ankylosing Spondylitis

Background

The aim of this study was to evaluate the relationships of CYP2C9 and COX-2 genetic polymorphisms with therapeutic efficacy of non-steroidal anti-inflammatory drugs (NSAIDs) in treatment of ankylosing spondylitis (AS).

Material/Methods

We enrolled 130 AS inpatients and outpatients in the Arthritis and Rheumatism Department of Peking University First Hospital and 106 healthy people getting routine check-ups between September 2013 and July 2014. CYP2C9 and COX-2 genetic polymorphisms were detected by PCR-RFLP. All AS patients underwent medical treatment and 12-week follow-up treatment. Score differences of BASDAI, ASAS20, ASAS50, and ASAS70 for AS patients with different genotypes before and after treatment were compared.

Results

In terms of COX-2-1290A/G and -1195G/A gene polymorphism genotype and allele frequency, the case group and control group were obviously different (all P<0.05), but CYP2C9*3 polymorphism genotype and allele frequency were not statistically different between the 2 groups (P>0.05). AS patients had improved BASDAI, ASAS20, ASAS50, and ASAS70 scores after they received NSAID treatment (all P<0.05). Furthermore, the efficacy of NSAID in treatment of AS and COX-2 gene −1290A/G and −1195G/A polymorphism were associated (all P<0.05), but it is not associated with CYP2C9 *3 polymorphism (all P>0.05).

Conclusions

COX-2-1290A/G and -1195G/A polymorphism may increase AS risk and they both can be considered as biological indicators for prediction of efficacy of NSAIDs in treatment of AS.

Reaction phenotyping: advances in the experimental strategies used to characterize the contribution of drug-metabolizing enzymes

During the process of drug discovery, the pharmaceutical industry is faced with numerous challenges. One challenge is the successful prediction of the major routes of human clearance of new medications. For compounds cleared by metabolism, accurate predictions help provide an early risk assessment of their potential to exhibit significant interpatient differences in pharmacokinetics via routes of metabolism catalyzed by functionally polymorphic enzymes and/or clinically significant metabolic drug-drug interactions. This review details the most recent and emerging in vitro strategies used by drug metabolism and pharmacokinetic scientists to better determine rates and routes of metabolic clearance and how to translate these parameters to estimate the amount these routes contribute to overall clearance, commonly referred to as fraction metabolized. The enzymes covered in this review include cytochrome P450s together with other enzymatic pathways whose involvement in metabolic clearance has become increasingly important as efforts to mitigate cytochrome P450 clearance are successful. Advances in the prediction of the fraction metabolized include newly developed methods to differentiate CYP3A4 from the polymorphic enzyme CYP3A5, scaling tools for UDP-glucuronosyltranferase, and estimation of fraction metabolized for substrates of aldehyde oxidase.