Minimizing Polymorphic Metabolism in Drug Discovery: Evaluation of the Utility of in Vitro Methods for Predicting Pharmacokinetic Consequences Associated with CYP2D6 Metabolism

Impact of Viloxazine Extended-Release Capsules (Qelbree®) on Select Cytochrome P450 Enzyme Activity and Evaluation of CYP2D6 Genetic Polymorphisms on Viloxazine Pharmacokinetics

BACKGROUND AND OBJECTIVE

Viloxazine extended-release (ER) [Qelbree®] is a nonstimulant attention-deficit/hyperactivity disorder (ADHD) treatment. In vitro studies suggested potential for viloxazine to inhibit cytochrome 450 (CYP) enzymes 1A2, 2B6, 2D6 and 3A4. This clinical study therefore evaluated viloxazine ER effects on index substrates for CYP1A2, 2D6, and 3A4, and secondarily evaluated the impact of CYP2D6 polymorphisms on viloxazine pharmacokinetics.

METHODS

Thirty-seven healthy subjects received a modified Cooperstown cocktail (MCC; caffeine 200 mg, dextromethorphan 30 mg, midazolam 0.025 mg/kg) on Day 1, viloxazine ER 900 mg/day on Days 3-5, and a combination of viloxazine ER 900 mg and MCC on Day 6. Viloxazine ER effects on MCC substrates were evaluated using analysis of variance. The impact of CYP2D6 genetic polymorphisms on steady-state viloxazine plasma concentrations was evaluated using Student's t test assessing pharmacokinetic parameter differences between poor versus extensive metabolizers.

RESULTS

The least squares geometric mean ratio [GMR%] (90% CI) of MCC substrate + viloxazine ER/MCC substrate alone for caffeine maximum concentration (Cmax), area under the plasma concentration-time curve from time 0 to the last quantifiable concentration (AUCt), and area under the plasma concentration-time curve from time 0 extrapolated to infinity (AUC∞) was 99.11 (95.84-102.49), 436.15 (398.87-476.92), and 583.35 (262.41-1296.80), respectively; 150.76 (126.03-180.35), 185.76 (155.01-222.61), and 189.71 (160.37-224.42) for dextromethorphan Cmax, AUCt, and AUC∞, respectively; and 112.81 (104.71-121.54), 167.56 (153.05-183.45), and 168.91 (154.38-184.80) for midazolam Cmax, AUCt, and AUC∞, respectively. At steady state, viloxazine least squares GMR (90% CI) for poor/extensive CYP2D6 metabolizers were Cmax 120.70 (102.33-142.37) and area under the plasme concentration-time curve from time 0 to 24 hours (AUC0-24 125.66 (105.36-149.87)).

CONCLUSION

Viloxazine ER is a strong CYP1A2 inhibitor and a weak CYP2D6 and CYP3A4 inhibitor. CYP2D6 polymorphisms did not meaningfully alter the viloxazine ER pharmacokinetic profile.

Could Cytochrome P450 2D6, 3A4 and 3A5 Polymorphisms Explain the Variability in Clinical Response to Clomiphene Citrate of Anovulatory PCOS Women?

INTRODUCTION

Cytochrome P450 2D6, 3A4 and 3A5 are involved in the metabolism of many drugs. These enzymes have a genetic polymorphism responsible for different metabolic phenotypes. They play a role in the metabolism of clomiphene citrate (CC), which is used to induce ovulation. Response to CC treatment is variable, and no predictive factors have thus far been identified.

OBJECTIVE

To study a possible link between the cytochrome P450 2D6, 3A4 and 3A5 polymorphisms and clinical response to CC.

STUDY DESIGN

Seventy-seven women with anovulatory Polycystic Ovarian Syndrome (PCOS) treated with CC were included which determined their cytochrome P450 2D6, 3A4 and 3A5 genotypes and used the results to predict ovarian response to this drug. Predicted responses based on the cytochrome genotypes were compared with the observed clinical responses using the calculation of a weighted Kappa coefficient.

MAIN OUTCOME MEASURES

Number of dominant follicles assessed by ultrasound at the end of the follicular phase and confirmation of ovulation by blood progesterone assay in the luteal phase.

RESULTS

Concordance between the predicted and observed responses for the combination of the three cytochromes was 36.71%, with a negative Kappa coefficient (K = -0.0240), which corresponds to a major disagreement. Similarly, for predictions based on the cytochrome P450 2D6 genotype alone, only 39.24% of predictions were verified (coefficient K = -0.0609).

CONCLUSION

The genetic polymorphism of cytochromes P450 2D6, 3A4 and 3A5 does not appear to influence clinical response to CC used to induce ovulation in anovulatory PCOS women.

Inter-phenotypic differences in CYP2C9 and CYP2C19 metabolism: Bayesian meta-regression of human population variability in kinetics and application in chemical risk assessment

Quantifying variability in pharmacokinetics (PK) and toxicokinetics (TK) provides a science-based approach to refine uncertainty factors (UFs) for chemical risk assessment. In this context, genetic polymorphisms in cytochromes P450 (CYPs) drive inter-phenotypic differences and may result in reduction or increase in metabolism of drugs or other xenobiotics. Here, an extensive literature search was performed to identify PK data for probe substrates of the human polymorphic isoforms CYP2C9 and CYP2C19. Relevant data from 158 publications were extracted for markers of chronic exposure (clearance and area under the plasma concentration-time curve) and analysed using a Bayesian meta-regression model. Enzyme function (EF), driven by inter-phenotypic differences across a range of allozymes present in extensive and poor metabolisers (EMs and PMs), and fraction metabolised (Fm), were identified as exhibiting the highest impact on the metabolism. The Bayesian meta-regression model provided good predictions for such inter-phenotypic differences. Integration of population distributions for inter-phenotypic differences and estimates for EF and Fm allowed the derivation of CYP2C9- and CYP2C19-related UFs which ranged from 2.7 to 12.7, and were above the default factor for human variability in TK (3.16) for PMs and major substrates (Fm >60%). These results provide population distributions and pathway-related UFs as conservative in silico options to integrate variability in CYP2C9 and CYP2C19 metabolism using in vitro kinetic evidence and in the absence of human data. The future development of quantitative extrapolation models is discussed with particular attention to integrating human in vitro and in vivo PK or TK data with pathway-related variability for chemical risk assessment.

Phenoconversion of Cytochrome P450 Metabolism: A Systematic Review

Phenoconversion is the mismatch between the individual’s genotype-based prediction of drug metabolism and the true capacity to metabolize drugs due to nongenetic factors. While the concept of phenoconversion has been described in narrative reviews, no systematic review is available. A systematic review was conducted to investigate factors contributing to phenoconversion and the impact on cytochrome P450 metabolism. Twenty-seven studies met the inclusion criteria and were incorporated in this review, of which 14 demonstrate phenoconversion for a specific genotype group. Phenoconversion into a lower metabolizer phenotype was reported for concomitant use of CYP450-inhibiting drugs, increasing age, cancer, and inflammation. Phenoconversion into a higher metabolizer phenotype was reported for concomitant use of CYP450 inducers and smoking. Moreover, alcohol, pregnancy, and vitamin D exposure are factors where study data suggested phenoconversion. The studies reported genotype–phenotype discrepancies, but the impact of phenoconversion on the effectiveness and toxicity in the clinical setting remains unclear. In conclusion, phenoconversion is caused by both extrinsic factors and patient- and disease-related factors. The mechanism(s) behind and the extent to which CYP450 metabolism is affected remain unexplored. If studied more comprehensively, accounting for phenoconversion may help to improve our ability to predict the individual CYP450 metabolism and personalize drug treatment.

How precise is quantitative prediction of pharmacokinetic effects due to drug-drug interactions and genotype from in vitro data? A comprehensive analysis on the example CYP2D6 and CYP2C19 substrates

Drug-drug interactions (DDI) and genomic variation (PG) can lead to dangerously high blood and tissue concentrations with some drugs but may be negligible with other drugs. Using a quantitative metaanalysis, we analyzed on the example of CYP2D6 and CYP2C19 substrates, how well the effects of DDI and PG can be predicted by in vitro methods. In addition, we analyzed the quantitative effect of prototypic inhibitors of the two enzymes in relation to their genetic deficiency. More than 600 published studies were screened which compared either human pharmacokinetics with and without comedication, or which compared human pharmacokinetics of deficient with extensive metabolizers, or which assessed metabolism by in vitro approaches. With human liver microsomes, the in vitro to in vivo agreement of fractional clearances was reasonably high if loss of substrate was quantified in the in vitro assays performed with and without enzyme specific inhibitors. Also a generally very high correlation between the clinical pharmacokinetic effects of inherited deficiency and inhibition by drug-drug interactions could be demonstrated. Most cases of poor correlation were explained by the lack of CYP2D6 versus CYP2C19 specificity of fluoxetine or by a poor knowledge of the quantitative contribution of the metabolic pathways if metabolite formation was quantified in the in vitro assays. The good correspondence of the in vitro data with clinical DDI and clinical PG studies may be a good basis for future application of these methods in drug development and drug therapy.

Metabolism and in vitro drug-drug interaction assessment of viloxazine

Viloxazine is currently being developed as a treatment for attention deficit/hyperactivity disorder (ADHD). The aim of these studies is to update the understanding of the rat and human metabolism and the in vitro drug-drug interaction profile of viloxazine to a degree where it meets current regulatory standards for such investigations. In vivo absorption-distribution-metabolism-excretion (ADME) studies demonstrated that in humans 5-hydroxylation followed by glucuronidation is the major metabolic route. This route was also seen as a minor route in rats where the major route is O-deethylation with subsequent sulfation. In humans, the 5-hydoxylation pathway is mediated by CYP2D6. An estimate for the fraction of the metabolism via this pathway suggests a PM/EM difference of <2-fold, making it highly unlikely that this will be an issue of clinical significance. Viloxazine forms a unique N-carbamoyl glucuronide in humans. The chemical reactivity characteristics of this metabolite are similar to stable glucuronide conjugates and dissimilar from acyl glucuronides; therefore, it is regarded as a stable Phase II conjugate. In vitro drug-drug interaction (DDI) testing indicates that viloxazine is not a significant inhibitor or inducer of CYPs and transporters with the exception of CYP1A2.

Discovery of DSP-1053, a novel benzylpiperidine derivative with potent serotonin transporter inhibitory activity and partial 5-HT1A receptor agonistic activity

We have previously shown that SMP-304, a serotonin uptake inhibitor with weak 5-HT_1A partial agonistic activity, may act under high serotonin levels as a 5-HT_1A antagonist that improves the onset of paroxetine in the rat swimming test. However, SMP-304 is mostly metabolized by CYP2D6, indicating limited efficacy among individuals and increased side effects. To reduce CYP2D6 metabolic contribution and enhance SERT/5-HT_1A binding affinity, we carried out a series of substitutions at the bromine atom in the left part of the benzene ring of SMP-304 and replaced the right part of SMP-304 with a chroman-4-one. This optimization work led to the identification of the antidepressant candidate DSP-1053 as a potent SERT inhibitor with partial 5-HT_1A receptor agonistic activity. DSP-1053 showed low CYP2D6 metabolic contribution and a robust increase in serotonin levels in the rat frontal cortex.

Assessment of drug metabolism enzyme and transporter pharmacogenetics in drug discovery and early development: perspectives of the I-PWG

Genetic variants of drug metabolism enzymes and transporters can result in high pharmacokinetic and pharmacodynamic variability, unwanted characteristics of efficacious and safe drugs. Ideally, the contributions of these enzymes and transporters to drug disposition can be predicted from in vitro experiments and in silico modeling in discovery or early development, and then be utilized during clinical development. Recently, regulatory agencies have provided guidance on the preclinical investigation of pharmacogenetics, for application to clinical drug development. This white paper summarizes the results of an industry survey conducted by the Industry Pharmacogenomics Working Group on current practice and challenges with using in vitro systems and in silico models to understand pharmacogenetic causes of variability in drug disposition.

Impact of physiological, pathological and environmental factors on the expression and activity of human cytochrome P450 2D6 and implications in precision medicine

With only 1.3-4.3% in total hepatic CYP content, human CYP2D6 can metabolize more than 160 drugs. It is a highly polymorphic enzyme and subject to marked inhibition by a number of drugs, causing a large interindividual variability in drug clearance and drug response and drug-drug interactions. The expression and activity of CYP2D6 are regulated by a number of physiological, pathological and environmental factors at transcriptional, post-transcriptional, translational and epigenetic levels. DNA hypermethylation and histone modifications can repress the expression of CYP2D6. Hepatocyte nuclear factor-4α binds to a directly repeated element in the promoter of CYP2D6 and thus regulates the expression of CYP2D6. Small heterodimer partner represses hepatocyte nuclear factor-4α-mediated transactivation of CYP2D6. GW4064, a farnesoid X receptor agonist, decreases hepatic CYP2D6 expression and activity while increasing small heterodimer partner expression and its recruitment to the CYP2D6 promoter. The genotypes are key determinants of interindividual variability in CYP2D6 expression and activity. Recent genome-wide association studies have identified a large number of genes that can regulate CYP2D6. Pregnancy induces CYP2D6 via unknown mechanisms. Renal or liver diseases, smoking and alcohol use have minor to moderate effects only on CYP2D6 activity. Unlike CYP1 and 3 and other CYP2 members, CYP2D6 is resistant to typical inducers such as rifampin, phenobarbital and dexamethasone. Post-translational modifications such as phosphorylation of CYP2D6 Ser135 have been observed, but the functional impact is unknown. Further functional and validation studies are needed to clarify the role of nuclear receptors, epigenetic factors and other factors in the regulation of CYP2D6.

Metabolism and clinical pharmacokinetics of 2-methyl-n-(2'-(pyrrolidinyl-1-ylsulfonyl)-n-[1,1'-biphenyl]-4-yl)propran-1-amine: insights into monoamine oxidase- and CYP-mediated disposition by integration of in vitro ADME tools

1. In early discovery stages, 2-methyl-N-(2'-(pyrrolidinyl-1-ylsulfonyl)-[1,1'-biphenyl]-4-yl)propan-1-amine (PBPA) demonstrated monoamine oxidase A (MAO-A) and cytochrome P450 (CYP)-mediated clearance. While human liver microsomes predicted low CL(b) PBPA demonstrated a moderate CL(p)/F in humans. The plasma pharmacokinetic (PK) of PBPA was characterized by unexpected high inter-individual variability. Hence, a retrospective analysis was undertaken to understand the disposition processes of PBPA, by applying in vitro mechanistic tools. 2. The in vitro-to-in vivo of rat CL(b) of PBPA was calculated as similar to that of human, suggesting rat to be a better predictor of a MAO-A/CYP substrate, but not dog or monkey; this is consistent with differences in expression of MAO-A in rat, dog, monkey and human. Fraction metabolized (f(m)) of human MAO A (hMAO-A) (50%), CYP3A4 (8%), CYP3A5 (16%) and CYP2D6 (29%) was determined, in vitro. 3. While the fm of CYP3A5 was <50%, Michaelis-Menten kinetics demonstrated that it was a higher capacity pathway compared with MAO-A, 2D6 and 3A4. This was consistent with strong association of dose-normalized plasma C(max) and area under the plasma concentration time curve (AUC(0-tlast)) of PBPA with CYP3A5 genotype, but not with genotype of CYP2D6. 4. This investigation demonstrates the value of integrating in vitro mechanistic tools to gain comprehensive understanding of disposition properties of drug candidates, in a discovery paradigm and prior to the investment in clinical trials.

Pharmacogenomics of CYP3A: considerations for HIV treatment

The understanding of the cytochrome P450 3A SNP in antiretroviral therapy is important, because it is highly inducible, extremely polymorphic and metabolizes many of the drugs that are key components of highly active antiretroviral therapy regimens. This enzyme is prolific and promiscuous towards drug and xenobiotic substrate selection and it is also unpredictable among individuals, having a 5- to 20-fold variability in its ability to contribute to drug clearance. The importance of human CYP3A pharmacogenetics is also gaining attention in other established areas of pharmacotherapy as it may contribute to the goal of predicting efficacy and/or toxicity, specifically with the discovery of null allele CYP3A4*20. This review summarizes the current understanding, implications of genetic variation in the CYP3A enzymes, the central role of CYP3A in linking human genetics, the pharmacokinetics and resulting pharmacodynamic responses to certain antiretroviral drugs, and their eventual place in applied clinical pharmacotherapy.

A proposal for a pharmacokinetic interaction significance classification system (PISCS) based on predicted drug exposure changes and its potential application to alert classifications in product labelling

BACKGROUND AND OBJECTIVE

Pharmacokinetic drug-drug interactions (DDIs) are one of the major causes of adverse events in pharmacotherapy, and systematic prediction of the clinical relevance of DDIs is an issue of significant clinical importance. In a previous study, total exposure changes of many substrate drugs of cytochrome P450 (CYP) 3A4 caused by coadministration of inhibitor drugs were successfully predicted by using in vivo information. In order to exploit these predictions in daily pharmacotherapy, the clinical significance of the pharmacokinetic changes needs to be carefully evaluated. The aim of the present study was to construct a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered with pharmacokinetic changes in a systematic manner. Furthermore, the classifications proposed by PISCS were compared in a detailed manner with current alert classifications in the product labelling or the summary of product characteristics used in Japan, the US and the UK.

METHODS

A matrix table was composed by stratifying two basic parameters of the prediction: the contribution ratio of CYP3A4 to the oral clearance of substrates (CR), and the inhibition ratio of inhibitors (IR). The total exposure increase was estimated for each cell in the table by associating CR and IR values, and the cells were categorized into nine zones according to the magnitude of the exposure increase. Then, correspondences between the DDI significance and the zones were determined for each drug group considering the observed exposure changes and the current classification in the product labelling. Substrate drugs of CYP3A4 selected from three therapeutic groups, i.e. HMG-CoA reductase inhibitors (statins), calcium-channel antagonists/blockers (CCBs) and benzodiazepines (BZPs), were analysed as representative examples. The product labelling descriptions of drugs in Japan, US and UK were obtained from the websites of each regulatory body.

RESULTS

Among 220 combinations of drugs investigated, estimated exposure changes were more than 5-fold for 41 combinations in which ten combinations were not alerted in the product labelling at least in one country; these involved buspirone, nisoldipine and felodipine as substrates, and ketoconazole, voriconazole, telithromycin, clarithromycin and nefazodone as inhibitors. For those drug combinations, the alert classifications were anticipated as potentially inappropriate. In the current product labelling, many inter-country differences were also noted. Considering the relationships between previously observed exposure changes and the current alert classifications, the boundaries between 'contraindication' and 'warning/caution' were determined as a 7-fold exposure increase for statins and CCBs, and as a 4-fold increase for BZPs. PISCS clearly discriminated these drug combinations in accordance with the determined boundaries. Classifications by PISCS were expected to be valid even for future drugs because the classifications were made by zones, not by designating individual drugs.

CONCLUSION

The present analysis suggested that many current alert classifications were potentially inappropriate especially for drug combinations where pharmacokinetics had not been evaluated. It is expected that PISCS would contribute to constructing a leak-less alerting system for a broad range of pharmacokinetic DDIs. Further validation of PISCS is required in clinical studies with key drug combinations, and its extension to other CYP and metabolizing enzymes remains to be achieved.

Polymorphism of human cytochrome P450 enzymes and its clinical impact

Pharmacogenetics is the study of how interindividual variations in the DNA sequence of specific genes affect drug response. This article highlights current pharmacogenetic knowledge on important human drug-metabolizing cytochrome P450s (CYPs) to understand the large interindividual variability in drug clearance and responses in clinical practice. The human CYP superfamily contains 57 functional genes and 58 pseudogenes, with members of the 1, 2, and 3 families playing an important role in the metabolism of therapeutic drugs, other xenobiotics, and some endogenous compounds. Polymorphisms in the CYP family may have had the most impact on the fate of therapeutic drugs. CYP2D6, 2C19, and 2C9 polymorphisms account for the most frequent variations in phase I metabolism of drugs, since almost 80% of drugs in use today are metabolized by these enzymes. Approximately 5-14% of Caucasians, 0-5% Africans, and 0-1% of Asians lack CYP2D6 activity, and these individuals are known as poor metabolizers. CYP2C9 is another clinically significant enzyme that demonstrates multiple genetic variants with a potentially functional impact on the efficacy and adverse effects of drugs that are mainly eliminated by this enzyme. Studies into the CYP2C9 polymorphism have highlighted the importance of the CYP2C9*2 and *3 alleles. Extensive polymorphism also occurs in other CYP genes, such as CYP1A1, 2A6, 2A13, 2C8, 3A4, and 3A5. Since several of these CYPs (e.g., CYP1A1 and 1A2) play a role in the bioactivation of many procarcinogens, polymorphisms of these enzymes may contribute to the variable susceptibility to carcinogenesis. The distribution of the common variant alleles of CYP genes varies among different ethnic populations. Pharmacogenetics has the potential to achieve optimal quality use of medicines, and to improve the efficacy and safety of both prospective and currently available drugs. Further studies are warranted to explore the gene-dose, gene-concentration, and gene-response relationships for these important drug-metabolizing CYPs.

Effects of CYP2D6 status on harmaline metabolism, pharmacokinetics and pharmacodynamics, and a pharmacogenetics-based pharmacokinetic model

Harmaline is a beta-carboline alkaloid showing neuroprotective and neurotoxic properties. Our recent studies have revealed an important role for cytochrome P450 2D6 (CYP2D6) in harmaline O-demethylation. This study, therefore, aimed to delineate the effects of CYP2D6 phenotype/genotype on harmaline metabolism, pharmacokinetics (PK) and pharmacodynamics (PD), and to develop a pharmacogenetics mechanism-based compartmental PK model. In vitro kinetic studies on metabolite formation in human CYP2D6 extensive metabolizer (EM) and poor metabolizer (PM) hepatocytes indicated that harmaline O-demethylase activity (V(max)/K(m)) was about 9-fold higher in EM hepatocytes. Substrate depletion showed mono-exponential decay trait, and estimated in vitro harmaline clearance (CL(int), microL/min/10(6)cells) was significantly lower in PM hepatocytes (28.5) than EM hepatocytes (71.1). In vivo studies in CYP2D6-humanized and wild-type mouse models showed that wild-type mice were subjected to higher and longer exposure to harmaline (5 and 15mg/kg; i.v. and i.p.), and more severe hypothermic responses. The PK/PD data were nicely described by our pharmacogenetics-based PK model involving the clearance of drug by CYP2D6 (CL(CYP2D6)) and other mechanisms (CL(other)), and an indirect response PD model, respectively. Wild-type mice were also more sensitive to harmaline in marble-burying tests, as manifested by significantly lower ED(50) and steeper Hill slope. These findings suggest that distinct CYP2D6 status may cause considerable variations in harmaline metabolism, PK and PD. In addition, the pharmacogenetics-based PK model may be extended to define PK difference caused by other polymorphic drug-metabolizing enzyme in different populations.

Integrated in vitro analysis for the in vivo prediction of cytochrome P450-mediated drug-drug interactions

Unbound IC(50) (IC(50,u)) values of 15 drugs were determined in eight recombinantly expressed human cytochromes P450 (P450s) and human hepatocytes, and the data were used to simulate clinical area under the plasma concentration-time curve changes (deltaAUC) on coadministration with prototypic CYP2D6 substrates. Significant differences in IC(50,u) values between enzyme sources were observed for quinidine (0.02 microM in recombinant CYP2D6 versus 0.5 microM in hepatocytes) and propafenone (0.02 versus 4.1 microM). The relative contribution of individual P450s toward the oxidative metabolism of clinical probes desipramine, imipramine, tolterodine, propranolol, and metoprolol was estimated via determinations of intrinsic clearance using recombinant P450s (rP450s). Simulated deltaAUC were compared with those observed in vivo via the ratios of unbound inhibitor concentration at the entrance to the liver to inhibition constants determined against rP450s ([I](in,u)/K(i)) and incorporating parallel substrate elimination pathways. For this dataset, there were 20% false negatives (observed deltaAUC >or= 2, predicted deltaAUC < 2), 77% correct predictions, and 3% false positives. Thus, the [I](in,u)/K(i) approach appears relatively successful at estimating the degree of clinical interactions and can be incorporated into drug discovery strategies. Using a Simcyp ADME (absorption, metabolism, distribution, elimination) simulator (Simcyp Ltd., Sheffield, UK), there were 3% false negatives, 94% correct simulations, and 3% false positives. False-negative predictions were rationalized as a result of mechanism-based inhibition, production of inhibitory metabolites, and/or hepatic uptake. Integrating inhibition and reaction phenotyping data from automated rP450 screens have shown applicability to predict the occurrence and degree of in vivo drug-drug interactions, and such data may identify the clinical consequences for candidate drugs as both "perpetrators" and "victims" of P450-mediated interactions.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor.

WHAT THIS STUDY ADDS

Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions.

AIMS

The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques.

METHODS

The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP.

RESULTS

When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs.

CONCLUSIONS

The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.

Application of CYP3A4 in vitro data to predict clinical drug-drug interactions; predictions of compounds as objects of interaction

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

Numerous retrospective analyses have shown the utility of in vitro systems for predicting potential drug-drug interactions (DDIs). Prediction of DDIs from in vitro data is commonly obtained using estimates of enzyme K(i), inhibitor and substrate concentrations and absorption rate for substrate and inhibitor.

WHAT THIS STUDY ADDS

Using a generic approach for all test compounds, the findings from the current study showed the use of recombinant P450s provide a more robust in vitro measure of P450 contribution (fraction metabolized, f(m)) than that achieved when using chemical inhibitors in combination with human liver microsomes, for the prediction of potential CYP3A4 drug-drug interactions prior to clinical investigation. The current study supported the use of SIMCYP(R), a modelling and simulation software in utilizing the in vitro measures in the prediction of potential drug-drug interactions.

AIMS

The aim of this study was to explore and optimize the in vitro and in silico approaches used for predicting clinical DDIs. A data set containing clinical information on the interaction of 20 Pfizer compounds with ketoconazole was used to assess the success of the techniques.

METHODS

The study calculated the fraction and the rate of metabolism of 20 Pfizer compounds via each cytochrome P450. Two approaches were used to determine fraction metabolized (f(m)); 1) by measuring substrate loss in human liver microsomes (HLM) in the presence and absence of specific chemical inhibitors and 2) by measuring substrate loss in individual cDNA expressed P450s (also referred to as recombinant P450s (rhCYP)) The fractions metabolized via each CYP were used to predict the drug-drug interaction due to CYP3A4 inhibition by ketoconazole using the modelling and simulation software SIMCYP.

RESULTS

When in vitro data were generated using Gentest supersomes, 85% of predictions were within two-fold of the observed clinical interaction. Using PanVera baculosomes, 70% of predictions were predicted within two-fold. In contrast using chemical inhibitors the accuracy was lower, predicting only 37% of compounds within two-fold of the clinical value. Poorly predicted compounds were found to either be metabolically stable and/or have high microsomal protein binding. The use of equilibrium dialysis to generate accurate protein binding measurements was especially important for highly bound drugs.

CONCLUSIONS

The current study demonstrated that the use of rhCYPs with SIMCYP provides a robust in vitro system for predicting the likelihood and magnitude of changes in clinical exposure of compounds as a consequence of CYP3A4 inhibition by a concomitantly administered drug.