Different inhibitory effect of fluvoxamine on omeprazole metabolism between CYP2C19 genotypes

Assessment of omeprazole and famotidine effects on the pharmacokinetics of tacrolimus in patients following kidney transplant-randomized controlled trial

Tacrolimus is metabolized in the liver with the participation of the CYP3A4 and CYP3A5 enzymes. Proton pump inhibitors are used in kidney transplant patients to prevent duodenal and gastric ulcer disease due to glucocorticoids. Omeprazole, unlike famotidine, is a substrate and inhibitor of the enzymes CYP2C19, CYP3A4, CYP3A5. The aim of this study was to compare the impact of omeprazole and famotidine on the pharmacokinetics of tacrolimus. A randomized, non-blinded study involving 22 stabilized adult kidney transplant patients was conducted. Patients received the standard triple immunosuppression regimen and omeprazole 20 mg (n = 10) or famotidine 20 mg (n = 12). The study material consisted of blood samples in which tacrolimus concentrations were determined using the Chemiluminescent Microparticle Immuno Assay method. A single administration of omeprazole increased tacrolimus concentrations at 2 h (day 2) = 11.90 ± 1.59 ng/mL vs. 2 h (day 1 - no omeprazole administration) = 9.40 ± 0.79 ng/mL (p = 0.0443). AUC0-6 amounted to 63.07 ± 19.46 ng × h/mL (day 2) vs. 54.23 ± 10.48 ng × h/mL (day 1), (p = 0.0295). AUC2-6 amounted to 44.32 ± 11.51 ng × h/mL (day 2) vs. 38.68 ± 7.70 ng × h/mL (day 1), (p = 0.0130). Conversely, no significant changes in values of pharmacokinetic parameters were observed for famotidine. Omeprazole significantly increases blood exposure of tacrolimus. The administration of famotidine instead of omeprazole seems safer for patients following kidney transplantation. Clinical Trial Registration: clinicaltrials.gov, identifier NCT05061303.

Safety analysis of co-administering tacrolimus and omeprazole in renal transplant recipients - A review

Tacrolimus is a calcineurin inhibitor used to prevent rejection in allogenic solid organ transplant recipients, which is metabolized in the liver with cytochrome P450 isoforms 3A4 and 3A5 (CYP3A4, CYP3A5). In turn, proton pump inhibitors (PPIs), such as Omeprazole - a substrate and inhibitor of CYP2C19 and CYP3A4 enzymes - are administered to kidney transplant patients in order to prevent duodenal and gastric ulcer disease, associated with the glucocorticoid treatment. Simultaneous administration of both drugs in renal patients has the potential to trigger drug interactions. In fact, there are several mechanisms which may impact the pharmacokinetics of tacrolimus. Inhibition of the CYP2C19 isoform may suppress the metabolism of omeprazole, subsequently altering its metabolic pathway to be metabolized by the CYP3A4 enzyme in order to maintain adequate biotransformation. Therefore, the competition for CYP3A4 may affect the metabolism of tacrolimus and result in its increased plasma concentrations, as well as in adverse reactions. Another mechanism has been related to the genetic polymorphism of the CYP2C19 isoform. Since all these interactions may lead to dysfunctions of the transplanted kidney, it seems significant to eliminate their consequences, for instance via the administration of drugs which are neither substrates, nor inhibitors of the CYP3A4 enzyme. Finally, the nephrotoxic effect of omeprazole should also be accounted for. Bearing in mind the aforementioned observations, the aim of the presented paper was to review the available studies addressing the effect of omeprazole on the pharmacokinetics of tacrolimus.

Effect of nivasorexant (ACT-539313), a selective orexin-1-receptor antagonist, on multiple cytochrome P450 probe substrates in vitro and in vivo using a cocktail approach in healthy subjects

Nivasorexant, a selective orexin-1-receptor antagonist, has recently been assessed in the treatment of humans with binge-eating disorder. Herein, the inhibitory potential of nivasorexant on cytochromes P450 (CYPs) 2C9, 2C19, and 3A4 was evaluated. Human liver microsomes/recombinant CYP enzymes were evaluated in vitro. In vivo, a single-center, open-label, fixed-sequence study was performed in healthy adults to explore the effect of 100 mg nivasorexant administered twice daily (b.i.d.) on the pharmacokinetics (PK) of flurbiprofen (50 mg, CYP2C9), omeprazole (20 mg, CYP2C19), midazolam (2 mg, CYP3A4) making use of a cocktail approach. Plasma PK sampling was performed over 24 h on Day 1 (Cocktail alone), 8 (Cocktail + nivasorexant), and 15 (Cocktail + nivasorexant at steady state). Genotyping of subjects' CYPs was performed while safety and tolerability were also assessed. In vitro, nivasorexant inhibited CYP2C9, 2C19, and 3A4 in competitive inhibition assays with IC50 values of 8.6, 1.6, and 19-44 μM, respectively, while showing a significant time-dependent CYP2C19 inhibition. In 22 subjects, exposure to flurbiprofen, omeprazole, and midazolam was generally higher during concomitant single- (i.e., area under the plasma concentration-time curve [AUC] ratio increased by 1.04-, 2.05-, and 1.56-fold, respectively) and repeated-dose (i.e., AUC ratio increased by 1.47-, 6.84-, and 3.71-fold, respectively) nivasorexant administration compared with the cocktail substrates administered alone. The most frequently reported adverse event was somnolence. According to regulatory guidance, nivasorexant is classified as a moderate CYP2C19 and weak CYP3A4 inhibitor after 1 day and as a weak CYP2C9, strong CYP2C19, and moderate CYP3A4 inhibitor after 8 days of 100 mg b.i.d. administration. Clinicaltrials.gov ID: NCT05254548.

Novel models for the prediction of drug-gene interactions

INTRODUCTION

Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation of genetic preemptive testing into clinical practice, mathematical modeling can help to understand, quantify and predict the effects of DGIs in vivo. Moreover, modeling can contribute to optimize prospective clinical drug trial activities and to reduce DGI-related ADRs.

AREAS COVERED

Approaches and challenges of mechanistical DGI implementation and model parameterization are discussed for population pharmacokinetic and physiologically based pharmacokinetic models. The broad spectrum of published DGI models and their applications is presented, focusing on the investigation of DGI effects on pharmacology and model-based dose adaptations.

EXPERT OPINION

Mathematical modeling provides an opportunity to investigate complex DGI scenarios and can facilitate the development process of safe and efficient personalized dosing regimens. However, reliable DGI model input data from in vivo and in vitro measurements are crucial. For this, collaboration among pharmacometricians, laboratory scientists and clinicians is important to provide homogeneous datasets and unambiguous model parameters. For a broad adaptation of validated DGI models in clinical practice, interdisciplinary cooperation should be promoted and qualification toolchains must be established.

Verification of a cocktail approach for quantitative drug-drug interaction assessment: a comparative analysis between the results of a single drug and a cocktail drug

A cocktail approach is a method to comprehensively evaluate the activity of cytochrome P450 enzymes (CYPs) by co-administering multiple CYP substrates. This is the first report that compares the results from a cocktail study to a single substrate separate administration study (single study) with concomitant administration of CYP inducers/inhibitors. The validity of a cocktail study for use as a quantitative drug-drug interactions (DDIs) assessment was evaluated.We administered a cocktail drug (caffeine, losartan, omeprazole, dextromethorphan, midazolam) with rifampicin, cimetidine or fluvoxamine. A comparative analysis was performed between the results of a cocktail study and single studies. The results of single studies were obtained from a literature review and the trials of single substrate separate administration.A strong positive correlation of the AUC ratio of all drugs between single studies and the cocktail study was obtained. The ratio of AUC change of 12 combinations converged to 0.82-1.09, and 2 combinations ranged between 0.74-1.32.The differences in the degree of interaction between the single studies and cocktail study are acceptable to evaluate DDIs for almost all combinations. Our results indicate that a cocktail study is an adequate and quantitative evaluation method for DDIs.

Inhibition and induction of CYP enzymes in humans: an update

The cytochrome P450 (CYP) enzyme family is the most important enzyme system catalyzing the phase 1 metabolism of pharmaceuticals and other xenobiotics such as herbal remedies and toxic compounds in the environment. The inhibition and induction of CYPs are major mechanisms causing pharmacokinetic drug–drug interactions. This review presents a comprehensive update on the inhibitors and inducers of the specific CYP enzymes in humans. The focus is on the more recent human in vitro and in vivo findings since the publication of our previous review on this topic in 2008. In addition to the general presentation of inhibitory drugs and inducers of human CYP enzymes by drugs, herbal remedies, and toxic compounds, an in-depth view on tyrosine-kinase inhibitors and antiretroviral HIV medications as victims and perpetrators of drug–drug interactions is provided as examples of the current trends in the field. Also, a concise overview of the mechanisms of CYP induction is presented to aid the understanding of the induction phenomena.

Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions

Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.

Effects of the dietary inclusion of a probiotic or prebiotic on florfenicol pharmacokinetic profile in broiler chicken

We evaluated the effect of prebiotic or probiotic as feed additives on florfenicol kinetic in broilers feed. Unsexed two hundred, thirty-five-day-old broiler chickens, were put in four equal groups (n = 50). The first group was administrated florfenicol intravenous at 30 mg/kg body weight (BW) only once dosage without pre- or probiotic administration to determine the bioavailability. While, the second group was administrated florfenicol (intracrop routes; a dosage of 30 mg/kg BW for five progressive days) without pre- or probiotic co-administration. The third and the fourth groups were administrated the same dose of florfenicol (intracrop route) for five successive days, followed by 10 days of prebiotic or probiotic treatment respectively. The plasma florfenicol % was identified by high-pressure liquid chromatography (HPLC) after the first florfenicol administration (intravenous or intracrop routes) in all groups. Then, the residual levels of florfenicol were determined in liver, kidney and muscle tissues from the second, third and fourth groups which were exposed to florfenicol orally. Our results demonstrated that broilers pre-treated with prebiotic or probiotic significantly increased C_max , AUC_{0- t} , AUC_0-inf as well as AUMC values, while significant drop was recorded in V/F and CL/F. Prebiotic or probiotic influenced the cumulative effect of florfenicol in liver and kidney tissues of treated birds.

MGB Block ARMS Real-Time PCR for Diagnosis of CYP2C19 Mutation in a Chinese Population

Background:

CYP2C19 is an important genetic factor modulating clopidogrel dose requirement.

Objective:

Therefore, a simple and economic genotyping method for predicting the clopidogrel dose of patients would be useful in clinical applications.

Methods:

In this study, the MGB blocker ARMS real-time PCR contained two forward primers, two MGB blockers and a common reverse primer have been used for CYP2C19*2, *3 and *17 substitutions.

Results:

Results showed that heterozygotes and homozygotes of CYP2C19*2, *3 and *17 could be distinguished by the MGB blocker ARMS real-time PCR successfully. In the Chinese population, patients with allele frequencies of CYP2C19*2, *3, and *17 are 18.43%, 3.03% and 0.76%, respectively.

Conclusion:

This study indicates that the MGB blocker ARMS real-time PCR will be a simple, economical method for the rapid detection of SNPs in CYP2C19.

Effect of co-administered inducer or inhibitor on omeprazole pharmacokinetics based on CYP2C19 genotype

Polymorphisms of cytochrome P450 (CYP) enzymes can affect enzymatic activity, drug metabolism and drug interactions. Although the potential for drug interactions is especially important when co-administering drugs with strong inductive or inhibitory potential towards drug-metabolizing enzymes, the relationship between CYP genotypes and the extent of the inductive or inhibitory effects remain poorly understood. We investigated the effects of rifampicin (inductive) and fluvoxamine (inhibitory) on metabolism of omeprazole and CYP2C19 enzymatic activity in 19 healthy Japanese subjects. Pharmacokinetic analyses of the CYP2C19 probe drug, omeprazole, were performed before and after rifampicin or fluvoxamine administration. The allele frequencies of the CYP2C19*1, CYP2C19*2 and CYP2C19*3 genotypes were 65.8%, 26.3% and 7.9%, respectively. Subjects with the CYP2C19*1 allele displayed higher levels of omeprazole metabolism than those without the CYP2C19*1 allele. Rifampicin increased omeprazole metabolism in all subjects irrespective of genotype, which suggested that CYP2C19 enzymatic activity was induced by rifampicin administration for all genotypes. Conversely, while fluvoxamine reduced omeprazole metabolism in subjects carrying the CYP2C19*1 allele, it had no impact on omeprazole pharmacokinetics in subjects without this allele. The genotyping of CYP2C19 may be useful for predicting drug interactions with metabolic inhibitors.

Complex Drug-Drug-Gene-Disease Interactions Involving Cytochromes P450: Systematic Review of Published Case Reports and Clinical Perspectives

Drug pharmacokinetics (PK) is influenced by multiple intrinsic and extrinsic factors, among which concomitant medications are responsible for drug-drug interactions (DDIs) that may have a clinical relevance, resulting in adverse drug reactions or reduced efficacy. The addition of intrinsic factors affecting cytochromes P450 (CYPs) activity and/or expression, such as genetic polymorphisms and diseases, may potentiate the impact and clinical relevance of DDIs. In addition, greater variability in drug levels and exposures has been observed when such intrinsic factors are present in addition to concomitant medications perpetrating DDIs. This variability results in poor predictability of DDIs and potentially dramatic clinical consequences. The present review illustrates the issue of complex DDIs using systematically searched published case reports of DDIs involving genetic polymorphisms, renal impairment, cirrhosis, and/or inflammation. Current knowledge on the impact of each of these factors on drug exposure and DDIs is summarized and future perspectives for the management of such complex DDIs in clinical practice are discussed, including the use of advanced Computerized Physician Order Entry (CPOE) systems, the development of model-based dose optimization strategies, and the education of healthcare professionals with respect to personalized medicine.

Direct and quantitative evaluation of the major human CYP contribution (fmCYP) to drug clearance using the in vitro Silensomes™ model

1. We have applied the concept of using MBIs to produce CYP-Silensomes to quantify the contribution of the major CYPs to drug metabolism (fmCYP). 2. The target CYPs were extensively and selectivity inhibited by the selected MBIs, while non-target CYPs were inhibited by less than 20% of the homologous control activities. Only CYP2D6-Silensomes exhibited a CYP2B6 inhibition that could be easily and efficiently encountered by subtracting the fm_CYP2B6 measured using CYP2B6-Silensomes to adjust the fm_CYP2D6. 3. To validate the use of a panel of 6 CYP-Silensomes, we showed that the fmCYP values of mono- and multi-CYP metabolised drugs were well predicted, with 70% within ± 15% accuracy. Moreover, the correlation with observed fmCYP values was higher than that for rhCYPs, which were run in parallel using the same drugs (<45% within ±15% accuracy). Moreover, the choice of the RAF substrate in rhCYP predictions was shown to affect the accuracy of the fmCYP measurement. 4. These results support the use of CYP1A2-, CYP2B6-, CYP2C8-, CYP2C9-, CYP2D6 and CYP3A4-Silensomes to accurately predict fmCYP values during the in vitro enzyme phenotyping assays in early, as well as in development, phases of drug development.

Translational High-Dimensional Drug Interaction Discovery and Validation Using Health Record Databases and Pharmacokinetics Models

Polypharmacy increases the risk of drug-drug interactions (DDIs). Combining epidemiological studies with pharmacokinetic modeling, we detected and evaluated high-dimensional DDIs among 30 frequent drugs. Multidrug combinations that increased the risk of myopathy were identified in the US Food and Drug Administration Adverse Event Reporting System (FAERS) and electronic medical record (EMR) databases by a mixture drug-count response model. CYP450 inhibition was estimated among the 30 drugs in the presence of 1 to 4 inhibitors using in vitro / in vivo extrapolation. Twenty-eight three-way and 43 four-way DDIs had significant myopathy risk in both databases and predicted increases in the area under the concentration-time curve ratio (AUCR) >2-fold. The high-dimensional DDI of omeprazole, fluconazole, and clonidine was associated with a 6.41-fold (FAERS) and 18.46-fold (EMR) increased risk of myopathy local false discovery rate (<0.005); the AUCR of omeprazole in this combination was 9.35. The combination of health record informatics and pharmacokinetic modeling is a powerful translational approach to detect high-dimensional DDIs.

Mass balance and metabolism of Z-215, a novel proton pump inhibitor, in healthy volunteers

The human mass balance of [¹⁴C]Z-215, a novel proton pump inhibitor, was characterised in six healthy male volunteers following single oral administration of [¹⁴C]Z-215 (20 mg, 3.7 MBq) to determine the elimination pathway of Z-215 and the distribution of its metabolites in plasma, urine, and faeces (NCT02618629). [¹⁴C]Z-215 was rapidly absorbed, with a C_max of 434 ng/mL at 0.38 h for Z-215 and 732 ng eq./mL at 0.5 h for total radioactivity. Means of 59.61% and 31.36% of the administered radioactive dose were excreted in urine and faeces, respectively, within 168 h post-dose. The majority of the dose was recovered within 24 h in urine and 96 h in faeces. Unchanged Z-215 was excreted in urine at trace levels but was not detected in faeces. The main components in plasma were Z-215 and Z-215 sulphone, accounting for 29.8% and 13.3% of the total circulating radioactivity, respectively. Additionally, Z-215 was metabolised through oxidation, reduction and conjugation. Our in vitro Z-215 metabolism study showed that the major isozyme contributing to the oxidation of Z-215, including the formation of Z-215 sulphone, was CYP3A4. In conclusion, Z-215 is well absorbed in humans and primarily eliminated via metabolism, where CYP3A4 plays an important role.

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

Pharmacogenomics of the cytochrome P450 2C family: impacts of amino acid variations on drug metabolism

Pharmacogenomics investigates DNA and RNA variations in the human genome related to drug responses. Cytochrome P450 (CYP) is a supergene family of drug-metabolizing enzymes responsible for the metabolism of approximately 90% of human drugs. Among the major CYP isoforms, the CYP2C subfamily is of clinical significance because it metabolizes approximately 20% of clinically administrated drugs and represents several variant alleles leading to adverse drug reactions or altering drug efficacy. Here, we review recent progress on understanding the interindividual variability of the CYP2C members and the functional and clinical impact on drug metabolism. We summarize current advances in the molecular modeling of CYP2C polymorphisms and discuss the structural bases and molecular mechanisms of amino acid variants of CYP2C members that affect drug metabolism.

Simulation of Metabolic Drug-Drug Interactions Perpetrated by Fluvoxamine Using Hybridized Two-Compartment Hepatic Drug-Pool-Based Tube Modeling and Estimation of In Vivo Inhibition Constants

Co-administration of fluvoxamine (FLV) (perpetrator) and ramelteon (victim, high-clearance CYP1A2 substrate) reportedly showed a 130-fold increase in the area under blood-ramelteon-levels curve (AUCR), which is unpredictable by any method assuming the traditional well-stirred hepatic extraction (Eh ) model. Thus, in order to predict this drug interaction (DDI), a mathematical method that allows simulation of dynamic changes in blood victim levels in response to metabolic inhibition by a perpetrator, without the use of any specialized tools, was derived using hybridized two-compartment hepatic drug-pool-based tube modeling. Using this method, the ramelteon-victimized DDI could be simulated in comparison with other victim DDIs, assuming a consistent FLV dosing regimen. Despite large differences in AUCRs, CYP1A2 or CYP2C19 substrate-victimized DDIs resulted in equivalent inhibition constants (Ki , around 3 nM) and net enzymatic inhibitory activities calculated by eliminating hepatic availability increases for victims. Thus, the unusually large ramelteon DDI could be attributed to the Eh of ramelteon itself. This DDI risk could also be accurately predicted from Ki s estimated in the other CYP1A2 or CYP2C19-substrate interactions. Meanwhile, dynamic changes in blood perpetrator levels were demonstrated to have a small effect on DDI, thus suggesting the usefulness of a tube-based static method for DDI prediction.

Pharmacokinetic drug interaction profiles of proton pump inhibitors: an update

Proton pump inhibitors (PPIs) are used extensively for the treatment of gastric acid-related disorders, often over the long term, which raises the potential for clinically significant drug interactions in patients receiving concomitant medications. These drug–drug interactions have been previously reviewed. However, the current knowledge is likely to have advanced, so a thorough review of the literature published since 2006 was conducted. This identified new studies of drug interactions that are modulated by gastric pH. These studies showed the effect of a PPI-induced increase in intragastric pH on mycophenolate mofetil pharmacokinetics, which were characterised by a decrease in the maximum exposure and availability of mycophenolic acid, at least at early time points. Post-2006 data were also available outlining the altered pharmacokinetics of protease inhibitors with concomitant PPI exposure. New data for the more recently marketed dexlansoprazole suggest it has no impact on the pharmacokinetics of diazepam, phenytoin, theophylline and warfarin. The CYP2C19-mediated interaction that seems to exist between clopidogrel and omeprazole or esomeprazole has been shown to be clinically important in research published since the 2006 review; this effect is not seen as a class effect of PPIs. Finally, data suggest that coadministration of PPIs with methotrexate may affect methotrexate pharmacokinetics, although the mechanism of interaction is not well understood. As was shown in the previous review, individual PPIs differ in their propensities to interact with other drugs and the extent to which their interaction profiles have been defined. The interaction profiles of omeprazole and pantoprazole sodium (pantoprazole-Na) have been studied most extensively. Several studies have shown that omeprazole carries a considerable potential for drug interactions because of its high affinity for CYP2C19 and moderate affinity for CYP3A4. In contrast, pantoprazole-Na appears to have lower potential for interactions with other medications. Lansoprazole and rabeprazole also seem to have a weaker potential for interactions than omeprazole, although their interaction profiles, along with those of esomeprazole and dexlansoprazole, have been less extensively investigated. Only a few drug interactions involving PPIs are of clinical significance. Nonetheless, the potential for drug interactions should be considered when choosing a PPI to manage gastric acid-related disorders. This is particularly relevant for elderly patients taking multiple medications, or for those receiving a concomitant medication with a narrow therapeutic index.

Pharmacokinetic interaction between fluoxetine and omeprazole in healthy male volunteers: a prospective pilot study

BACKGROUND

Fluoxetine is an inhibitor of the main metabolizing enzymes (cytochrome P450 [CYP] 2C19 and CYP3A4) of omeprazole and thus might influence that drug's pharmacokinetics. The changes in omeprazole's pharmacokinetics may have clinical significance concerning efficacy and tolerability of the treatment.

OBJECTIVE

The aim of this study was to assess the pharmacokinetic interaction of fluoxetine with omeprazole in healthy volunteers.

METHODS

The study enrolled healthy adult men and consisted of 2 periods. In the first period, all subjects received a single 40-mg dose of omeprazole. This was followed by an 8-day period during which fluoxetine monotherapy (60 mg/d) was administered as a single oral daily dose. At the end of those 8 days, the subjects were administered a 40-mg dose of omeprazole with a 60-mg dose of fluoxetine. Plasma concentrations of omeprazole were determined at 0.5, 1, 1.33, 1.66, 2, 2.5, 3, 4, 5, 6, 7, 8, 10, and 12 hour(s) after study drug administration. Omeprazole plasma concentrations were determined by a validated HPLC method. Pharmacokinetic parameters of omep-razole were calculated using noncompartmental analysis. Adverse events were assessed throughout the study duration.

RESULTS

Eighteen healthy male volunteers (mean [SD] age, 22.11 [2.52] years [range, 18-26 years]; body mass index, 23.34 [2.31] kg/m(2) [range, 19.1-27.1 kg/m(2)]) were enrolled and completed the study. In the 2 periods of treatment, the mean Cmax of omeprazole was 730.8 ng/mL (omeprazole monotherapy) and 1725.5 ng/mL (combination treatment with fluoxetine). The observed AUC0-∞ was 1453.3 and 5072.5 ng/mL/h and AUC0-t was 1465.0 and 5185.3 ng/mL/h, respectively. The Tmax was 1.30 and 1.63 hours and the elimination rate constant was 0.753 and 0.482 hr(-1). The t½ was 0.96 and 1.47 hours, whereas the mean residence time was 2.33 and 3.35 hours, respectively. Statistically significant differences were observed for all parameters between periods 1 and 2 (all, P < 0.001).

CONCLUSION

The data found in this prospective pilot study suggest a pharmacokinetic interaction between fluoxetine and omeprazole in these healthy volunteers, but its relevance has to be confirmed.

Inhibition of baicalin on metabolism of phenacetin, a probe of CYP1A2, in human liver microsomes and in rats

Baicalin has been used as mainly bioactive constituent of about 100 kinds of traditional Chinese medicines in Chinese pharmacopoeia. The effect of baicalin on cytochrome P450 should be paid more attention because baicalin was used widely. The aim of this study was to investigate whether baicalin could inhibit CYP1A2 in pooled human liver microsomes (HLMs) and in rats in vivo and the gene polymorphisms could affect inter-individual variation in IC50 in 28 human livers. Phenacetin was used as probe of CYP1A2. Kinetic parameter of CYP1A2 and IC50 of baicalin on CYP1A2 to each sample were measured and the common CYP1A2 polymorphisms (-3860G>A and -163C>A) were genotyped. The results showed that baicalin exhibited a mixed-type inhibition in pooled HLMs, with a Ki value of 25.4 µM. There was substantial variation in Km, Vmax, CLint of CYP1A2 and IC50 of baicalin on CYP1A2 (3∼10-fold). The range was from 26.6 to 114.8 µM for Km, from 333 to 1330 pmol·min(-1)·mg(-1)protein for Vmax and from 3.8 to 45.3 µL·min(-1)·mg(-1) protein for CLint in HLMs (n = 28). The Mean (range) value of IC50 in 28 HLMs was 36.3 (18.9 to 56.1) µM. The genotypes of -3860G>A and -163C>A had no significant effect on the inhibition of baicalin on CYP1A2. The animal experiment results showed that baicalin (450 mg/kg, i.v.) significantly decreased the Cmax and CL of phenacetin, and increased C(60 min), t1/2, Vd and AUC (P<0.05). There were significant correlations between percentage of control in C(60 min), t1/2, CL, AUC of phenacetin and Cmax of baicalin in 11 rats (P<0.05). Protein binding experiments in vitro showed that baicalin (0-2000 mg/L) increased the unbound phenacetin from 14.5% to 28.3%. In conclusion, baicalin can inhibit the activity of CYP1A2 in HLMs and exhibit large inter-individual variation that has no relationship with gene polymorphism. Baicalin can change the pharmacokinetics of phenacetin in rats.

Impact of genetic polymorphism on drug-drug interactions mediated by cytochromes: a general approach

Currently, quantitative prediction of the impact of genetic polymorphism and drug-drug interactions mediated by cytochromes, based on in vivo data, is made by two separate methods and restricted to a single cytochrome. We propose a unified approach for describing the combined impact of drug-drug interactions and genetic polymorphism on drug exposure. It relies on in vivo data and uses the following three characteristic parameters: one for the victim drug, one for the interacting drug, and another for the genotype. These parameters are known for a wide range of drugs and genotypes. The metrics of interest are the ratio of victim drug area under the curve (AUC) in patients with genetic variants taking both drugs, to the AUC in patients with either variant or wild-type genotype taking the victim drug alone. The approach was evaluated by external validation, comparing predicted and observed AUC ratios found in the literature. Data were found for 22 substrates, 30 interacting drugs, and 38 substrate-interacting drug couples. The mean prediction error of AUC ratios was 0.02, and the mean prediction absolute error was 0.38 and 1.34, respectively. The model may be used to predict the variations in exposure resulting from a number of drug-drug-genotype combinations. The proposed approach will help (1) to identify comedications and population at risk, (2) to adapt dosing regimens, and (3) to prioritize the clinical pharmacokinetic studies to be done.

Impact of the CYP2C8 *3 polymorphism on the drug-drug interaction between gemfibrozil and pioglitazone

AIM

The objective of this study was to determine the extent to which the CYP2C8*3 allele influences pharmacokinetic variability in the drug-drug interaction between gemfibrozil (CYP2C8 inhibitor) and pioglitazone (CYP2C8 substrate).

METHODS

In this randomized, two phase crossover study, 30 healthy Caucasian subjects were enrolled based on CYP2C8*3 genotype (n = 15, CYP2C8*1/*1; n = 15, CYP2C8*3 carriers). Subjects received a single 15 mg dose of pioglitazone or gemfibrozil 600 mg every 12 h for 4 days with a single 15 mg dose of pioglitazone administered on the morning of day 3. A 48 h pharmacokinetic study followed each pioglitazone dose and the study phases were separated by a 14 day washout period.

RESULTS

Gemfibrozil significantly increased mean pioglitazone AUC(0,∞) by 4.3-fold (P < 0.001) and there was interindividual variability in the magnitude of this interaction (range, 1.8- to 12.1-fold). When pioglitazone was administered alone, the mean AUC(0,∞) was 29.7% lower (P = 0.01) in CYP2C8*3 carriers compared with CYP2C8*1 homozygotes. The relative change in pioglitazone plasma exposure following gemfibrozil administration was significantly influenced by CYP2C8 genotype. Specifically, CYP2C8*3 carriers had a 5.2-fold mean increase in pioglitazone AUC(0,∞) compared with a 3.3-fold mean increase in CYP2C8*1 homozygotes (P = 0.02).

CONCLUSION

CYP2C8*3 is associated with decreased pioglitazone plasma exposure in vivo and significantly influences the pharmacokinetic magnitude of the gemfibrozil-pioglitazone drug-drug interaction. Additional studies are needed to evaluate the impact of CYP2C8 genetics on the pharmacokinetics of other CYP2C8-mediated drug-drug interactions.

How pre-marketing data can be used for predicting the weight of drug interactions in clinical practice

Unexpected drug interactions have led to the withdrawal of many drugs, raising concern about the gap between what is known at the time of approval and the risk of serious effects in the longer term, particularly in high-risk populations generally excluded from drug development. This is because the majority of drug interaction studies are done using in vitro methods, or in healthy young volunteers who may not reflect the complexity of patients, and the settings in which the drug will be used in clinical practice. Pre-marketing interaction studies should therefore be designed to make information easily accessible and clinically transferable. They should be adequate in terms of sample size, population, comorbidity, phenotyping and/or genotyping, end-points and outcome measures, and conducted in conditions of dose, route and timing of co-administration that reproduce the proposed therapeutic indications of the new drug. Although young volunteers have the advantage of minimizing some confounding effects introduced by diseases or polypharmacy, patients drawn from populations for whom the drug is intended would be more relevant and accurate, providing the studies are feasible and safe.

The (R)-omeprazole hydroxylation index reflects CYP2C19 activity in healthy Japanese volunteers

PURPOSE

Omeprazole has (R)- and (S)-enantiomers, which exhibit different pharmacokinetics (PK) among patients with cytochrome P450 (CYP) 2C19 genotype groups. The aim of this study was to investigate whether the 1-point, 4-h postdose (R)-omeprazole hydroxylation index (HI) of racemic omeprazole reflects the three CYP2C19 genotype groups in Japanese individuals.

METHODS

Ninety healthy Japanese individuals were enrolled and classified into the three different CYP2C19 genotype groups: homozygous extensive metabolizers (hmEMs; n = 34), heterozygous EMs (htEMs; n = 44), and poor metabolizers (PMs; n = 12). Blood samples were drawn 4 h after the intake of an oral dose of omeprazole 40 mg, and plasma levels of omeprazole and its metabolites were analyzed by high-performance liquid chromatography (HPLC) using a chiral column.

RESULTS

Mean plasma concentrations of (R)- and (S)-omeprazole in PMs were significantly higher than those in hmEMs and htEMs, and similar results were obtained in the case of omeprazole sulfone. Additionally, there was a significant difference in plasma concentrations of (R)-5-hydroxyomeprazole among CYP2C19 genotype groups, whereas no significant differences were observed in that of (S)-5-hydroxyomeprazole. Similarly, (R)-omeprazole HI in hmEMs, htEMs, and PMs were 5.6, 3.1, and 0.3, respectively, which were significantly different, but no significant difference was present in the (S)-omeprazole HI.

CONCLUSION

Our findings demonstrate that (R)-omeprazole HI correlated better with CYP2C19 genotype groups than racemic-omeprazole HI, and these results may be useful for classification among patients in CYP2C19 genotype groups prior to omeprazole treatment.

In vivo quantitative prediction of the effect of gene polymorphisms and drug interactions on drug exposure for CYP2C19 substrates

We present a unified quantitative approach to predict the in vivo alteration in drug exposure caused by either cytochrome P450 (CYP) gene polymorphisms or CYP-mediated drug-drug interactions (DDI). An application to drugs metabolized by CYP2C19 is presented. The metrics used is the ratio of altered drug area under the curve (AUC) to the AUC in extensive metabolizers with no mutation or no interaction. Data from 42 pharmacokinetic studies performed in CYP2C19 genetic subgroups and 18 DDI studies were used to estimate model parameters and predicted AUC ratios by using Bayesian approach. Pharmacogenetic information was used to estimate a parameter of the model which was then used to predict DDI. The method adequately predicted the AUC ratios published in the literature, with mean errors of -0.15 and -0.62 and mean absolute errors of 0.62 and 1.05 for genotype and DDI data, respectively. The approach provides quantitative prediction of the effect of five genotype variants and 10 inhibitors on the exposure to 25 CYP2C19 substrates, including a number of unobserved cases. A quantitative approach for predicting the effect of gene polymorphisms and drug interactions on drug exposure has been successfully applied for CYP2C19 substrates. This study shows that pharmacogenetic information can be used to predict DDI. This may have important implications for the development of personalized medicine and drug development.

Importance of multi-p450 inhibition in drug-drug interactions: evaluation of incidence, inhibition magnitude, and prediction from in vitro data

Drugs that are mainly cleared by a single enzyme are considered more sensitive to drug-drug interactions (DDIs) than drugs cleared by multiple pathways. However, whether this is true when a drug cleared by multiple pathways is coadministered with an inhibitor of multiple P450 enzymes (multi-P450 inhibition) is not known. Mathematically, simultaneous equipotent inhibition of two elimination pathways that each contribute half of the drug clearance is equal to equipotent inhibition of a single pathway that clears the drug. However, simultaneous strong or moderate inhibition of two pathways by a single inhibitor is perceived as an unlikely scenario. The aim of this study was (i) to identify P450 inhibitors currently in clinical use that can inhibit more than one clearance pathway of an object drug in vivo and (ii) to evaluate the magnitude and predictability of DDIs caused by these multi-P450 inhibitors. Multi-P450 inhibitors were identified using the Metabolism and Transport Drug Interaction Database. A total of 38 multi-P450 inhibitors, defined as inhibitors that increased the AUC or decreased the clearance of probes of two or more P450s, were identified. Seventeen (45%) multi-P450 inhibitors were strong inhibitors of at least one P450, and an additional 12 (32%) were moderate inhibitors of one or more P450s. Only one inhibitor (fluvoxamine) was a strong inhibitor of more than one enzyme. Fifteen of the multi-P450 inhibitors also inhibit drug transporters in vivo, but such data are lacking on many of the inhibitors. Inhibition of multiple P450 enzymes by a single inhibitor resulted in significant (>2-fold) clinical DDIs with drugs that are cleared by multiple pathways such as imipramine and diazepam, while strong P450 inhibitors resulted in only weak DDIs with these object drugs. The magnitude of the DDIs between multi-P450 inhibitors and diazepam, imipramine, and omeprazole could be predicted using in vitro data with similar accuracy as probe substrate studies with the same inhibitors. The results of this study suggest that inhibition of multiple clearance pathways in vivo is clinically relevant, and the risk of DDIs with object drugs may be best evaluated in studies using multi-P450 inhibitors.

Influence of SLCO1B1 polymorphisms on the drug-drug interaction between darunavir/ritonavir and pravastatin

The authors investigated whether SLCO1B1 polymorphisms contribute to variability in pravastatin pharmacokinetics when pravastatin is administered alone versus with darunavir/ritonavir. HIV-negative healthy participants were prospectively enrolled on the basis of SLCO1B1 diplotype: group 1 (*1A/*1A, n = 9); group 2 (*1A/*1B, n = 10; or *1B/*1B, n = 2); and group 3 (*1A/*15, n = 1; *1B/*15, n = 5; or *1B/*17, n = 1). Participants received pravastatin (40 mg) daily on days 1 through 4, washout on days 5 through 11, darunavir/ritonavir (600/100 mg) twice daily on days 12 through 18, with pravastatin 40 mg added back on days 15 through 18. Pharmacokinetic studies were conducted on day 4 (pravastatin alone) and day 18 (pravastatin + darunavir/ritonavir). Pravastatin area under the plasma concentration-time curve (AUC(tau)) was 21% higher during administration with darunavir/ritonavir compared with pravastatin alone; however, this difference was not statistically significant (P = .11). Group 3 variants had 96% higher pravastatin AUC(tau) on day 4 and 113% higher pravastatin AUC(tau) on day 18 compared with group 1. The relative change in pravastatin pharmacokinetics was largest in group 3 but did not differ significantly between diplotype groups. In sum, the influence of SLCO1B1*15 and *17 haplotypes on pravastatin pharmacokinetics was maintained in the presence of darunavir/ritonavir. Because OATP1B1 inhibition would be expected to be greater in carriers of normal or high-functioning SLCO1B1 haplotypes, these findings suggest that darunavir/ritonavir is not a potent inhibitor of OATP1B1-mediated pravastatin transport in vivo.

Impact of CYP2C19 variant genotypes on clinical efficacy of antiplatelet treatment with clopidogrel: systematic review and meta-analysis

OBJECTIVE

To evaluate the accumulated information from genetic association studies investigating the impact of variants of the cytochrome P450 (CYP) 2C19 genotype on the clinical efficacy of clopidogrel.

DESIGN

Systematic review and meta-analysis with a structured search algorithm and prespecified eligibility criteria for retrieval of relevant studies; dominant genetic model assumptions and quantitative methods for calculating summary effect estimates from study level odds ratios; systematic assessment of bias within and between studies; and grading of the cumulative evidence by consensus criteria.

DATA SOURCES

Medline, Embase, the Cochrane Library, online databases, contents pages and bibliographies of general medical, cardiovascular, pharmacological, and genetic journals. Eligibility criteria for selecting studies Original full length reports assessing the cumulative incidence of major adverse cardiovascular events or stent thrombosis over a follow-up period of at least a month in association with carrier status for the loss of function or gain of function CYP2C19 allele in adult patients with coronary artery disease and a clinical presentation of acute coronary syndrome or stable angina pectoris who were taking clopidogrel.

RESULTS

15 studies met the inclusion criteria. The random effects summary odds ratio for stent thrombosis in carriers of at least one CYP2C19 loss of function allele versus non-carriers combining nine studies was 1.77 (95% confidence interval 1.31 to 2.40; P < 0.001). This nominally significant odds ratio was subject to considerable bias across the studies (small study effect bias and replication diversity). The adjustment for these quality modifiers tended to abolish the association. The corresponding random effects summary odds ratio of major adverse cardiovascular events for 12 studies combined was 1.11 (0.89 to 1.39; P = 0.36). The random effects summary odds ratio of stent thrombosis in carriers versus non-carriers of at least one CYP2C19*17 gain of function allele for three studies combined was 0.99 (0.60 to 1.62; P = 0.96), and the corresponding odds ratio of major adverse cardiovascular events in five studies was 0.93 (0.75 to 1.14; P = 0.48). The overall quality of epidemiological evidence was graded as low, which excludes reliable clinical assessments.

CONCLUSIONS

Accumulated information from genetic association studies does not indicate a substantial or consistent influence of CYP2C19 gene polymorphisms on the clinical efficacy of clopidogrel. The current evidence does not support the use of individualised antiplatelet regimens guided by CYP2C19 genotype.

Genetic polymorphisms of cytochrome P450 enzymes and antidepressant metabolism

INTRODUCTION

The cytochrome P450 (CYP) enzymes are the major enzymes responsible for Phase I reactions in the metabolism of several substances, including antidepressant medications. Thus, it has been hypothesized that variants in the CYP network may influence antidepressant efficacy and safety. Nonetheless, data on this field are still contradictory. The authors aim to give an overview of the published studies analyzing the influence of CYP highly polymorphic loci on antidepressant treatment in order to translate the acquired knowledge to a clinical level.

AREAS COVERED

The authors collected and compared experimental works and reviews published from the 1980s to the present and included in the Medline database. The included studies pertain to the effects of CYP gene polymorphisms on antidepressant pharmacokinetic parameters and clinical outcomes (response and drug-related adverse effects), with a focus on applications in clinical practice. The authors focused mainly on in vivo studies in humans (patients or healthy volunteers).

EXPERT OPINION

Great variability in antidepressant metabolism among individuals has been demonstrated. Thus, with the current interest in individualized medicine, several genetic tests to detect CYP variants have been produced. They provide a potentially useful way to anticipate some clinical outcomes of antidepressant treatment, although they will only be extensively used in clinical practice if precise and specific treatment options and guidelines based on genetic tests can be provided.

Effects of diltiazem on pharmacokinetics of tacrolimus in relation to CYP3A5 genotype status in renal recipients: from retrospective to prospective

The impact of CYP3A5*3, a CYP3A5 nonexpresser genotype, on inhibitory effects of diltiazem on tacrolimus metabolism has not been assessed. In retrospective study, when coadministered with diltiazem, mean increments in dose-adjusted C(0D7), C(max) and AUC(0-12 h) for tacrolimus were larger in CYP3A5 expressers than in CYP3A5 nonexpressers (48.7 vs 3.7%, 31.7 vs 17.2% and 38.2 vs 18.5%, respectively). Subsequently, a prospective study was carried out, patients were randomized to algorithm-predicted dosing or standard dosing. For CYP3A5 expressers, an algorithm guided by CYP3A5 and diltiazem significantly reduced tacrolimus maintenance dosage (P=0.009) and improved the accuracy of tacrolimus initial dose, resulting in reduction in out-of-range C(0) after initial dose (P=0.002) and dose adjustments (P=0.004). However, for CYP3A5 nonexpressers, primary end points were not achieved, and tacrolimus-sparing effect of diltiazem was not remarkable. Our study results show that CYP3A5 genotype-guided tacrolimus-diltiazem combination is a promising therapy in renal transplant recipients in the early postoperative stage.

Influence of the genetic polymorphisms in the 5' flanking and exonic regions of CYP2C19 on proguanil oxidation

CYP2C19 is a polymorphic enzyme which metabolizes several clinically important drugs including proguanil. Variation in the 5' regulatory region may influence CYP2C19 activity. This study evaluates the relationship between proguanil metabolic ratio and genetic variations of CYP2C19 in a South Indian population. Fifty unrelated healthy subjects were genotyped for CYP2C19 (*)2 and (*)3 alleles and the 5' flanking region of CYP2C19 was sequenced. Plasma concentrations of proguanil and cycloguanil were estimated by reverse phase HPLC after single oral doses (200 mg) of proguanil. In silico docking analysis of transcription factors binding to its sites in CYP2C19 5' regulatory region was performed. The mean metabolic ratios (proguanil/cycloguanil) were highest in (*)1/(*)2 or (*)1/(*)3 subjects and in (*)2/(*)2 or (*)2/(*)3 as compared to (*)1/(*)1 subjects. Subjects with promoter region variation -98T>C showed decrease in the metabolic ratios irrespective of other variation, which may explain the deviation from the genotype-phenotype association of CYP2C19. In silico analysis predicted alteration in the interaction of transcription factors to their binding sites in the presence of variant alleles. The results of this study would be useful in predicting interindividual differences in the metabolism of substrates of CYP2C19.

Influence of CYP2C19 on the relationship between pharmacokinetics and intragastric pH of omeprazole administered by successive intravenous infusions in Chinese healthy volunteers

OBJECTIVES

To explore the effect of cytochrome P450 2C19 (CYP2C19) polymorphisms on the relationship between the pharmacokinetics and pharmacodynamics of omeprazole administered by intravenous successive infusions in Chinese healthy volunteers.

METHODS

A total of 21 subjects [7 homozygous extensive metabolizers (homEMs), 9 heterozygous extensive metabolizers (hetEMs), 5 poor metabolizers (PMs)] received a 5-day course of omeprazole (40 mg) administered as a single dose daily during a 30-min period. Plasma concentrations were monitored by sampling at very short intervals for the first 8.5 h post-omeprazole administration and at 24 h post-administration, and intragastric pH was recorded on days 1 and 5.

RESULTS

After a single dose, both the area under the plasma concentration-time curve (AUC) and peak concentration (C(max)) were higher in PMs than in EMs. Both the mean half-life (t((1/2))) and total clearance in PMs were significantly higher and lower than those in homEMs and EMs, respectively. Mean AUC and C(max) ratios in homEMs, hetEMs, and PMs were 1.0:1.1:1.4 and 1.0:1.0:1.1, respectively. Relative to the values determined after a single dose in EMs, after repeated doses, the intragastric pH, AUC, C(max), and t((1/2)) had increased significantly, while the total clearance had decreased significantly. Mean AUC and C(max) ratios in homEMs, hetEMs, and PMs were 1.4:1.4:1.5 and 1.2:1.2:1.3, respectively, compared to those of a single dose. The mean intragastric pH was significantly higher in PMs than in EMs after the fifth dose.

CONCLUSIONS

There is a relationship between the pharmacokinetics and pharmacodynamics of omeprazole, with the latter depending in part on the duration of administration as evidenced by a higher AUC or C(max) and intragastric pH resulting from repeated dosing.

Prediction of pharmacokinetic drug-drug interaction caused by changes in cytochrome P450 activity using in vivo information

The aim of the present paper was to present an overview of the current status of the methods used to predict the magnitude of pharmacokinetic drug-drug interactions (DDIs) which are caused by apparent changes in cytochrome P450 (CYP) activity with an emphasis on a method using in vivo information. In addition, more than a hundred representative CYP substrates, inhibitor and inducer drugs involved in significant pharmacokinetic DDIs were selected from the literature and are listed. Although the magnitude of DDIs has been conventionally predicted based on in vitro experiments, their predictability is restricted occasionally due to several difficulties, including a precise determination of the unbound inhibitor concentrations at the enzyme site and a reliable in vitro measurement of the inhibition constant (K(i)). Alternatively, a simple method has been recently proposed for the prediction of the magnitude of DDIs based on information fully available from in vivo clinical studies. The new in vivo-based method would be applicable to the adjustment of dose regimens in actual pharmacotherapy situations although it requires a prior clinical study for the prediction. In this review, theoretical and quantitative relationships between the in vivo- and the in vitro-based prediction methods are considered. One of the interesting outcomes of the consideration is that the K(i)-normalized dose (dose/in vitro K(i)) of larger than approximately 20L (2-200L, when variability is considered) may be a pragmatic index which predicts significant in vivo DDIs. In the last part of the article, the relevance of the inclusion of the in vivo-based method into the process of new drug development is discussed for good prediction of in vivo DDIs.

Proton pump inhibitors: an update of their clinical use and pharmacokinetics

BACKGROUND

Proton pump inhibitors (PPIs) represent drugs of first choice for treating peptic ulcer, Helicobacter pylori infection, gastrooesophageal reflux disease, nonsteroidal anti-inflammatory drug (NSAID)-induced gastrointestinal lesions (complications), and Zollinger-Ellison syndrome.

RESULTS

The available agents (omeprazole/esomeprazole, lansoprazole, pantoprazole, and rabeprazole) differ somewhat in their pharmacokinetic properties (e.g., time-/dose-dependent bioavailability, metabolic pattern, interaction potential, genetic variability). For all PPIs, there is a clear relationship between drug exposure (area under the plasma concentration/time curve) and the pharmacodynamic response (inhibition of acid secretion). Furthermore, clinical outcome (e.g., healing and eradication rates) depends on maintaining intragastric pH values above certain threshold levels. Thus, any changes in drug disposition will subsequently be translated directly into clinical efficiency so that extensive metabolizers of CYP2C19 will demonstrate a higher rate of therapeutic nonresponse.

CONCLUSIONS

This update of pharmacokinetic, pharmacodynamic, and clinical data will provide the necessary guide by which to select between the various PPIs that differ-based on pharmacodynamic assessments-in their relative potencies (e.g., higher doses are needed for pantoprazole and lansoprazole compared with rabeprazole). Despite their well-documented clinical efficacy and safety, there is still a certain number of patients who are refractory to treatment with PPIs (nonresponder), which will leave sufficient space for future drug development and clinical research.

Differential genotype dependent inhibition of CYP2C9 in humans

The effects of genetic polymorphisms in drug-metabolizing enzymes (e.g., CYP2C9(*)3) on drug clearance have been well characterized but much less is known about whether these polymorphisms alter susceptibility to drug-drug interactions. Previous in vitro work has demonstrated that genotype-dependent inhibition of CYP2C9 mediated flurbiprofen metabolism, suggesting the possibility of genotype-dependent inhibition interactions in vivo. In the current study, flurbiprofen was used as a probe substrate and fluconazole as a prototypical inhibitor to investigate whether genotype-dependent inhibition of CYP2C9 occurs in vivo. From 189 healthy volunteers who were genotyped for CYP2C9 polymorphisms, 11 control subjects (CYP2C9(*)1/(*)1), 9 heterozygous and 2 homozygous for the CYP2C9(*)3 allele participated in the pharmacokinetic drug interaction study. Subjects received a single 50-mg oral dose of flurbiprofen alone or after administration of either 200 or 400 mg of fluconazole for 7 days using an open, randomized, crossover design. Flurbiprofen and fluconazole plasma concentrations along with flurbiprofen and 4'-hydroxyflurbiprofen urinary excretion were monitored. Flurbiprofen apparent oral clearance differed significantly among the three genotype groups (p < 0.05) at baseline but not after pretreatment with 400 mg of fluconazole for 7 days. Changes in flurbiprofen apparent oral clearance after fluconazole coadministration were gene dose-dependent, with virtually no change occurring in (*)3/(*)3 subjects. Analysis of fractional clearances suggested that the fraction metabolized by CYP2C9, as influenced by genotype, determined the degree of drug interaction observed. In summary, the presence of CYP2C9(*)3 alleles (either one or two alleles) can alter the degree of drug interaction observed upon coadministration of inhibitors.

Effect of fluvoxamine on the pharmacokinetics of roflumilast and roflumilast N-oxide

OBJECTIVE

To investigate the effects of steady-state dosing of fluvoxamine, an inhibitor of cytochrome P450 (CYP) 1A2 and CYP2C19, on the pharmacokinetics of roflumilast, an oral, once-daily phosphodiesterase 4 (PDE4) inhibitor and its pharmacodynamically active metabolite roflumilast N-oxide.

METHODS

In an open-label, non-randomised, one-sequence, two-period, two-treatment crossover study, 14 healthy subjects received a single oral dose of roflumilast 500 microg on study day 1. After a 6-day washout period, repeated doses of fluvoxamine 50 mg once daily were given from days 8 to 21. On day 15, roflumilast 500 microg and fluvoxamine 50 mg were taken concomitantly. Percentage ratios of test/reference (reference: roflumilast alone; test: roflumilast plus steady-state fluvoxamine) of geometric means and their 90% confidence intervals for area under the plasma concentration-time curve, maximum plasma concentration (roflumilast and roflumilast N-oxide) and plasma clearance of roflumilast were calculated.

RESULTS

Upon co-administration with steady-state fluvoxamine, the exposure to roflumilast as well as roflumilast N-oxide increased by a factor of 2.6 and 1.5, respectively. Roflumilast plasma clearance decreased by a factor of 2.6, from 9.06 L/h (reference) to 3.53 L/h (test). The combined effect of fluvoxamine co-administration on roflumilast and roflumilast N-oxide exposures resulted in a moderate (i.e. 59%) increase in total PDE4 inhibitory activity.

CONCLUSION

Co-administration of roflumilast and fluvoxamine affects the disposition of roflumilast and its active metabolite roflumilast N-oxide most likely via a potent dual pathway inhibition of CYP1A2 and CYP2C19 by fluvoxamine. The exposure increases observed for roflumilast N-oxide are suggested to be attributable to CYP2C19 co-inhibition by fluvoxamine and thus, are not to be expected to occur when roflumilast is co-administered with more selective CYP1A2 inhibitors.

Estimation of CYP2C19 activity by the omeprazole hydroxylation index at a single point in time after intravenous and oral administration

OBJECTIVE

The purpose of this study was to identify the common time point to achieve hydroxylation index (HI: omeprazole plasma concentration/5-hydroxyomeprazole plasma concentration) reflecting AUCOPZ/AUC5OH-OPZ after intravenous (IV) and oral (PO) administration.

METHODS

Twenty young and 28 elderly healthy subjects, including different CYP2C19 genotypes, were enrolled in the study. The young subjects received either 40 mg PO or 20 mg IV omeprazole, whereas the elderly subjects received 10 mg IV. The relation between AUCOPZ/AUC5OH-OPZ and HI was determined by Spearman's rank correlation. Multiple stepwise linear regression analysis was performed to identify the common time point to calculate HI that reflects AUCOPZ/AUC5OH-OPZ after IV.

RESULTS

In the correlation between HI and AUCOPZ/AUC5OH-OPZ IV at observed time points, HI3h showed the highest correlation coefficients (r = 0.894, p < 0.001) in all 48 subjects. The correlation of HI between IV and PO at observed time points showed that HI3h was highest (r = 0.916, p < 0.001) in 20 young subjects. Additionally, there was no significant difference between HI(3h) of IV and that of PO (12.9 +/- 15.9 and 12.9 +/- 15.1, p = 0.997). The regression equation of HI3h was the best to estimate AUCOPZ/AUC5OH-OPZ (AUCOPZ/AUC5OH-OPZ = 1.37 * HI3h + 0.18 * Age - 7.83, r2 = 0.883, p < 0.001).

CONCLUSIONS

This study demonstrated that HI3h after omeprazole IV was able to estimate AUCOPZ/AUC5OH-OPZ, as well as HI3h after PO. Additionally, CYP2C19 activity can be estimated more definitely by using HI after omeprazole IV without intestinal absorption.