Inter-individual Variability of In Vivo CYP2D6 Activity in Different Genotypes

Molecular Mechanisms Underlying Single Nucleotide Polymorphism-Induced Reactivity Decrease in CYP2D6

Cytochrome P450 2D6 (CYP2D6) is one of the most important enzymes involved in drug metabolism. Genetic polymorphism can influence drug metabolism by CYP2D6 such that a therapy is seriously affected by under- or overdosing of drugs. However, a general explanation at the atomistic level for poor activity is missing so far. Here we show for the 20 most common single nucleotide polymorphisms (SNPs) of CYP2D6 that poor metabolism is driven by four mechanisms. We found in extensive all-atom molecular dynamics simulations that the rigidity of the I-helix (central helix), distance between central phenylalanines (stabilizing bound substrate), availability of basic residues on the surface of CYP2D6 (binding of cytochrome P450 reductase), and position of arginine 132 (electron transfer to heme) are essential for an extensive function of the enzyme. These results were applied to SNPs with unknown effects, and potential SNPs that may lead to poor drug metabolism were identified. The revealed molecular mechanisms might be important for other drug-metabolizing cytochrome P450 enzymes.

Relevance of plasma lenvatinib concentrations and endogenous urinary cytochrome P450 3A activity biomarkers in clinical practice

Lenvatinib (LEN), a multitarget tyrosine kinase inhibitor used in various cancer treatments, is mainly metabolized by cytochrome P450 3A (CYP3A) enzymes. The importance of therapeutic drug monitoring (TDM) in patients administered LEN has been proposed. Although some biomarkers of endogenous CYP3A activity have been reported, their utility in dosage adjustments has not been well evaluated. This study investigated the correlation between plasma LEN concentrations and endogenous urinary CYP3A biomarkers in clinical practice. Concentrations of plasma LEN (N = 225) and CYP3A biomarkers (cortisol, 6β-hydroxycortisol, deoxycholic acid, and 1β-hydroxydeoxycholic acid) in urine (N = 214) from 20 patients (hepatocellular carcinoma, N = 6; thyroid cancer, N = 3; endometrial cancer, N = 8; and renal cell carcinoma, N = 3) collected for consultation for up to 1 year were evaluated using liquid chromatography-tandem mass spectrometry. Moreover, plasma trough LEN concentrations were predicted using a three-compartment model with linear elimination for outpatients administered LEN before sample collection. Moderate correlations were observed between the quantified actual concentrations and the predicted trough concentrations of LEN, whereas there was no correlation with endogenous urinary CYP3A biomarkers. The utility of endogenous urinary CYP3A biomarkers could not be determined. However, TDM for outpatients administered orally available medicines may be predicted using a nonlinear mixed effect model (NONMEM). This study investigated the utility of endogenous urinary CYP3A biomarkers for personalized medicine and NONMEM for predicting plasma trough drug concentrations. These findings will provide important information for further clinical investigation and detailed TDM.

Prediction of combination effect of quinidine on the pharmacokinetics of tipepidine using a physiologically based pharmacokinetic model

Tipepidine, an antitussive drug, has been reported to have central pharmacological effects and can be expected to be safely repositioned as treatment for psychiatric disorders. Since tipepidine requires three doses per day, development of a once-daily medication would be highly beneficial. Previously, we reported that combination use with quinidine, a CYP2D6 inhibitor, prolongs the half-life of tipepidine in chimeric mice with humanised liver.In this study, to predict this combination effect in humans, a physiologically based pharmacokinetic (PBPK) model was developed, and quantitative simulation was conducted. The simulation results indicated that concomitant administration of tipepidine with quinidine increased the predicted Cmax, AUC, and t1/2 of tipepidine in the Japanese population by 3.4-, 6.6-, and 2.4-fold, respectively.Furthermore, to compare with another approach that aims to prolong the half-life, the PK profile of tipepidine administered in hypothetical extended-release form was simulated. Extended-release form was predicted to be more influenced by CYP2D6 genotype than combination with quinidine, and the predicted plasma exposure was markedly increased in poor metabolizers, potentially leading to adverse effects.In conclusion, quantitative simulation using the PBPK model suggests the feasibility of the safe repositioning of tipepidine as a once-daily medication in combination with quinidine.

Personalizing atomoxetine dosing in children with ADHD: what can we learn from current supporting evidence

PURPOSE

There is marked heterogeneity in treatment response of atomoxetine in patients with attention deficit/hyperactivity disorder (ADHD), especially for the pediatric population. This review aims to evaluate current evidence to characterize the dose-exposure relationship, establish clinically relevant metrics for systemic exposure to atomoxetine, define a therapeutic exposure range, and to provide a dose-adaptation strategy before implementing personalized dosing for atomoxetine in children with ADHD.

METHODS

A comprehensive search was performed across electronic databases (PubMed and Embase) covering the period of January 1, 1985 to July 10, 2022, to summarize recent advances in the pharmacokinetics, pharmacogenomics/pharmacogenetics (PGx), therapeutic drug monitoring (TDM), physiologically based pharmacokinetics (PBPK), and population pharmacokinetics (PPK) of atomoxetine in children with ADHD.

RESULTS

Some factors affecting the pharmacokinetics of atomoxetine were summarized, including food, CYP2D6 and CYP2C19 phenotypes, and drug‒drug interactions (DDIs). The association between treatment response and genetic polymorphisms of genes encoding pharmacological targets, such as norepinephrine transporter (NET/SLC6A2) and dopamine β hydroxylase (DBH), was also discussed. Based on well-developed and validated assays for monitoring plasma concentrations of atomoxetine, the therapeutic reference range in pediatric patients with ADHD proposed by several studies was summarized. However, supporting evidence on the relationship between systemic atomoxetine exposure levels and clinical response was far from sufficient.

CONCLUSION

Personalizing atomoxetine dosage may be even more complex than anticipated thus far, but elucidating the best way to tailor the non-stimulant to a patient's individual need will be achieved by combining two strategies: detailed research in linking the pharmacokinetics and pharmacodynamics in pediatric patients, and better understanding in nature and causes of ADHD, as well as environmental stressors.

Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan

The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.

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.

Human variability in polymorphic CYP2D6 metabolism: Implications for the risk assessment of chemicals in food and emerging designer drugs

The major human cytochrome P450 CYP2D6 isoform enzyme plays important roles in the liver and in the brain with regards to xenobiotic metabolism. Xenobiotics as CYP2D6 substrates include a whole range of pharmaceuticals, pesticides and plant alkaloids to cite but a few. In addition, a number of endogenous compounds have been shown to be substrates of CYP2D6 including trace amines in the brain such as tyramine and 5-methoxytryptamine as well as anandamide and progesterone. Because of the polymorphic nature of CYP2D6, considerable inter-phenotypic and inter-ethnic differences in the pharmaco/toxicokinetics (PK/TK) and metabolism of CYP2D6 substrates exist with potential consequences on the pharmacology and toxicity of chemicals. Here, large extensive literature searches have been performed to collect PK data from published human studies for a wide range of pharmaceutical probe substrates and investigate human variability in CYP2D6 metabolism. The computed kinetic parameters resulted in the largest open source database, quantifying inter-phenotypic differences for the kinetics of CYP2D6 probe substrates in Caucasian and Asian populations, to date. The database is available in supplementary material (CYPD6 DB) and EFSA knowledge junction (DOI to added). Subsequently, meta-analyses using a hierarchical Bayesian model for markers of chronic oral exposure (oral clearance, area under the plasma concentration time curve) and acute oral exposure (maximum plasma concentration (Cmax) provided estimates of inter-phenotypic differences and CYP2D6-related uncertainty factors (UFs) for chemical risk assessment in Caucasian and Asian populations classified as ultra-rapid (UM), extensive (EMs), intermediate (IMs) and poor metabolisers (PMs). The model allowed the integration of inter-individual (i.e. inter-phenotypic and inter-ethnic), inter-compound and inter-study variability together with uncertainty in each PK parameter. Key findings include 1. Higher frequencies of PMs in Caucasian populations compared to Asian populations (>8% vs 1-2%) for which EM and IM were the most frequent phenotype. 2. Large inter-phenotypic differences in PK parameters for Caucasian EMs (coefficients of variation (CV) > 50%) compared with Caucasian PMs and Asian EMs and IMs (i.e CV < 40%). 3. Inter-phenotypic PK differences between EMs and PMs in Caucasian populations increase with the quantitative contribution of CYP2D6 for the metabolism (fm) for a range of substrates (fm_CYP2D6 range: 20-95% of dose) (range: 1-54) to a much larger extent than those for Asian populations (range: 1-4). 4. Exponential meta-regressions between Fm_CYP2D6 in EMs and inter-phenotypic differences were also shown to differ between Caucasian and Asian populations as well as CYP2D6-related UFs. Finally, implications of these results for the risk assessment of food chemicals and emerging designer drugs of public health concern, as CYP2D6 substrates, are highlighted and include the integration of in vitro metabolism data and CYP2D6-variability distributions for the development of quantitative in vitro in vivo extrapolation models.

Impact of CYP2D6 activity and cachexia progression on enantiomeric alteration of plasma tramadol and its demethylated metabolites and their relationships with central nervous system symptoms in head and neck cancer patients

This study aimed to evaluate the influence of CYP2D6 activity and cachexia progression on the enantiomeric alteration of plasma tramadol and its demethylated metabolites in head and neck cancer patients. Fifty-three head and neck cancer patients receiving oral tramadol were enrolled. The plasma concentrations of tramadol, O-desmethyltramadol (ODT) and N-desmethyltramadol (NDT) enantiomers were determined. The CYP2D6 activity score (AS) and degree of cachexia progression were assessed according to genotype and the Glasgow Prognostic Score (GPS), respectively. The enantiomeric ratio of NDT was (+)-form dominant in all patients. CYP2D6 AS had negative correlations with the plasma concentrations of (+)-NDT and (-)-NDT. The plasma concentrations of (+)-tramadol and (+)-ODT were higher in patients with GPS 1 or 2 than in those with GPS 0. Lower metabolic ratios to NDT enantiomers were observed in patients with GPS 1 or 2. In patients with GPS 1 or 2, the plasma (-)-tramadol was associated with the incidence of central nervous system symptoms. In conclusion, CYP2D6 AS partially explained the contribution of CYP2D6 activity to plasma tramadol and its demethylated metabolite enantiomers. Additionally, cachexia progression elevated the plasma (+)-tramadol and (+)-ODT levels through the reduction of N-demethylation of (+)-tramadol.

Evaluating Potential Disease-Mediated Protein-Drug Interactions in Patients With Moderate-to-Severe Plaque Psoriasis Receiving Subcutaneous Guselkumab

This open-label, multicenter, phase I therapeutic protein-drug interaction study was designed to evaluate the potential effect of guselkumab, a fully human anti-interleukin-23 immunoglobulin G1 lambda monoclonal antibody, on the pharmacokinetics of a cocktail of representative cytochrome P450 (CYP) probe substrates (midazolam (CYP3A4), S-warfarin (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), and caffeine (CYP1A2)). Fourteen participants with psoriasis received a single subcutaneous dose of guselkumab 200 mg on day 8 and an oral probe cocktail on days 1, 15, and 36. Blood samples were collected for measuring plasma concentrations of these probe substrates on days 1, 15, and 36. No consistent trends in observed maximum plasma concentration and area under the curve from time 0 to infinity values of each probe CYP-substrate before (day 1) and after guselkumab treatment (days 15 and 36) could be identified in each individual patient, suggesting that the use of guselkumab in patients with psoriasis is unlikely to influence the systemic exposure of drugs metabolized by CYP isozymes (CYP3A4, CYP2C9, CYP2C19, CYP2D6, and CYP1A2). The probe cocktail was generally well-tolerated when administered in combination with guselkumab in patients with psoriasis. Clinicaltrials.gov Identifiers: NCT02397382.

Determination of the Kinetic Parameters for 123I Uptake by the Thyroid, Thyroid Weights, and Thyroid Volumes in Present-day Healthy Japanese Volunteers

The purpose of this study was to evaluate the kinetic parameters that determine the uptake rate of radioiodide in the thyroid over 24 h after administration and to estimate thyroid volumes/masses of present-day Japanese. Methods: We determined the thyroid uptake rate of I in healthy male Japanese after oral administration (4.5-8.0 MBq) without iodine restriction. Masses of thyroid glands were collected in 2012-2016 during autopsies of 7,651 male and 3,331 female subjects. Volumes of thyroid glands were estimated by ultrasonography and magnetic resonance imaging in 52 male subjects. Results: The thyroid uptake rate of I for 24 h was 16.1 ± 5.4%. Kinetic model analysis was conducted to obtain the clearances (L h) for thyroid uptake and urinary excretion of I (0.499 ± 0.258 and 2.10 ± 0.39 L h, respectively). The masses of thyroid glands were on average 19.8 g (95% confidence interval of 18.3-19.5 g) and 15.5 g (95% confidence interval of 14.7-16.2 g) in male and female subjects aged 19-52 y, respectively. Volumes of thyroid glands estimated by ultrasonography and magnetic resonance imaging were 17.5 ± 5.2 and 14.2 ± 5.3 mL, respectively. In healthy Japanese, there has been no significant change for at least 50 y in the thyroid uptake of radioiodide over 24 h or in its kinetic parameters. These Japanese-specific kinetic parameters will allow quantitative estimation of the radiation exposure from the Fukushima accident and its variance during the individual's evacuation from or stay in Fukushima.

Application of PBPK Modeling and Virtual Clinical Study Approaches to Predict the Outcomes of CYP2D6 Genotype-Guided Dosing of Tamoxifen

The Tamoxifen Response by CYP2D6 Genotype‐based Treatment‐1 (TARGET‐1) study (n = 180) was conducted from 2012–2017 in Japan to determine the efficacy of tamoxifen dosing guided by cytochrome P450 2D6 (CYP2D6) genotypes. To predict its outcomes prior to completion, we constructed the comprehensive physiologically based pharmacokinetic (PBPK) models of tamoxifen and its metabolites and performed virtual TARGET‐1 studies. Our analyses indicated that the expected probability to achieve the end point (demonstrating the superior efficacy of the escalated tamoxifen dose over the standard dose in patients carrying CYP2D6 variants) was 0.469 on average. As the population size of this virtual clinical study (VCS) increased, the expected probability was substantially increased (0.674 for n = 260). Our analyses also informed that the probability to achieve the end point in the TARGET‐1 study was negatively impacted by a large variability in endoxifen levels. Our current efforts demonstrate the promising utility of the PBPK modeling and VCS approaches in prospectively designing effective clinical trials.

Prediction of inter-individual variability on the pharmacokinetics of CYP2C8 substrates in human

Inter-individual variability in pharmacokinetics can lead to unexpected side effects and treatment failure, and is therefore an important factor in drug development. CYP2C8 is a major drug-metabolizing enzyme known to be involved in the metabolism of over 100 drugs. In this study, we predicted the inter-individual variability in AUC/Dose of CYP2C8 substrates in healthy volunteers using the Monte Carlo simulation. Inter-individual variability in the hepatic intrinsic clearance of CYP2C8 substrates (CL_int,h,2C8) was estimated from the inter-individual variability in pharmacokinetics of pioglitazone, which is a major CYP2C8 substrate. The coefficient of variation (CV) of CL_int,h,2C8 was estimated to be 40%. Using this value, the CVs of AUC/Dose of other major CYP2C8 substrates, rosiglitazone and amodiaquine, were predicted to validate the estimated CV of CL_int,h,2C8. As a result, the reported CVs of both substrates were within the 2.5-97.5 percentile range of the predicted CVs. Furthermore, the CVs of AUC/Dose of the CYP2C8 substrates loperamide and chloroquine, which are affected by renal clearance, were also successfully predicted. Combining this value with previously reported CVs of other CYPs, we were able to successfully predict the inter-individual variability in pharmacokinetics of various drugs in clinical.

Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability

The thousands of chemicals present in the environment (USGAO, 2013) must be triaged to identify priority chemicals for human health risk research. Most chemicals have little of the toxicokinetic (TK) data that are necessary for relating exposures to tissue concentrations that are believed to be toxic. Ongoing efforts have collected limited, in vitro TK data for a few hundred chemicals. These data have been combined with biomonitoring data to estimate an approximate margin between potential hazard and exposure. The most "at risk" 95th percentile of adults have been identified from simulated populations that are generated either using standard "average" adult human parameters or very specific cohorts such as Northern Europeans. To better reflect the modern U.S. population, we developed a population simulation using physiologies based on distributions of demographic and anthropometric quantities from the most recent U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES) data. This allowed incorporation of inter-individual variability, including variability across relevant demographic subgroups. Variability was analyzed with a Monte Carlo approach that accounted for the correlation structure in physiological parameters. To identify portions of the U.S. population that are more at risk for specific chemicals, physiologic variability was incorporated within an open-source high-throughput (HT) TK modeling framework. We prioritized 50 chemicals based on estimates of both potential hazard and exposure. Potential hazard was estimated from in vitro HT screening assays (i.e., the Tox21 and ToxCast programs). Bioactive in vitro concentrations were extrapolated to doses that produce equivalent concentrations in body tissues using a reverse dosimetry approach in which generic TK models are parameterized with: 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. For risk-based prioritization of chemicals, predicted bioactive equivalent doses were compared to demographic-specific inferences of exposure rates that were based on NHANES urinary analyte biomonitoring data. The inclusion of NHANES-derived inter-individual variability decreased predicted bioactive equivalent doses by 12% on average for the total population when compared to previous methods. However, for some combinations of chemical and demographic groups the margin was reduced by as much as three quarters. This TK modeling framework allows targeted risk prioritization of chemicals for demographic groups of interest, including potentially sensitive life stages and subpopulations.

Effect of 24 Cytochrome P450 2D6 Variants Found in the Chinese Population on Atomoxetine Metabolism in vitro

OBJECTIVE

The aim of this article was to assess the catalytic activities of 24 cytochrome P450 2D6 (CYP2D6) variants found in the Chinese population toward atomoxetine in vitro as well as CYP2D6.1.

METHODS

In this study, the co-expression enzyme of human recombinant CYPOR, CYPb5, and CYP2D6.1 or other CYP2D6 variants with the baculovirus-mediated insect cells (Sf21) was used to study the catalytic activities of 24 CYP2D6 variants toward atomoxetine metabolism. The metabolite of atomoxetine (4-hydroxyatomoxetine) was detected by ultra-high performance liquid chromatography-mass spectrometry method.

RESULTS

The intrinsic clearance (Vmax/Km) values of most variants were significantly altered when compared with CYP2D6.1. CYP2D6.94, CYP2D6.D336N, CYP2D6.R440C exhibited marked increased values 172, 126, 121% respectively. CYP2D6.89 and CYP2D6.98 exhibited similar catalytic activity as the wild type, whereas 17 variants exhibited significantly decreased values (from 5 to 87%) due to increase Km and/or decrease Vmax values. However, CYP2D6.92 and CYP2D6.96 showed no or few activity because of producing nothing.

CONCLUSIONS

Our results suggest that most of these newly found variants exhibit significantly changed catalytic activities compared with the wild type. And these findings provide valuable information for the growth and development of personalized medicine in China.

Rapid onset of syndrome of inappropriate antidiuretic hormone secretion induced by duloxetine in an elderly type 2 diabetic patient with painful diabetic neuropathy

Diabetic neuropathy is the most common diabetic complication. Duloxetine, a serotonin noradrenaline reuptake inhibitor (SNRI), is widely used for the treatment of diabetic painful neuropathy (DPN) because of the efficacy and safety profile. Syndrome of inappropriate antidiuretic hormone secretion, which is strongly associated duloxetine, is a rare but occasionally life-threatening adverse effect. Here, we report a case of syndrome of inappropriate antidiuretic hormone secretion that rapidly developed after starting duloxetine in an elderly Japanese female type 2 diabetes mellitus patient. Furthermore, we discuss the possible relationship between the onset of syndrome of inappropriate antidiuretic hormone secretion and the gene polymorphism of cytochrome P450 isoform 1A2 and 2D6, both of which are responsible for duloxetine metabolism.

Prediction of inter-individual variability in the pharmacokinetics of CYP2C19 substrates in humans

Significant inter-individual variability of exposure for CYP2C19 substrates may be only partly due to genetic polymorphism. Therefore, the in vivo inter-individual variability in hepatic intrinsic clearance (CL(int,h)) of CYP2C19 substrates was estimated from reported AUC values using Monte Carlo simulations. The coefficient of variation (CV) for CL(int,h) in poor metabolizers (PM) expected from genotypes CYP2C19*2/*2, CYP2C19*3/*3 or CYP2C19*2/*3 was estimated as 25.8% from the CV for AUC of omeprazole in PMs. With this, CVs of CL(int,h) in extensive metabolizers (EM: CYP2C19*1/*1), intermediate metabolizers (IM: CYP2C19*1/*2 or *3) and ultra-rapid metabolizers (UM), CYP2C19*17/*17 and *1/*17, were estimated as 66.0%, 55.8%, 6.8% and 48.0%, respectively. To validate these CVs, variability in the AUC of CYP2C19 substrates lansoprazole and rabeprazole, partially metabolized by CYP3A4 in EMs and IMs, were simulated using the CV in CL(int,h) for CYP2C19 EMs and IMs and 33% of the CV previously reported for CYP3A4. Published values were within 2.5-97.5 percentile range of simulated CVs for the AUC. Furthermore, simulated CVs for the AUC of omeprazole and lansoprazole in ungenotyped populations were comparable with published values. Thus, estimated CL(int,h) variability can predict variability in the AUC of drugs metabolized not only by CYP2C19 but also by multiple enzymes.