IN VITRO-IN VIVO EXTRAPOLATION OF CYP2D6 INACTIVATION BY PAROXETINE: PREDICTION OF NONSTATIONARY PHARMACOKINETICS AND DRUG INTERACTION MAGNITUDE

Pharmacokinetics during therapeutic hypothermia in neonates: from pathophysiology to translational knowledge and physiologically-based pharmacokinetic (PBPK) modeling

INTRODUCTION

Perinatal asphyxia (PA) still causes significant morbidity and mortality. Therapeutic hypothermia (TH) is the only effective therapy for neonates with moderate to severe hypoxic-ischemic encephalopathy after PA. These neonates need additional pharmacotherapy, and both PA and TH may impact physiology and, consequently, pharmacokinetics (PK) and pharmacodynamics (PD).

AREAS COVERED

This review provides an overview of the available knowledge in PubMed (until November 2022) on the pathophysiology of neonates with PA/TH. In vivo pig models for this setting enable distinguishing the effect of PA versus TH on PK and translating this effect to human neonates. Available asphyxia pig models and methodological considerations are described. A summary of human neonatal PK of supportive pharmacotherapy to improve neurodevelopmental outcomes is provided.

EXPERT OPINION

To support drug development for this population, knowledge from clinical observations (PK data, real-world data on physiology), preclinical (in vitro and in vivo (minipig)) data, and molecular and cellular biology insights can be integrated into a predictive physiologically-based PK (PBPK) framework, as illustrated by the I-PREDICT project (Innovative physiology-based pharmacokinetic model to predict drug exposure in neonates undergoing cooling therapy). Current knowledge, challenges, and expert opinion on the future directions of this research topic are provided.

Pharmacokinetics of immediate and sustained-release formulations of paroxetine: Population pharmacokinetic approach to guide paroxetine personalized therapy in chinese psychotic patients

Paroxetine is one of the most potent selective serotonin reuptake inhibitors (SSRIs) approved for treating depression, panic disorder, and obsessive-compulsive disorder. There is evidence linking genetic polymorphisms and nonlinear metabolism to the Paroxetine’s pharmacokinetic (PK) variability. The purpose of the present study was to develop a population PK (PPK) model of paroxetine in Chinese patients, which was used to define the paroxetine’s PK parameters and quantify the effect of clinical and baseline demographic factors on these PK characteristics. The study included 184 inpatients with psychosis (103 females and 81 males), with a total of 372 serum concentrations of paroxetine for PPK analyses. The total daily dosage ranged from 20 to 75 mg. One compartment model could fit the PKs characterize of paroxetine. Covariate analysis revealed that dose, formulation, and sex had a significant effect on the PK parameters of paroxetine; however, there was no evident genetic influence of CYP2D6 enzymes on paroxetine concentrations in Chinese patients. The study determined that the population’s apparent distribution volume (V/F) and apparent clearance (CL/F), respectively, were 8850 and 21.2 L/h. The CL/F decreased 1-2-fold for each 10 mg dose increase, whereas the different formulations caused a decrease in V/F of 66.6%. Sex was found to affect bioavailability (F), which decreased F by 47.5%. Females had higher F values than males. This PPK model described data from patients with psychosis who received paroxetine immediate-release tablets (IR-T) and/or sustained-release tablets (SR-T). Paroxetine trough concentrations and relative bioavailability were different between formulations and sex. The altered serum concentrations of paroxetine resulting from individual variants and additive effects need to be considered, to optimize the dosage regimen for individual patients.

Physiologically Based Pharmacokinetic Modeling to Describe the CYP2D6 Activity Score-Dependent Metabolism of Paroxetine, Atomoxetine and Risperidone

The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of CYP2D6 activity as well as interindividual and interpopulation variability in CYP2D6 activity. Here, the CYP2D6 activity score provides an established tool to categorize the large number of CYP2D6 alleles by activity and facilitates the process of genotype-to-phenotype translation. Compared to the broad traditional phenotype categories, the CYP2D6 activity score additionally serves as a superior scale of CYP2D6 activity due to its finer graduation. Physiologically based pharmacokinetic (PBPK) models have been successfully used to describe and predict the activity score-dependent metabolism of CYP2D6 substrates. This study aimed to describe CYP2D6 drug–gene interactions (DGIs) of important CYP2D6 substrates paroxetine, atomoxetine and risperidone by developing a substrate-independent approach to model their activity score-dependent metabolism. The models were developed in PK-Sim^®, using a total of 57 plasma concentration–time profiles, and showed good performance, especially in DGI scenarios where 10/12, 5/5 and 7/7 of DGI AUC_last ratios and 9/12, 5/5 and 7/7 of DGI C_max ratios were within the prediction success limits. Finally, the models were used to predict their compound’s exposure for different CYP2D6 activity scores during steady state. Here, predicted DGI AUC_ss ratios were 3.4, 13.6 and 2.0 (poor metabolizers; activity score = 0) and 0.2, 0.5 and 0.95 (ultrarapid metabolizers; activity score = 3) for paroxetine, atomoxetine and risperidone active moiety (risperidone + 9-hydroxyrisperidone), respectively.

Predictive In Vitro-In Vivo Extrapolation for Time Dependent Inhibition of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6 Using Pooled Human Hepatocytes, Human Liver Microsomes, and a Simple Mechanistic Static Model

Inactivation of Cytochrome P450 (CYP450) enzymes can lead to significant increases in exposure of co-medicants. The majority of reported in vitro to in vivo extrapolation (IVIVE) data have historically focused on CYP3A4 leaving the assessment of other CYP isoforms insubstantial. To this end, the utility of human hepatocytes (HHEP) and microsome (HLM) to predict clinically relevant DDIs was investigated with a focus on CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6. Evaluation of IVIVE for CYP2B6 was limited to only weak inhibition. A search of the University of Washington Drug-Drug Interaction Database was conducted to identify a clinically relevant weak, moderate and strong inhibitor for selective substrates of CYP1A2, CYP2C8, CYP2C9, CYP2C19 and CYP2D6, resulting in 18 inhibitors for in vitro characterization against 119 clinical interaction studies. Pooled human hepatocytes and HLM were pre-incubated with increasing concentrations of inhibitors for designated timepoints. Time dependent inhibition (TDI) was detected in HLM for four moderate/strong inhibitors suggesting that some optimization of incubation conditions (i.e. lower protein concentrations) is needed to capture weak inhibition. Clinical risk assessment was conducted by incorporating the in vitro derived kinetic parameters k_inact and K_I into static equations recommended by regulatory authorities. Significant overprediction was observed when applying the basic models recommended by regulatory agencies. Mechanistic static models (MSM), which consider the fraction of metabolism through the impacted enzyme, using the unbound hepatic inlet concentration lead to the best overall prediction accuracy with 92% and 85% of data from HHEPs and HLM, respectively, within 2-fold of the observed value. Significance Statement Collectively, the data demonstrate that coupling time-dependent inactivation parameters derived from pooled human hepatocytes and HLM with a mechanistic static model provides an easy and quantitatively accurate means to determine clinical DDI risk from in vitro data. Weak and moderate inhibitors did not show TDI under standard incubation conditions using HLM and optimization of incubation conditions is warranted. Recommendations are made with respect to input parameters for IVIVE of TDI with non-CYP3A enzymes using available data from HLM and HHEPs.

An update on the treatment of premature ejaculation: A systematic review

To analyse the current therapeutic options for patients with premature ejaculation (PE) and highlight their mechanism(s) of action, effectiveness, advantages and limitations. A literature search was conducted using the PubMed database searching for articles exploring different PE treatment modalities. A Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) approach was used to report the results of the literature search. A total of 149 articles were included in this review. The currently available treatment methods for PE include behavioural therapy, local anaesthetics, tricyclic antidepressants, selective serotonin reuptake inhibitors, and selective phosphodiesterase inhibitors. Most PE treatments are either experimental or used off-label. New treatments are certainly warranted to overcome this exasperating sexual dysfunction.

Abbreviations: AIPE: Arabic Index of Premature Ejaculation; CNS: central nervous system; CYP: cytochrome P450; ED: erectile dysfunction; FDA: United States Food and Drug Administration; H1: histamine receptors; 5-HT: 5-hydroxytryptamine; IELT: The intravaginal ejaculation latency time; IPE: Index of Premature Ejaculation; M1: muscarinic receptors; OCD: obsessive–compulsive disorder; PDE5: phosphodiesterase type 5; PE: premature ejaculation; PEP: Premature Ejaculation Profile; PRO: patient-reported outcome; RCT: randomised controlled trial; SS: Severance Secret (cream); SSRIs: selective serotonin reuptake inhibitors; TCAs: tricyclic antidepressants

Cytochrome P450 enzymes: a review on drug metabolizing enzyme inhibition studies in drug discovery and development

Assessment of drug candidate's potential to inhibit cytochrome P450 (CYP) enzymes remains crucial in pharmaceutical drug discovery and development. Both direct and time-dependent inhibition of drug metabolizing CYP enzymes by the concomitant administered drug is the leading cause of drug-drug interactions (DDIs), resulting in the increased toxicity of the victim drug. In this context, pharmaceutical companies have grown increasingly diligent in limiting CYP inhibition liabilities of drug candidates in the early stages and examining risk assessments throughout the drug development process. This review discusses different strategies and decision-making processes for assessing the drug-drug interaction risks by enzyme inhibition and lays particular emphasis on in vitro study designs and interpretation of CYP inhibition data in a stage-appropriate context.

Mechanism-Based Inactivation of Cytochrome P450 Enzymes: Computational Insights

Mechanism-based inactivation (MBI) refers to the metabolic bioactivation of a xenobiotic by cytochrome P450s to a highly reactive intermediate which subsequently binds to the enzyme and leads to the quasi-irreversible or irreversible inhibition. Xenobiotics, mainly drugs with specific functional units, are the major sources of MBI. Two possible consequences of MBI by medicinal compounds are drug-drug interaction and severe toxicity that are observed and highlighted by clinical experiments. Today almost all of these latent functional groups (e.g., thiophene, furan, alkylamines, etc.) are known, and their features and mechanisms of action, owing to the vast experimental and theoretical studies, are determined. In the past decade, molecular modeling techniques, mostly density functional theory, have revealed the most feasible mechanism that a drug undergoes by P450 enzymes to generate a highly reactive intermediate. In this review, we provide a comprehensive and detailed picture of computational advances toward the elucidation of the activation mechanisms of various known groups with MBI activity. To this aim, we briefly describe the computational concepts to carry out and analyze the mechanistic investigations, and then, we summarize the studies on compounds with known inhibition activity including thiophene, furan, alkylamines, terminal acetylene, etc. This study can be reference literature for both theoretical and experimental (bio)chemists in several different fields including rational drug design, the process of toxicity prevention, and the discovery of novel inhibitors and catalysts.

Human CYP2D6 Is Functional in Brain In Vivo: Evidence from Humanized CYP2D6 Transgenic Mice

CYP2D metabolizes many drugs that act within the brain, and variable expression of CYP2D in the brain may alter local drug and metabolite levels sufficiently to affect behavioral responses. Transgenic mice that express human CYP2D6 (TG) were compared to wild type mice (WT). Following selective inhibition of human CYP2D6 in TG brain, we demonstrated in vivo that human CYP2D6 in the brain was sufficient to alter a drug-induced behavioral response. After a 4-h pre-treatment with intracerebroventricular (i.c.v.) propranolol, CYP2D activity in vivo and in vitro was reduced in TG brain, whereas CYP2D activity in vivo, but not in vitro, was reduced in WT brain. After a 24-h pre-treatment with i.c.v. propranolol, CYP2D activity in vivo and in vitro was reduced in TG brain, whereas CYP2D activity in vivo and in vitro was not changed in WT brain. These results indicate that i.c.v. propranolol irreversibly inhibited human CYP2D6 in TG brain but not mouse CYP2D in TG and WT brain. Pre-treatments with propranolol did not change liver CYP2D activity in vivo or in vitro. Furthermore, 24-h pre-treatment with i.c.v. propranolol resulted in a significant decrease of the haloperidol-induced catalepsy response in TG, but not in WT, without changing serum haloperidol levels in either mouse line. These studies reveal a new tool to selectively and irreversibly inhibit human CYP2D6 in TG brain and indicate that human CYP2D6 has a functional role within the brain sufficient to impact the central nervous system response from peripherally administered drugs.

Time-dependent enzyme inactivation: Numerical analyses of in vitro data and prediction of drug-drug interactions

Cytochrome P450 (CYP) enzyme kinetics often do not conform to Michaelis-Menten assumptions, and time-dependent inactivation (TDI) of CYPs displays complexities such as multiple substrate binding, partial inactivation, quasi-irreversible inactivation, and sequential metabolism. Additionally, in vitro experimental issues such as lipid partitioning, enzyme concentrations, and inactivator depletion can further complicate the parameterization of in vitro TDI. The traditional replot method used to analyze in vitro TDI datasets is unable to handle complexities in CYP kinetics, and numerical approaches using ordinary differential equations of the kinetic schemes offer several advantages. Improvement in the parameterization of CYP in vitro kinetics has the potential to improve prediction of clinical drug-drug interactions (DDIs). This manuscript discusses various complexities in TDI kinetics of CYPs, and numerical approaches to model these complexities. The extrapolation of CYP in vitro TDI parameters to predict in vivo DDIs with static and dynamic modeling is discussed, along with a discussion on current gaps in knowledge and future directions to improve the prediction of DDI with in vitro data for CYP catalyzed drug metabolism.

A review of the antimicrobial side of antidepressants and its putative implications on the gut microbiome

OBJECTIVE

Serotonin reuptake inhibitors are the predominant treatment for major depressive disorder. In recent years, the diversity of the gut microbiota has emerged to play a significant role in the occurrence of major depressive disorder and other mood and anxiety disorders. Importantly, the role of the gut microbiota in the treatment of such disorders remains to be elucidated. Here, we provide a review of the literature regarding the effects of physiologically relevant concentrations of serotonin reuptake inhibitors on the gut microbiota and the implications this might have on their efficacy in the treatment of mood disorders.

METHODS

First, an estimation of gut serotonin reuptake inhibitor concentrations was computed based on pharmacokinetic and gastrointestinal transit properties of serotonin reuptake inhibitors. Literature regarding the in vivo and in vitro antimicrobial properties of serotonin reuptake inhibitors was gathered, and the estimated gut concentrations were examined in the context of these data. Computer-based investigation revealed putative mechanisms for the antimicrobial effects of serotonin reuptake inhibitors.

RESULTS

In vivo evidence using animal models shows an antimicrobial effect of serotonin reuptake inhibitors on the gut microbiota. Examination of the estimated physiological concentrations of serotonin reuptake inhibitors in the gastrointestinal tract collected from in vitro studies suggests that the microbial community of both the small intestine and the colon are exposed to serotonin reuptake inhibitors for at least 4 hours per day at concentrations that are likely to exert an antimicrobial effect. The potential mechanisms of the effect of serotonin reuptake inhibitors on the gut microbiota were postulated to include inhibition of efflux pumps and/or amino acid transporters.

CONCLUSION

This review raises important issues regarding the role that gut microbiota play in the treatment of mood-related behaviours, which holds substantial potential clinical outcomes for patients suffering from major depressive disorder and other mood-related disorders.

Numerical Analysis of Time-Dependent Inhibition by MDMA

Methylenedioxymethamphetamine (MDMA) is a known drug of abuse and schedule 1 narcotic under the Controlled Substances Act. Previous pharmacokinetic work on MDMA used classic linearization techniques to conclude irreversible mechanism-based inhibition of CYP2D6. The current work challenges this outcome by assessing the possibility of two alternative reversible kinetic inhibition mechanisms known as the quasi-irreversible (QI) model and equilibrium model (EM). In addition, progress curve experiments were used to investigate the residual metabolism of MDMA by liver microsomes and CYP2D6 baculosomes over incubation periods up to 30 minutes. These experiments revealed activity in a terminal linear phase at the fractional rates with respect to initial turnover of 0.0354 ± 0.0089 in human liver microsomes and 0.0114 ± 0.0025 in baculosomes. Numerical model fits to percentage of remaining activity (PRA) data were consistent with progress curve modeling results, wherein an irreversible inhibition pathway was found unnecessary for good fit scoring. Both QI and EM kinetic mechanisms fit the PRA data well, although in CYP2D6 baculosomes the inclusion of an irreversible inactivation pathway did not allow for convergence to a reasonable fit. The kinetic complexity accessible to numerical modeling has been used to determine that MDMA is not an irreversible inactivator of CYP2D6, and instead follows what can be generally referred to as slowly reversible inhibition. SIGNIFICANCE STATEMENT: The work herein describes the usage of computational models to delineate between irreversible and slowly reversible time-dependent inhibition. Such models are used in the paper to analyze MDMA and classify it as a reversible time-dependent inhibitor.

Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates

A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.

CYP2D6 Protein Level Is the Major Contributor to Interindividual Variability in CYP2D6-Mediated Drug Metabolism in Healthy Human Liver Tissue

CYP2D6 genetic polymorphisms are considered a major contributor to the large interindividual variability in CYP2D6-mediated drug metabolism, but fail to explain a significant portion of the variability. The aim of this study was to assess the ability of the CYP2D6 activity score (AS) estimated from CYP2D6 genotype to predict CYP2D6 expression and enzyme activity. The CYP2D6 gene region was sequenced in 115 healthy human liver tissue samples to determine their CYP2D6 AS. Additionally, CYP2D6 enzyme activity, protein, and mRNA levels were estimated. CYP2D6 AS explained 23% of the interindividual variability in CYP2D6 activity, but only 7.5% in tissues assigned AS 1-2. The CYP2D6 protein level was found to be the major determinant of CYP2D6 activity, explaining 59% of variability. These findings suggest that while CYP2D6 AS is a good predictor of poor metabolizer phenotype, additional nongenetic factors may govern the rate of CYP2D6-mediated metabolism in those without the poor metabolizer phenotype.

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.

Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A

Time-dependent inactivation (TDI) of cytochrome P450s (CYPs) is a leading cause of clinical drug-drug interactions (DDIs). Current methods tend to overpredict DDIs. In this study, a numerical approach was used to model complex CYP3A TDI in human-liver microsomes. The inhibitors evaluated included troleandomycin (TAO), erythromycin (ERY), verapamil (VER), and diltiazem (DTZ) along with the primary metabolites N-demethyl erythromycin (NDE), norverapamil (NV), and N-desmethyl diltiazem (NDD). The complexities incorporated into the models included multiple-binding kinetics, quasi-irreversible inactivation, sequential metabolism, inhibitor depletion, and membrane partitioning. The resulting inactivation parameters were incorporated into static in vitro-in vivo correlation (IVIVC) models to predict clinical DDIs. For 77 clinically observed DDIs, with a hepatic-CYP3A-synthesis-rate constant of 0.000 146 min-1, the average fold difference between the observed and predicted DDIs was 3.17 for the standard replot method and 1.45 for the numerical method. Similar results were obtained using a synthesis-rate constant of 0.000 32 min-1. These results suggest that numerical methods can successfully model complex in vitro TDI kinetics and that the resulting DDI predictions are more accurate than those obtained with the standard replot approach.

In Vitro and In Vivo Investigation of Potential for Complex CYP3A Interaction for PF-00251802 (Dagrocorat), a Novel Dissociated Agonist of the Glucocorticoid Receptor

The dissociated agonists of the glucocorticoid receptor are a novel class of agents in clinical development for rheumatoid arthritis. PF‐04171327 (fosdagrocorat) is a phosphate ester prodrug of PF‐00251802 (dagrocorat), a selective high‐affinity partial agonist of the glucocorticoid receptor, which is further metabolized to PF‐04015475. This study evaluated the cytochrome P450 (CYP)–mediated drug–drug interaction (DDI) potential of PF‐00251802 and PF‐04015475 in vitro and used model‐based prediction approaches to estimate clinical impact. PF‐00251802 is a reversible inhibitor of several CYPs, but modeling has suggested no clinically relevant interaction. PF‐00251802 and PF‐04015475 are time‐dependent inhibitors and inducers of CYP3A in vitro; PF‐00251802 is also a time‐dependent inhibitor of CYP2D6. Model‐based prediction suggested the potential for weak inhibition of CYP3A in vivo. A clinical DDI study was conducted with midazolam, a sensitive CYP3A substrate. A phase 1 open‐label, multiple‐dose study evaluated the effect of PF‐04171327 on midazolam pharmacokinetics and safety in 12 healthy volunteers. Administration of midazolam alone or concomitantly with PF‐04171327 resulted in equivalent pharmacokinetic profiles (AUC_inf, 21.17 vs 20.28 ng·h/mL, respectively), indicating that PF‐04171327 had no net effect on CYP3A activity in vivo. These findings support the further development of PF‐00251802 and PF‐04171327 as potential treatments for patients with rheumatoid arthritis (NCT00987038).

Impact of CYP2D6 Functional Allelic Variations on Phenoconversion and Drug-Drug Interactions

We investigated whether CYP2D6 extensive metabolizers carrying a nonfunctional allele are at higher risk of phenoconversion to poor metabolizers in the presence of CYP2D6 inhibitors. Seventeen homozygous carriers of two fully-functional alleles and 17 heterozygous carriers of one fully-functional and one nonfunctional allele participated in this trial. Dextromethorphan 5 mg and tramadol 10 mg were given at each of the three study sessions. CYP2D6 was inhibited by duloxetine 60 mg (session 2) and paroxetine 20 mg (session 3). A higher rate of phenoconversion to intermediate metabolizers with duloxetine (71% vs. 25%, P = 0.009) and to poor metabolizers with paroxetine (94% vs. 56%, P = 0.011) was observed in heterozygous than homozygous extensive metabolizers. The magnitude of drug-drug interaction between dextromethorphan and paroxetine was higher in homozygous than in heterozygous subjects (14.6 vs. 8.5, P < 0.028). Our study suggests that genetic extensive metabolizers may not represent a homogenous population and that available genetic data should be considered when addressing drug-drug interactions in clinical practice.

Endogenous and xenobiotic metabolic stability of primary human hepatocytes in long-term 3D spheroid cultures revealed by a combination of targeted and untargeted metabolomics

Adverse reactions or lack of response to medications are important concerns for drug development programs. However, faithful predictions of drug metabolism and toxicity are difficult because animal models show only limited translatability to humans. Furthermore, current in vitro systems, such as hepatic cell lines or primary human hepatocyte (PHH) 2-dimensional (2D) monolayer cultures, can be used only for acute toxicity tests because of their immature phenotypes and inherent instability. Therefore, the migration to novel phenotypically stable models is of prime importance for the pharmaceutical industry. Novel 3-dimensional (3D) culture systems have been shown to accurately mimic in vivo hepatic phenotypes on transcriptomic and proteomic level, but information about their metabolic stability is lacking. Using a combination of targeted and untargeted high-resolution mass spectrometry, we found that PHHs in 3D spheroid cultures remained metabolically stable for multiple weeks, whereas metabolic patterns of PHHs from the same donors cultured as conventional 2D monolayers rapidly deteriorated. Furthermore, pharmacokinetic differences between donors were maintained in 3D spheroid cultures, enabling studies of interindividual variability in drug metabolism and toxicity. We conclude that the 3D spheroid system is metabolically stable and constitutes a suitable model for in vitro studies of long-term drug metabolism and pharmacokinetics.—Vorrink, S. U., Ullah, S., Schmid, S., Nandania, J., Velagapudi, V., Beck, O., Ingelman-Sundberg, M., Lauschke, V. M. Endogenous and xenobiotic metabolic stability of primary human hepatocytes in long-term 3D spheroid cultures revealed by a combination of targeted and untargeted metabolomics.

Comparison of the static in vivo approach to a physiologically based pharmacokinetic approach for metabolic drug–drug interactions prediction

Background: The in vivo mechanistic static model (IMSM) and the physiologically based pharmacokinetic (PBPK) model are two approaches used to predict the magnitude of drug–drug interactions (DDIs). The aim of this study was to evaluate the performance of IMSM and to compare IMSM with the PBPK approach implemented in Simcyp. Methods: The predictive performances of IMSM were evaluated on a panel of 628 DDIs. Subsequently, the IMSM and PBPK approaches were compared on a set of 104 DDIs. Results: The IMSM yielded 85% of predictions within 1.5-fold of the observed value on the 628 DDIs panel. The predictive performances of IMSM were better than those of the PBPK approach (median fold error 1 vs 0.86 on 104 studies; p = 0.02). Conclusion: The IMSM approach is an alternative tool for metabolic DDIs prediction.

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.

Exposure-outcome analysis in depressed patients treated with paroxetine using population pharmacokinetics

Purpose

This study investigated population pharmacokinetics of paroxetine, and then performed an integrated analysis of exposure and clinical outcome using population pharmacokinetic parameter estimates in depressed patients treated with paroxetine.

Patients and methods

A total of 271 therapeutic drug monitoring (TDM) data were retrospectively collected from 127 psychiatric outpatients. A population nonlinear mixed-effects modeling approach was used to describe serum concentrations of paroxetine. For 83 patients with major depressive disorder, the treatment response rate and the incidence of adverse drug reaction (ADR) were characterized by logistic regression using daily dose or area under the concentration–time curve (AUC) estimated from the final model as a potential exposure predictor.

Results

One compartment model was developed. The apparent clearance of paroxetine was affected by age as well as daily dose administered at steady-state. Overall treatment response rate was 72%, and the incidence of ADR was 30%. The logistic regression showed that exposure predictors were not associated with treatment response or ADR in the range of dose commonly used in routine practice. However, the incidence of ADR increased with the increase of daily dose or AUC for the patients with multiple concentrations.

Conclusion

In depressed patients treated with paroxetine, TDM may be of limited value for individualization of treatment.

Sex hormones regulate cerebral drug metabolism via brain miRNAs: down-regulation of brain CYP2D by androgens reduces the analgesic effects of tramadol

BACKGROUND AND PURPOSE

Brain cytochrome P450 2D (CYP2D) metabolises exogenous neurotoxins, endogenous substances and neurotransmitters. Brain CYP2D can be regulated in an organ-specific manner, but the possible regulatory mechanisms are poorly understood. We investigated the involvement of miRNAs in the selective regulation of brain CYP2D by testosterone and the corresponding alteration of the pharmacological profiles of tramadol by testosterone.

EXPERIMENTAL APPROACH

The regulation of CYP2D and brain-enriched miRNAs by testosterone was investigated using SH-SY5Y cells, U251 cells, and HepG2 cells as well as orchiectomized growth hormone receptor knockout (GHR-KO) mice and rats. Concentration-time curves of tramadol in rat brain were determined using a microdialysis technique. The analgesic action of tramadol was assessed by the tail-flick test in rats.

KEY RESULTS

miR-101 and miR-128-2 bound the 3'-untranslated region of the CYP2D6 mRNA and decreased its level. Testosterone decreased CYP2D6 catalytic function via the up-regulation of miR-101 and miR-128-2 in SH-SY5Y and U251 cells, but not in HepG2 cells. Orchiectomy decreased the levels of miR-101 and miR-128-2 in the hippocampus of male GHR-KO mice, indicating that androgens regulate miRNAs directly, not via the alteration of growth hormone secretion patterns. Changes in the pharmacokinetic and pharmacodynamic profiles of tramadol by orchiectomy was attenuated by either testosterone supplementation or a specific brain CYP2D inhibitor.

CONCLUSIONS AND IMPLICATIONS

The selective regulation of brain CYP2D via brain-enriched miRNAs, following changes in androgen levels, such as in testosterone therapy, androgen deprivation therapy and/or ageing may alter the response to centrally active substances.

Assessing the Risks Associated with Antidepressant Use in Plastic Surgery: A Systematic Review

BACKGROUND

Antidepressant use has increased dramatically over the past decade. Although there is no question about the benefits of these medications, uncertainty exists with regard to the implications of antidepressant treatment surrounding plastic surgery. This systematic review collates all of the available literature that evaluates the risks of patient antidepressant treatment, in relation to plastic surgery.

METHODS

A comprehensive literature review of the PubMed and Cochrane databases was conducted. Articles were assessed by two independent reviewers using predefined data fields and selected using specific inclusion criteria. The two authors independently reviewed the literature and extracted data from included reviews, and discrepancies were resolved by consensus.

RESULTS

Twenty-six articles were included in the analysis and were categorized into five groups for comparison: risk of bleeding, risk of breast cancer, risk of breast cancer recurrence, breast enlargement, and miscellaneous (unique complications). Extracted information included study type, statistical analyses, conclusion, and limitations.

CONCLUSIONS

This review does not support the cessation of antidepressants in patients before plastic surgery, as the numbers needed to harm are low and the implications of withdrawal may prove to be detrimental to postoperative management. However, the use of antidepressants for mental disorders may also implicate key patient risk factors for surgical complications, and sufficient exploration into the patient's indications for the prescription is crucial. Evidence so far does not suggest that antidepressants increase the risk of breast cancer or recurrence in general, but caution should be exercised for those specifically on concurrent tamoxifen and paroxetine treatment.

Determination of a Degradation Constant for CYP3A4 by Direct Suppression of mRNA in a Novel Human Hepatocyte Model, HepatoPac

Accurate determination of rates of de novo synthesis and degradation of cytochrome P450s (P450s) has been challenging. There is a high degree of variability in the multiple published values of turnover for specific P450s that is likely exacerbated by differences in methodologies. For CYP3A4, reported half-life values range from 10 to 140 hours. An accurate value for kdeg has been identified as a major limitation for prediction of drug interactions involving mechanism-based inhibition and/or induction. Estimation of P450 half-life from in vitro test systems, such as human hepatocytes, is complicated by differential decreased enzyme function over culture time, attenuation of the impact of enzyme loss through inclusion of glucocorticoids in media, and viability limitations over long-term culture times. HepatoPac overcomes some of these challenges by providing extended stability of enzymes (2.5 weeks in our hands). As such it is a unique tool for studying rates of enzyme degradation achieved through modulation of enzyme levels. CYP3A4 mRNA levels were rapidly depleted by >90% using either small interfering RNA or addition of interleukin-6, which allowed an estimation of the degradation rate constant for CYP3A protein over an incubation time of 96 hours. The degradation rate constant of 0.0240 ± 0.005 hour(-1) was reproducible in hepatocytes from five different human donors. These donors also reflected the overall population with respect to CYP3A5 genotype. This methodology can be applied to additional enzymes and may provide a more accurate in vitro derived kdeg value for predicting clinical drug-drug interaction outcomes.

Farnesoid X Receptor Agonist Represses Cytochrome P450 2D6 Expression by Upregulating Small Heterodimer Partner

Cytochrome P450 2D6 (CYP2D6) is a major drug-metabolizing enzyme responsible for eliminating approximately 20% of marketed drugs. Studies have shown that differential transcriptional regulation of CYP2D6 may contribute to large interindividual variability in CYP2D6-mediated drug metabolism. However, the factors governing CYP2D6 transcription are largely unknown. We previously demonstrated small heterodimer partner (SHP) as a novel transcriptional repressor of CYP2D6 expression. SHP is a representative target gene of the farnesoid X receptor (FXR). The objective of this study is to investigate whether an agonist of FXR, 3-(2,6-dichlorophenyl)-4-(3'-carboxy-2-chlorostilben-4-yl)oxymethyl-5-isopropylisoxazole (GW4064), alters CYP2D6 expression and activity. In CYP2D6-humanized transgenic mice, GW4064 decreased hepatic CYP2D6 expression and activity (by 2-fold) while increasing SHP expression (by 2-fold) and SHP recruitment to the CYP2D6 promoter. CYP2D6 repression by GW4064 was abrogated in Shp(-/-);CYP2D6 mice, indicating a critical role of SHP in CYP2D6 regulation by GW4064. Also, GW4064 decreased CYP2D6 expression (by 2-fold) in primary human hepatocytes, suggesting that the results obtained in CYP2D6-humanized transgenic mice can be translated to humans. This proof of concept study provides evidence for CYP2D6 regulation by an inducer of SHP expression, namely, the FXR agonist GW4064.

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

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

Predicting toxicities of reactive metabolite-positive drug candidates

Because of the inability to predict and quantify the risk of idiosyncratic adverse drug reactions (IADRs) and because reactive metabolites (RMs) are thought to be responsible for the pathogenesis of some IADRs, the potential for RM formation within new chemical entities is routinely examined with the ultimate goal of eliminating or reducing the liability through iterative design. Likewise, avoidance of structural alerts is almost a standard practice in drug design. However, the perceived safety concerns associated with the use of structural alerts and/or RM screening tools as standalone predictors of toxicity risks may be overexaggerated. Numerous marketed drugs form RMs but do not cause idiosyncratic toxicity. In this review article, we present a critique of the structural alert/RM concept as applied in drug discovery and evaluate the evidence linking structural alerts and RMs to observed toxic effects. Pragmatic risk mitigation strategies to aid the advancement of drug candidates that carry a RM liability are also discussed.

The Influence of Bioisosteres in Drug Design: Tactical Applications to Address Developability Problems

The application of bioisosteres in drug discovery is a well-established design concept that has demonstrated utility as an approach to solving a range of problems that affect candidate optimization, progression, and durability. In this chapter, the application of isosteric substitution is explored in a fashion that focuses on the development of practical solutions to problems that are encountered in typical optimization campaigns. The role of bioisosteres to affect intrinsic potency and selectivity, influence conformation, solve problems associated with drug developability, including P-glycoprotein recognition, modulating basicity, solubility, and lipophilicity, and to address issues associated with metabolism and toxicity is used as the underlying theme to capture a spectrum of creative applications of structural emulation in the design of drug candidates.

Irreversible enzyme inhibition kinetics and drug-drug interactions

This chapter describes the types of irreversible inhibition of drug-metabolizing enzymes and the methods commonly employed to quantify the irreversible inhibition and subsequently predict the extent and time course of clinically important drug-drug interactions.

The endogenous substrates of brain CYP2D

CYP2D6, one of the major cytochrome P450 isoforms present in the human brain, is associated with the incidence and prevalence of central nervous system (CNS) diseases. Human CYP2D6 and rat CYP2D are involved in the metabolism of various neurotransmitters and neurosteroids. Brain CYP2D can be regulated by endogenous steroids, including sex hormones. The alteration of CYP2D-mediated metabolism induced by endogenous steroids may cause changes in sensitivity to environmental and industrial toxins and carcinogens as well as physiological and pathophysiological processes controlled by biologically active compounds. This review summarizes the current knowledge regarding the distribution, endogenous substrates, and regulation of brain CYP2D.

Predicting drug-drug interactions: application of physiologically based pharmacokinetic models under a systems biology approach

The development of in vitro-in vivo extrapolation (IVIVE), a 'bottom-up' approach, to predict pharmacokinetic parameters and drug-drug interactions (DDIs) has accelerated mainly due to an increase in the understanding of the multiple mechanisms involved in these interactions and the availability of appropriate in vitro systems that act as surrogates for delineating various elements of the interactions relevant to absorption, distribution, metabolism and elimination. Recent advances in the knowledge of the population variables required for IVIVE (demographic, anatomical, genetic and physiological parameters) have also contributed to the appreciation of the sources of variability and wider use of this approach for different scenarios within the pharmaceutical industry. Initially, the authors present an overview of the integration of IVIVE into 'static' and 'dynamic' models for the quantitative prediction of DDIs. The main purpose of this review is to discuss the application of IVIVE in conjunction with physiologically based pharmacokinetic modeling under a systems biology approach to characterize the potential DDIs in individual patients, including those who cannot be investigated in formal clinical trials for ethical reasons. In addition, we address the issues related to the prediction of complex DDIs involving the inhibition of cytochrome P- and transporter-mediated activities through multiple drugs.

A physiologically based pharmacokinetic model to predict disposition of CYP2D6 and CYP1A2 metabolized drugs in pregnant women

Conducting pharmacokinetic (PK) studies in pregnant women is challenging. Therefore, we asked if a physiologically based pharmacokinetic (PBPK) model could be used to evaluate different dosing regimens for pregnant women. We refined and verified our previously published pregnancy PBPK model by incorporating cytochrome P450 CYP1A2 suppression (based on caffeine PK) and CYP2D6 induction (based on metoprolol PK) into the model. This model accounts for gestational age-dependent changes in maternal physiology and hepatic CYP3A activity. For verification, the disposition of CYP1A2-metabolized drug theophylline (THEO) and CYP2D6-metabolized drugs paroxetine (PAR), dextromethorphan (DEX), and clonidine (CLO) during pregnancy was predicted. Our PBPK model successfully predicted THEO disposition during the third trimester (T3). Predicted mean postpartum to third trimester (PP:T3) ratios of THEO area under the curve (AUC), maximum plasma concentration, and minimum plasma concentration were 0.76, 0.95, and 0.66 versus observed values 0.75, 0.89, and 0.72, respectively. The predicted mean PAR steady-state plasma concentration (Css) ratio (PP:T3) was 7.1 versus the observed value 3.7. Predicted mean DEX urinary ratio (UR) (PP:T3) was 2.9 versus the observed value 1.9. Predicted mean CLO AUC ratio (PP:T3) was 2.2 versus the observed value 1.7. Sensitivity analysis suggested that a 100% induction of CYP2D6 during T3 was required to recover the observed PP:T3 ratios of PAR Css, DEX UR, and CLO AUC. Based on these data, it is prudent to conclude that the magnitude of hepatic CYP2D6 induction during T3 ranges from 100 to 200%. Our PBPK model can predict the disposition of CYP1A2, 2D6, and 3A drugs during pregnancy.

Prolonged Drug-Drug Interaction between Terbinafine and Perphenazine

I report here an elderly woman receiving perphenazine together with terbinafine. After 1 week of terbinafine treatment she experienced extrapyramidal symptoms and, in particular, akathisia. Her symptoms did not disappear for 6 weeks, and so at 2 weeks prior to this most recent admission she had stopped taking terbinafine. However, these symptoms persisted for 3 weeks after discontinuing terbinafine. It is well known that terbinafine inhibits CYP2D6 and that perphenazine is metabolized mainly by CYP2D6. Thus, when terbinafine and perphenazine are coadministrated, the subsequent increase in the concentration of perphenazine may induce extrapyramidal symptoms. Thus, terbinafine therapy may be associated with the induction and persistence of extrapyramidal symptoms, including akathisia. This case report emphasizes the importance of monitoring drug-drug interactions in patients undergoing terbinafine and perphenazine therapy.

Predicting drug interaction potential with a physiologically based pharmacokinetic model: a case study of telithromycin, a time-dependent CYP3A inhibitor

Telithromycin is a substrate and an inhibitor of cytochrome P450 3A (CYP3A4), with dose- and time-dependent nonlinear pharmacokinetics (PK). We hypothesized that the time-dependent inhibition (TDI) of CYP3A4 was responsible for the nonlinear PK of telithromycin and then used physiologically based PK (PBPK) modeling and simulation to verify this mechanism. Telithromycin PBPK models integrating in vitro, in silico, and in vivo PK data ruled out the contribution of enzyme/transporter saturation and suggested that TDI is a plausible mechanism for PK nonlinearity. The model successfully predicted the clinical interaction with the CYP3A4 substrate midazolam, as verified by external data not used for the model-building (intravenous (i.v.) and oral (p.o.) midazolam area under the concentration-time curve (AUC) ratio with/without concurrent telithromycin administration: 3.26 and 6.72 predicted vs. 2.20 and 6.11 observed, respectively). Models assuming reversible inhibition failed to predict such strong CYP3A4 inhibition. In the absence of in vitro TDI data, a PBPK model can be used to incorporate TDI mechanisms based on nonlinear PK data to predict clinical drug-drug interactions.

Structural alert/reactive metabolite concept as applied in medicinal chemistry to mitigate the risk of idiosyncratic drug toxicity: a perspective based on the critical examination of trends in the top 200 drugs marketed in the United States

Because of a preconceived notion that eliminating reactive metabolite (RM) formation with new drug candidates could mitigate the risk of idiosyncratic drug toxicity, the potential for RM formation is routinely examined as part of lead optimization efforts in drug discovery. Likewise, avoidance of "structural alerts" is almost a norm in drug design. However, there is a growing concern that the perceived safety hazards associated with structural alerts and/or RM screening tools as standalone predictors of toxicity risks may be over exaggerated. In addition, the multifactorial nature of idiosyncratic toxicity is now well recognized based upon observations that mechanisms other than RM formation (e.g., mitochondrial toxicity and inhibition of bile salt export pump (BSEP)) also can account for certain target organ toxicities. Hence, fundamental questions arise such as: When is a molecule that contains a structural alert (RM positive or negative) a cause for concern? Could the molecule in its parent form exert toxicity? Can a low dose drug candidate truly mitigate metabolism-dependent and -independent idiosyncratic toxicity risks? In an effort to address these questions, we have retrospectively examined 68 drugs (recalled or associated with a black box warning due to idiosyncratic toxicity) and the top 200 drugs (prescription and sales) in the United States in 2009 for trends in physiochemical characteristics, daily doses, presence of structural alerts, evidence for RM formation as well as toxicity mechanism(s) potentially mediated by parent drugs. Collectively, our analysis revealed that a significant proportion (∼78-86%) of drugs associated with toxicity contained structural alerts and evidence indicating that RM formation as a causative factor for toxicity has been presented in 62-69% of these molecules. In several cases, mitochondrial toxicity and BSEP inhibition mediated by parent drugs were also noted as potential causative factors. Most drugs were administered at daily doses exceeding several hundred milligrams. There was no obvious link between idiosyncratic toxicity and physicochemical properties such as molecular weight, lipophilicity, etc. Approximately half of the top 200 drugs for 2009 (prescription and sales) also contained one or more alerts in their chemical architecture, and many were found to be RM-positive. Several instances of BSEP and mitochondrial liabilities were also noted with agents in the top 200 category. However, with relatively few exceptions, the vast majority of these drugs are rarely associated with idiosyncratic toxicity, despite years of patient use. The major differentiating factor appeared to be the daily dose; most of the drugs in the top 200 list are administered at low daily doses. In addition, competing detoxication pathways and/or alternate nonmetabolic clearance routes provided suitable justifications for the safety records of RM-positive drugs in the top 200 category. Thus, while RM elimination may be a useful and pragmatic starting point in mitigating idiosyncratic toxicity risks, our analysis suggests a need for a more integrated screening paradigm for chemical hazard identification in drug discovery. Thus, in addition to a detailed assessment of RM formation potential (in relationship to the overall elimination mechanisms of the compound(s)) for lead compounds, effects on cellular health (e.g., cytotoxicity assays), BSEP inhibition, and mitochondrial toxicity are the recommended suite of assays to characterize compound liabilities. However, the prospective use of such data in compound selection will require further validation of the cellular assays using marketed agents. Until we gain a better understanding of the pathophysiological mechanisms associated with idiosyncratic toxicities, improving pharmacokinetics and intrinsic potency as means of decreasing the dose size and the associated "body burden" of the parent drug and its metabolites will remain an overarching goal in drug discovery.

The relationship between clinical pharmacokinetics of aripiprazole and CYP2D6 genetic polymorphism: effects of CYP enzyme inhibition by coadministration of paroxetine or fluvoxamine

Purpose

To investigate the effects of coadministration of paroxetine or fluvoxamine on the pharmacokinetics of aripiprazole in healthy adult Japanese with different CYP2D6 genotypes.

Methods

Fourteen CYP2D6 extensive metabolizer (EM) and 14 CYP2D6 intermediate metabolizer (IM) subjects were coadministered a single oral dose of aripiprazole 3 mg after steady-state plasma concentrations of the SSRIs paroxetine (20 mg/day) or fluvoxamine (100 mg/day) were reached by repeated oral doses for 6–7 days. The pharmacokinetics of aripiprazole with and without coadministration of SSRIs were compared according to CYP2D6 genotypes.

Results

Coadministration of paroxetine, a potent CYP2D6 inhibitor, decreased systemic clearance (CL/F) of aripiprazole by 58 and 23% in CYP2D6 EMs and IMs, respectively, demonstrating that the percentage inhibition of CYP2D6 activity by coadministration of paroxetine was apparently greater in CYP2D6 EMs than in IMs. Coadministration of fluvoxamine, a less potent CYP3A4 inhibitor, decreased the CL/F of aripiprazole by 39% in CYP2D6 EMs and 40% in IMs, indicating the same inhibitory effect on CYP enzymes, regardless of the CYP2D6 genotype. Percent contribution of CYP2D6 to total CL/F (CYP2D6 plus CYP3A4) of aripiprazole estimated as a reduced percentage of CL/F by CYP enzyme inhibition was 62% for CYP2D6 EMs and 24% for IMs in paroxetine coadministration, and 40% for CYP2D6 EMs and 18% for IMs in fluvoxamine coadministration.

Conclusions

There were marked differences in the degree of influence of paroxetine coadministration on the pharmacokinetics of aripiprazole between CYP2D6 EMs and IMs, but no apparent differences were found between two CYP2D6 genotypes in fluvoxamine coadministration. Aripiprazole can be used safely in combination with SSRIs that have a CYP enzyme-inhibitory action.

Consideration of reliable concentrations for prediction of change in enzyme activity by mechanism-based inactivation using physiologically-based pharmacokinetic model simulations

Using physiologically-based pharmacokinetic model simulations with the assumption that elimination of inactivator is not altered by mechanism-based inactivation (MBI) of the target enzyme, we examined at what concentrations the influence of MBI could be accurately and simply predicted. The method utilizing maximum unbound systemic concentration as the inactivator concentration (method 1) tended to overestimate this influence, and accuracy expressed as the ratio of estimated and exact fold decrease in enzyme activity ranged from 0.80 to 8.41. In addition, when the volume of distribution was large or the absorption rate constant was small, method 1 provided relatively precise estimation, with the ratio of nearly 1. We propose use of two concentrations, the steady-state average unbound liver concentration and maximum limit of steady-state average unbound liver concentration, to predict the effects of MBI. The accuracy of prediction of MBI using these two concentrations ranged from 0.90 to 1.04 and 0.92 to 2.96, respectively, and was higher than that with method 1. These two concentrations can be obtained early in the drug development process, and estimated results can be expected to contribute to determination of the effects of MBI.