An in vitro mechanistic study to elucidate the desipramine/bupropion clinical drug-drug interaction

Current Utilization of Bupropion Treatment in Children, Young Adults, and Adults in the United States

Introduction: While available for decades, the use of bupropion has increased in recent years. To provide an updated review on the use of bupropion, this article aimed to describe bupropion prescription details, potential indication, and treatment duration in children, young adults, and adults starting bupropion treatment. Methods: Individuals aged 6-64 newly initiating bupropion hydrochloride treatment were identified from commercial claims data (MarketScan, 1/1/2016-12/31/2022). New bupropion use was defined as at least 1 year without any prior bupropion dispensed prescription. Potential indications for bupropion treatment were identified from inpatient/outpatient records (ICD-10-CM diagnoses) in the 30 days prior to bupropion initiation. All analyses were stratified by age: children (6-17 years), young adults (18-29 years), and adults (30-64 years) and treatment duration up to 1 year was estimated with Kaplan-Meier estimation. Results: The study sample included 39,833 children, 177,710 young adults, and 548,557 adults newly initiating bupropion treatment. Bupropion extended-release 24-hour 150 mg was the most common (62%) formulation and dose at initiation. Depression was the most prevalent potential indication (children = 57%, young adults = 47%, adults = 36%) and attention-deficit/hyperactivity disorder (ADHD) was the next most common potential indication in children (25%) and young adults (12%); tobacco cessation and weight loss also identified as potential indications. Twenty-two percent of bupropion initiators were on concurrent selective serotonin reuptake inhibitor treatment. In children, suicidal ideation (16.3%), poisoning (5.9%), and anorexia or bulimia nervosa (2.2%) were relatively common diagnoses prior to bupropion initiation. Overall, 39%-45% remained on bupropion treatment for at least 6 months, with variation by potential indication. Conclusion: The antidepressant bupropion is prescribed to children, young adults, and adults for a variety of indications in the United States, with depression and ADHD the most common indications in children. As the prescribing of bupropion becomes more widespread, additional safety and effectiveness data will be necessary to inform prescribing decisions, particularly in populations with unknown efficacy.

Role of vesicular monoamine transporter-2 for treating attention deficit hyperactivity disorder: a review

RATIONALE

The Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) classifies attention deficit hyperactivity disorder (ADHD) as a neurodevelopmental disorder that interferes with human functioning and development. As the clinical presentation of ADHD involves a deficiency in executive function, neurocognitive deficits involving distinctive neuropathological changes must be present for clinical diagnosis.

OBJECTIVES

The vesicular monoamine transporter (VMAT), specifically VMAT-2, plays a role in ADHD pathogenesis. In addition, experimental data show that the stimulants (amphetamines and methylphenidate) are first-line treatments for the condition because of their extensive interaction with VMAT-2. The interactions of peptides, bupropion, and nutritional supplements with VMAT-2 receptors have been researched, but more evidence is needed to elucidate their pharmacodynamic properties. Therefore, this literature review evaluated the current pharmacological treatment modalities, peptides, and nutritional supplements for ADHD that target the VMAT-2 system.

METHODS, RESULTS, AND CONCLUSIONS

We obtained relevant studies from several platforms, including the National Center for Biotechnology, Clinical Key, Access Medicine, and PubMed. From the results of these studies, we observed that stimulants interact highly with the VMAT-2 transporter, with omega-3 fatty acids, peptides, and bupropion exerting some modulatory activity on VMAT-2. These agents should be considered for the future treatment of ADHD, although clinical-level research involving human participants is necessary.

Bupropion Increased More than Five Times the Systemic Exposure to Aripiprazole: An In Vivo Study in Wistar albino Rats

Background/Objectives: In psychiatric disorders, antipsychotics and antidepressant medication are often administered together. Aripiprazole, a third-generation antipsychotic drug, is extensively metabolized by CYP2D6 and CYP3A4 isoenzymes, while bupropion, used in depressive disorders, is known as a moderate or strong CYP2D6 enzyme inhibitor. This in vivo experiment aimed to assess the presence of a pharmacokinetic drug interaction between aripiprazole and bupropion and its magnitude on the systemic exposure of aripiprazole. Methods: 24 healthy Wistar albino male rats were included in two study groups. A single dose of 8 mg/kg aripiprazole was given to rats in the reference group, while the test group received repeated doses of bupropion for 6 days, followed by a single dose of aripiprazole. An LC-MS/MS method was developed for the concomitant quantification of aripiprazole and its active metabolite, dehydroaripiprazole, and non-compartmental analysis was employed to assess their pharmacokinetic parameters. Results: The mean AUC0-∞ of aripiprazole increased 5.65-fold (1117.34 ± 931.41 vs. 6311.66 ± 2978.71 hr·ng/mL), the mean Cmax increased by 96.76% and the apparent systemic clearance decreased over 9-fold after bupropion repeated doses. The exposure to aripiprazole's active metabolite increased as well, having a 4-fold increase in the mean AUC0-∞ (from 461.13 ± 339.82 to 1878.66 ± 1446.91 hr·ng/mL) and a 2-fold increase in the mean Cmax. Conclusions: The total exposure to the aripiprazole parent compound and active moiety significantly increased after bupropion pretreatment in this preclinical in vivo experiment. Clinical studies should further establish the significance of this interaction in humans.

A Review of CYP-Mediated Drug Interactions: Mechanisms and In Vitro Drug-Drug Interaction Assessment

Drug metabolism is a major determinant of drug concentrations in the body. Drug-drug interactions (DDIs) caused by the co-administration of multiple drugs can lead to alteration in the exposure of the victim drug, raising safety or effectiveness concerns. Assessment of the DDI potential starts with in vitro experiments to determine kinetic parameters and identify risks associated with the use of comedication that can inform future clinical studies. The diverse range of experimental models and techniques has significantly contributed to the examination of potential DDIs. Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of many drugs on the market, making them frequently implicated in drug metabolism and DDIs. Consequently, there has been a growing focus on the assessment of DDI risk for CYPs. This review article provides mechanistic insights underlying CYP inhibition/induction and an overview of the in vitro assessment of CYP-mediated DDIs.

Biotransformation research advances - 2022 year in review

This annual review is the eighth of its kind since 2016 (Baillie et al. 2016, Khojasteh et al. 2017, Khojasteh et al. 2018, Khojasteh et al. 2019, Khojasteh et al. 2020, Khojasteh et al. 2021, Khojasteh et al. 2022). Our objective is to explore and share articles which we deem influential and significant in the field of biotransformation.

Stereoselective Metabolism of Bupropion to Active Metabolites in Cellular Fractions of Human Liver and Intestine

Striking stereoselective disposition of the antidepressant and smoking cessation aid bupropion (BUP) and its active metabolites observed clinically influence patients' response to BUP therapy and its clinically important drug-drug interactions (DDI) with CYP2D6 substrates. However, understanding of the biochemical mechanisms responsible is incomplete. This study comprehensively examined hepatic and extrahepatic stereoselective metabolism of BUP in vitro Racemic-, R-, and S-BUP were incubated separately with pooled cellular fractions of human liver [microsomes (HLMs), S9 fractions (HLS9s), and cytosols (HLCs)] and intestinal [microsomes (HIMs), S9 fractions (HIS9s), and cytosols (HICs)] and cofactors. Formations of diastereomers of 4-hydroxyBUP (OHBUP), threohydroBUP (THBUP), and erythrohydroBUP (EHBUP) were quantified using a novel chiral ultra-high performance liquid chromatography/tandem mass spectrometry method. Racemic BUP (but not R- or S-BUP) was found suitable to determine stereoselective metabolism of BUP; both enantiomers showed complete racemization. Compared with that of RR-THBUP, the in vitro intrinsic clearance (Clint) for the formation of SS-THBUP was 42-, 19-, and 8.3-fold higher in HLMs, HLS9 fractions, and HLCs, respectively; Clint for the formation of SS-OHBUP and RS-EHBUP was also higher (2.7- to 3.9-fold) than their R-derived counterparts. In cellular fractions of human intestine, ≥ 95% of total reduction was accounted by the formation of RR-THBUP. Ours is the first to demonstrate marked stereoselective reduction of BUP in HLCs, HIMs, HIS9 fractions, and HICs, providing the first evidence for tissue- and cellular fraction-dependent stereoselective metabolism of BUP. These data may serve as the first critical step toward understanding factors dictating BUP's stereoselective disposition, effects, and DDI risks. SIGNIFICANCE STATEMENT: This work provides a deeper insight into bupropion (BUP) stereoselective oxidation and reduction to active metabolites in cellular fractions of human liver and intestine tissues. The results demonstrate tissue- and cellular fraction-dependent stereospecific metabolism of BUP. These data may improve prediction of BUP stereoselective disposition and understanding of BUP's effects and CYP2D6-dependent drug-drug interaction in vivo.

Do Inhibitory Metabolites Impact DDI Risk Assessment? Analysis of in vitro and in vivo Data from NDA Reviews Between 2013 and 2018

Evaluating the potential of new drugs and their metabolites to cause drug-drug interactions (DDIs) is critical for understanding drug safety and efficacy. Although multiple analyses of proprietary metabolite testing data have been published, no systematic analyses of metabolite data collected according to current testing criteria have been conducted. To address this knowledge gap, 120 new molecular entities approved between 2013 and 2018 were reviewed. Comprehensive data on metabolite-to-parent area under the curve ratios (AUC_M /AUC_P ), inhibitory potency of parent and metabolites, and clinical DDIs were collected. Sixty-four percent of the metabolites quantified in vivo had AUC_M /AUC_P  ≥ 0.25 and 75% of these metabolites were tested for cytochrome P450 (CYP) inhibition in vitro, resulting in 15 metabolites with potential DDI risk identification. Although 50% of the metabolites with AUC_M /AUC_P  < 0.25 were also tested in vitro, none of them showed meaningful CYP inhibition potential. The metabolite percentage of plasma total radioactivity cutoff of ≥ 10% did not appear to add value to metabolite testing strategies. No relationship between metabolite versus parent drug polarity and inhibition potency was observed. Comparison of metabolite and parent maximum concentration (C_max ) divided by inhibition constant (K_i ) values suggested that metabolites can contribute to in vivo DDIs and, hence, quantitative prediction of clinical DDI magnitude may require both parent and metabolite data. This systematic analysis of metabolite data for newly approved drugs supports an AUC_M /AUC_P cutoff of ≥ 0.25 to warrant metabolite in vitro CYP screening to adequately characterize metabolite inhibitory DDI potential and support quantitative DDI predictions.

Dose-Dependent Inhibition of CYP2D6 by Bupropion in Patients With Depression

PURPOSE

The aim of this study was to investigate the potential dose-dependent CYP2D6 inhibition by bupropion (BUP) in patients with depression.

METHODS

Patients combining BUP with venlafaxine were included from a therapeutic drug monitoring (TDM) database at the Diakonhjemmet Hospital (Oslo, Norway). The O/N-desmethylvenlafaxine metabolic ratio measured in TDM samples was used as a biomarker for CYP2D6 phenotype and was compared between patients treated with BUP 150 mg/d and 300 mg/d or greater. In addition, reference groups of venlafaxine-treated patients genotyped as CYP2D6 poor metabolizers (PMs, no CYP2D6 activity) and normal metabolizers (NMs, fully functional CYP2D6 activity) were included.

FINDINGS

A total of 221 patients were included in the study. The median O/N-desmethylvenlafaxine metabolic ratio was significantly higher in patients treated with BUP 150 mg/d (n = 59) versus 300 mg/d or greater (n = 34, 1.77 vs 0.96, P < 0.001). In CYP2D6 NMs (n = 62) and PMs (n = 66), the median metabolic ratios were 40.55 and 0.48, respectively. For patients treated with BUP 150 mg/d, 11 (19%) of the 59 patients were phenoconverted to PMs, whereas this was the case for 17 (50%) of the 34 patients treated with BUP 300 mg/d or greater.

CONCLUSIONS

Bupropion exhibits a clear dose-dependent CYP2D6 inhibitory effect during treatment of patients with depression. This finding is of clinical relevance when adjusting dosing of CYP2D6 substrates during comedication with BUP. Half of the patients treated with high-dose BUP are converted to CYP2D6 PM phenotype. Because of the variability in CYP2D6 inhibition, TDM of CYP2D6 substrates should be considered to provide individualized dose adjustments during comedication with BUP.

Physiologically Based Pharmacokinetic Modeling of Bupropion and Its Metabolites in a CYP2B6 Drug-Drug-Gene Interaction Network

The noradrenaline and dopamine reuptake inhibitor bupropion is metabolized by CYP2B6 and recommended by the FDA as the only sensitive substrate for clinical CYP2B6 drug-drug interaction (DDI) studies. The aim of this study was to build a whole-body physiologically based pharmacokinetic (PBPK) model of bupropion including its DDI-relevant metabolites, and to qualify the model using clinical drug-gene interaction (DGI) and DDI data. The model was built in PK-Sim® applying clinical data of 67 studies. It incorporates CYP2B6-mediated hydroxylation of bupropion, metabolism via CYP2C19 and 11β-HSD, as well as binding to pharmacological targets. The impact of CYP2B6 polymorphisms is described for normal, poor, intermediate, and rapid metabolizers, with various allele combinations of the genetic variants CYP2B6*1, *4, *5 and *6. DDI model performance was evaluated by prediction of clinical studies with rifampicin (CYP2B6 and CYP2C19 inducer), fluvoxamine (CYP2C19 inhibitor) and voriconazole (CYP2B6 and CYP2C19 inhibitor). Model performance quantification showed 20/20 DGI ratios of hydroxybupropion to bupropion AUC ratios (DGI AUCHBup/Bup ratios), 12/13 DDI AUCHBup/Bup ratios, and 7/7 DDGI AUCHBup/Bup ratios within 2-fold of observed values. The developed model is freely available in the Open Systems Pharmacology model repository.

Reversible Mechanisms of Enzyme Inhibition and Resulting Clinical Significance

Inhibition of a drug-metabolizing enzyme by the reversible interaction of a drug with the enzyme, thus decreasing the metabolism of another drug, is a major cause of clinically significant drug-drug interactions. This chapter defines the four reversible mechanisms of inhibition exhibited by drugs: competitive, noncompetitive, uncompetitive, and mixed competitive/noncompetitive. An in vitro procedure to determine the potential of a drug to be a reversible inhibitor is also provided. Finally, a number of examples of clinically significant drug-drug interactions resulting from reversible inhibition are described.

A Review: Effects of Macrolides on CYP450 Enzymes

As a kind of haemoglobin, cytochrome P450 enzymes (CYP450) participate in the metabolism of many substances, including endogenous substances, exogenous substances and drugs. It is estimated that 60% of common prescription drugs require bioconversion through CYP450. The influence of macrolides on CYP450 contributes to the metabolism and drug-drug interactions (DDIs) of macrolides. At present, most studies on the effects of macrolides on CYP450 are focused on CYP3A, but a few exist on other enzymes and drug combinations, such as telithromycin, which can decrease the activity of hepatic CYP1A2 and CYP3A2. This article summarizes some published applications of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. And the article may subsequently guide the rational use of drugs in clinical trials. To a certain extent, poisoning caused by adverse drug interactions can be avoided. Unreasonable use of macrolide antibiotics may enable the presence of residue of macrolide antibiotics in animal-origin food. It is unhealthy for people to eat food with macrolide antibiotic residues. So it is of great significance to guarantee food safety and protect the health of consumers by the rational use of macrolides. This review gives a detailed description of the influence of macrolides on CYP450 and the DDIs of macrolides caused by CYP450. Moreover, it offers a perspective for researchers to further explore in this area.

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.

Serotonin Toxicity: Associated Agents and Clinical Characteristics

BACKGROUND

Serotonin toxicity is a common cause of drug-induced altered mental status. However, data on the causes of serotonin toxicity, symptomatology, complications, and rate of antidotal treatment are limited.

METHODS

This study evaluated cases of serotonin toxicity in the ToxIC registry, an international database of prospectively collected cases seen by medical toxicologists. Serotonin toxicity was diagnosed by bedside evaluation of medical toxicology specialists and explicit criteria were not used. The database was searched for "serotonin syndrome" between January 1, 2010, and December 31, 2016.

RESULTS

There were 1010 cases included. Females made up 608 (60%) cases. Ages are as follows: younger than 2 years (3, 0.3%), 2 to 6 years (8, 0.8%), 7 to 12 years (9, 0.9%), 13 to 18 years (276, 27.3%), 19 to 65 years (675, 67%), older than 66 years (33, 3.4%), unknown (6, 0.6%). Reasons for encounter: intentional (768, 76%), adverse drug event/reaction (127, 12.6%), unintentional (66, 6%), and unknown (55, 5.4%). Signs/symptoms: hyperreflexia/clonus/myoclonus (601, 59.5%), agitation (337, 33.4%), tachycardia (256, 25.3%), rigidity (140, 13.9%), seizures (139, 13.7%), and hyperthermia (29, 2.9%).

COMPLICATIONS

rhabdomyolysis (97, 9.7%), dysrhythmias (8, 0.8%), and death (1, 0.1%).

TREATMENTS

benzodiazepines 67% (677/1010), cyproheptadine 15.1% (153/1010). There were 192 different xenobiotics reported with 2046 total exposures. Antidepressants were most common (915, 44.7%) with bupropion the most frequent overall (147, 7.2%). Common non-antidepressants were dextromethorphan (95, 6.9%), lamotrigine (64, 3.1%), and tramadol (60, 2.9%).

DISCUSSION

Serotonin toxicity most often occurred in adult patients with intentional overdose. Antidepressants were the most common agents of toxicity. Interestingly, bupropion, a norepinephrine/dopamine reuptake inhibitor, was the most frequently mentioned xenobiotic. Though often cited as a potential antidote, only 15% of patients received cyproheptadine. Severe toxicity was rare. A single death was reported.

DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening

Accurate identification of compound–protein interactions (CPIs) in silico may deepen our understanding of the underlying mechanisms of drug action and thus remarkably facilitate drug discovery and development. Conventional similarity- or docking-based computational methods for predicting CPIs rarely exploit latent features from currently available large-scale unlabeled compound and protein data and often limit their usage to relatively small-scale datasets. In the present study, we propose DeepCPI, a novel general and scalable computational framework that combines effective feature embedding (a technique of representation learning) with powerful deep learning methods to accurately predict CPIs at a large scale. DeepCPI automatically learns the implicit yet expressive low-dimensional features of compounds and proteins from a massive amount of unlabeled data. Evaluations of the measured CPIs in large-scale databases, such as ChEMBL and BindingDB, as well as of the known drug–target interactions from DrugBank, demonstrated the superior predictive performance of DeepCPI. Furthermore, several interactions among small-molecule compounds and three G protein-coupled receptor targets (glucagon-like peptide-1 receptor, glucagon receptor, and vasoactive intestinal peptide receptor) predicted using DeepCPI were experimentally validated. The present study suggests that DeepCPI is a useful and powerful tool for drug discovery and repositioning. The source code of DeepCPI can be downloaded from https://github.com/FangpingWan/DeepCPI.

Prediction of Drug-Drug Interactions with Bupropion and Its Metabolites as CYP2D6 Inhibitors Using a Physiologically-Based Pharmacokinetic Model

The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model for bupropion and its three primary metabolites—hydroxybupropion, threohydrobupropion and erythrohydrobupropion—based on a mixed “bottom-up” and “top-down” approach and to contribute to the understanding of the involvement and impact of inhibitory metabolites for DDIs observed in the clinic. PK profiles from clinical researches of different dosages were used to verify the bupropion model. Reasonable PK profiles of bupropion and its metabolites were captured in the PBPK model. Confidence in the DDI prediction involving bupropion and co-administered CYP2D6 substrates could be maximized. The predicted maximum concentration (C_max) area under the concentration-time curve (AUC) values and C_max and AUC ratios were consistent with clinically observed data. The addition of the inhibitory metabolites into the PBPK model resulted in a more accurate prediction of DDIs (AUC and C_max ratio) than that which only considered parent drug (bupropion) P450 inhibition. The simulation suggests that bupropion and its metabolites contribute to the DDI between bupropion and CYP2D6 substrates. The inhibitory potency from strong to weak is hydroxybupropion, threohydrobupropion, erythrohydrobupropion, and bupropion, respectively. The present bupropion PBPK model can be useful for predicting inhibition from bupropion in other clinical studies. This study highlights the need for caution and dosage adjustment when combining bupropion with medications metabolized by CYP2D6. It also demonstrates the feasibility of applying the PBPK approach to predict the DDI potential of drugs undergoing complex metabolism, especially in the DDI involving inhibitory metabolites.

The Pharmacokinetic Interaction Study between Carvedilol and Bupropion in Rats

BACKGROUND/AIMS

The effects of multiple-dose bupropion on the pharmacokinetics of single-dose carvedilol were investigated in order to evaluate this possible drug-drug interaction.

METHODS

A preclinical study was conducted among white male Wistar rats. Each rat was cannulated on the femoral vein prior to being connected to BASi Culex ABC®. During the reference period, each rat received an intravenous and an oral dose of 3.57 mg/kg body weight (b.w.) carvedilol, at 2 days distance. After 5 days of pretreatment with 21.42 mg/kg b.w. bupropion (by oral route, twice a day - given in order to reach the steady state), during the sixth day, 3.57 mg/kg b.w. carvedilol and 21.42 mg/kg b.w. bupropion were orally co-administrated (test period). After each administration of carvedilol, several samples of 200 µL blood were collected. The pharmacokinetic parameters of carvedilol were analyzed by the noncompartmental method.

RESULTS

The 5 days pretreatment with bupropion increased the exposure to carvedilol in rats by 180%, considering the modifications observed in the area under the curve of carvedilol. Carvedilol was shown to have higher plasma concentrations, delay in maximum concentration, and a prolonged half-life, after being pretreated with bupropion.

CONCLUSION

The administration of multiple-dose bupropion influences the pharmacokinetics of carvedilol (single oral dose) in rats.

In vitro to in vivo extrapolation of the complex drug-drug interaction of bupropion and its metabolites with CYP2D6; simultaneous reversible inhibition and CYP2D6 downregulation

Bupropion is a widely used antidepressant and smoking cessation aid and a strong inhibitor of CYP2D6 in vivo. Bupropion is administered as a racemic mixture of R- and S-bupropion and has stereoselective pharmacokinetics. Four primary metabolites of bupropion, threo- and erythro-hydrobupropion and R,R- and S,S-OH-bupropion, circulate at higher concentrations than the parent drug and are believed to contribute to the efficacy and side effects of bupropion as well as to the CYP2D6 inhibition. However, bupropion and its metabolites are only weak inhibitors of CYP2D6 in vitro, and the magnitude of the in vivo drug-drug interactions (DDI) caused by bupropion cannot be explained by the in vitro data even when CYP2D6 inhibition by the metabolites is accounted for. The aim of this study was to quantitatively explain the in vivo CYP2D6 DDI magnitude by in vitro DDI data. Bupropion and its metabolites were found to inhibit CYP2D6 stereoselectively with up to 10-fold difference in inhibition potency between enantiomers. However, the reversible inhibition or active uptake into hepatocytes did not explain the in vivo DDIs. In HepG2 cells and in plated human hepatocytes bupropion and its metabolites were found to significantly downregulate CYP2D6 mRNA in a concentration dependent manner. The in vivo DDI was quantitatively predicted by significant down-regulation of CYP2D6 mRNA and reversible inhibition of CYP2D6 by bupropion and its metabolites. This study is the first example of a clinical DDI resulting from CYP down-regulation and first demonstration of a CYP2D6 interaction resulting from transcriptional regulation.

Pharmacokinetic Drug Interactions with Tobacco, Cannabinoids and Smoking Cessation Products

Tobacco smoke contains a large number of compounds in the form of metals, volatile gases and insoluble particles, as well as nicotine, a highly addictive alkaloid. Marijuana is the most widely used illicit drug of abuse in the world, with a significant increase in the USA due to the increasing number of states that allow medical and recreational use. Of the over 70 phytocannabinoids in marijuana, Δ9-tetrahydrocannabinol (Δ9THC), cannabidiol (CBD) and cannibinol are the three main constituents. Both marijuana and tobacco smoking induce cytochrome P450 (CYP) 1A2 through activation of the aromatic hydrocarbon receptor, and the induction effect between the two products is additive. Smoking cessation is associated with rapid downregulation of CYP1A enzymes. On the basis of the estimated half-life of CYP1A2, dose reduction of CYP1A drugs may be necessary as early as the first few days after smoking cessation to prevent toxicity, especially for drugs with a narrow therapeutic index. Nicotine is a substrate of CYP2A6, which is induced by oestrogen, resulting in lower concentrations of nicotine in females than in males, especially in females taking oral contraceptives. The significant effects of CYP3A4 inducers and inhibitors on the pharmacokinetics of Δ9THC/CBD oromucosal spray suggest that CYP3A4 is the primary enzyme responsible for the metabolism of Δ9THC and CBD. Limited data also suggest that CBD may significantly inhibit CYP2C19. With the increasing use of marijuana and cannabis products, clinical studies are needed in order to determine the effects of other drugs on pharmacokinetics and pharmacodynamics.

An S-warfarin and AZD1981 interaction: in vitro and clinical pilot data suggest the N-deacetylated amino acid metabolite as the primary perpetrator

AIM

AZD1981 is an orally bioavailable chemoattractant receptor-homologous molecule expressed on Th2 cells (CRTh2) receptor antagonist progressed to phase II trials for the treatment of allergic asthma. Previously performed in vitro human hepatocyte incubations identified N-deacetylated AZD1981 as a primary metabolite. We report on metabolite exposure from a clinical excretion balance, on in vitro studies performed to determine the likelihood of a metabolite-dependent drug-drug interaction (DDI) and on a clinical warfarin DDI study. The aim was to demonstrate that N-deacetylated AZD1981 is responsible for the observed interaction.

METHODS

The excretion and biotransformation of [¹⁴ C]-AZD1981 were studied in healthy male volunteers, and subsequently in vitro cytochrome P450 (CYP) inhibition and hepatocyte uptake investigations were carried out with metabolites and the parent drug. A clinical DDI study using coadministered twice-daily 100 mg and 400 mg AZD1981 with 25 mg warfarin was performed.

RESULTS

The excretion balance study showed N-deacetylated AZD1981 to be the most abundant metabolite present in plasma. In vitro data revealed the metabolite to be a weak CYP2C9 time-dependent inhibitor, subject to more active hepatic uptake than the parent molecule. Clinically, the S-warfarin area under the plasma concentration-time curve increased, on average, 1.4-fold [95% confidence interval (CI) 1.22, 1.50] and 2.4-fold (95% CI 2.11, 2.64) after 100 mg (n = 13) and 400 mg (n = 11) AZD1981 administration, respectively. In vitro CYP inhibition and hepatocyte uptake data were used to explain the interaction.

CONCLUSIONS

N-deacetylated AZD1981 can be added to the small list of drug metabolites reported as sole contributors to clinical drug-drug interactions, with weak time-dependent inhibition exacerbated by efficient hepatic uptake being the cause.

Identification of non-reported bupropion metabolites in human plasma

Bupropion and its three active metabolites exhibit clinical efficacy in the treatment of major depression, seasonal depression and smoking cessation. The pharmacokinetics of bupropion in humans is highly variable. It is not known if there are any non‐reported metabolites formed in humans in addition to the three known active metabolites. This paper reports newly identified and non‐reported metabolites of bupropion in human plasma samples. Human subjects were dosed with a single oral dose of 75 mg of an immediate release bupropion HCl tablet. Plasma samples were collected and analysed by LC–MS/MS at 0, 6 and 24 h. Two non‐reported metabolites (M1 and M3) were identified with mass‐to‐charge (m/z) ratios of 276 (M1, hydration of bupropion) and 258 (M3, hydroxylation of threo/erythrohydrobupropion) from human plasma in addition to the known hydroxybupropion, threo/erythrohydrobupropion and the glucuronidation products of the major metabolites (M2 and M4–M7). These new metabolites may provide new insight and broaden the understanding of bupropion's variability in clinical pharmacokinetics. © 2016 The Authors Biopharmaceutics & Drug Disposition Published by John Wiley & Sons Ltd.

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.

Cytochrome P450 and Non-Cytochrome P450 Oxidative Metabolism: Contributions to the Pharmacokinetics, Safety, and Efficacy of Xenobiotics

The drug-metabolizing enzymes that contribute to the metabolism or bioactivation of a drug play a crucial role in defining the absorption, distribution, metabolism, and excretion properties of that drug. Although the overall effect of the cytochrome P450 (P450) family of drug-metabolizing enzymes in this capacity cannot be understated, advancements in the field of non-P450-mediated metabolism have garnered increasing attention in recent years. This is perhaps a direct result of our ability to systematically avoid P450 liabilities by introducing chemical moieties that are not susceptible to P450 metabolism but, as a result, may introduce key pharmacophores for other drug-metabolizing enzymes. Furthermore, the effects of both P450 and non-P450 metabolism at a drug's site of therapeutic action have also been subject to increased scrutiny. To this end, this Special Section on Emerging Novel Enzyme Pathways in Drug Metabolism will highlight a number of advancements that have recently been reported. The included articles support the important role of non-P450 enzymes in the clearance pathways of U.S. Food and Drug Administration-approved drugs over the past 10 years. Specific examples will detail recent reports of aldehyde oxidase, flavin-containing monooxygenase, and other non-P450 pathways that contribute to the metabolic, pharmacokinetic, or pharmacodynamic properties of xenobiotic compounds. Collectively, this series of articles provides additional support for the role of non-P450-mediated metabolic pathways that contribute to the absorption, distribution, metabolism, and excretion properties of current xenobiotics.

Use of Human Plasma Samples to Identify Circulating Drug Metabolites that Inhibit Cytochrome P450 Enzymes

Drug interactions elicited through inhibition of cytochrome P450 (P450) enzymes are important in pharmacotherapy. Recently, greater attention has been focused on not only parent drugs inhibiting P450 enzymes but also on possible inhibition of these enzymes by circulating metabolites. In this report, an ex vivo method whereby the potential for circulating metabolites to be inhibitors of P450 enzymes is described. To test this method, seven drugs and their known plasma metabolites were added to control human plasma at concentrations previously reported to occur in humans after administration of the parent drug. A volume of plasma for each drug based on the known inhibitory potency and time-averaged concentration of the parent drug was extracted and fractionated by high-pressure liquid chromatography-mass spectrometry, and the fractions were tested for inhibition of six human P450 enzyme activities (CYP1A2, CYP2C8, CYP2C9, CYP2C19, CYP2D6, and CYP3A4). Observation of inhibition in fractions that correspond to the retention times of metabolites indicates that the metabolite has the potential to contribute to P450 inhibition in vivo. Using this approach, norfluoxetine, hydroxyitraconazole, desmethyldiltiazem, desacetyldiltiazem, desethylamiodarone, hydroxybupropion, erythro-dihydrobupropion, and threo-dihydrobupropion were identified as circulating metabolites that inhibit P450 activities at a similar or greater extent as the parent drug. A decision tree is presented outlining how this method can be used to determine when a deeper investigation of the P450 inhibition properties of a drug metabolite is warranted.

Chiral Plasma Pharmacokinetics and Urinary Excretion of Bupropion and Metabolites in Healthy Volunteers

Bupropion, widely used as an antidepressant and smoking cessation aid, undergoes complex metabolism to yield numerous metabolites with unique disposition, effect, and drug-drug interactions (DDIs) in humans. The stereoselective plasma and urinary pharmacokinetics of bupropion and its metabolites were evaluated to understand their potential contributions to bupropion effects. Healthy human volunteers (n = 15) were administered a single oral dose of racemic bupropion (100 mg), which was followed by collection of plasma and urine samples and determination of bupropion and metabolite concentrations using novel liquid chromatography-tandem mass spectrometry assays. Time-dependent, elimination rate-limited, stereoselective pharmacokinetics were observed for all bupropion metabolites. Area under the plasma concentration-time curve from zero to infinity ratios were on average approximately 65, 6, 6, and 4 and Cmax ratios were approximately 35, 6, 3, and 0.5 for (2R,3R)-/(2S,3S)-hydroxybupropion, R-/S-bupropion, (1S,2R)-/(1R,2S)-erythrohydrobupropion, and (1R,2R)-/(1S,2S)-threohydrobupropion, respectively. The R-/S-bupropion and (1R,2R)-/(1S,2S)-threohydrobupropion ratios are likely indicative of higher presystemic metabolism of S- versus R-bupropion by carbonyl reductases. Interestingly, the apparent renal clearance of (2S,3S)-hydroxybupropion was almost 10-fold higher than that of (2R,3R)-hydroxybupropion. The prediction of steady-state pharmacokinetics demonstrated differential stereospecific accumulation [partial area under the plasma concentration-time curve after the final simulated bupropion dose (300-312 hours) from 185 to 37,447 nM⋅h] and elimination [terminal half-life of approximately 7-46 hours] of bupropion metabolites, which may explain observed stereoselective differences in bupropion effect and DDI risk with CYP2D6 at steady state. Further elucidation of bupropion and metabolite disposition suggests that bupropion is not a reliable in vivo marker of CYP2B6 activity. In summary, to our knowledge, this is the first comprehensive report to provide novel insight into mechanisms underlying bupropion disposition by detailing the stereoselective pharmacokinetics of individual bupropion metabolites, which will enhance clinical understanding of bupropion's effects and DDIs with CYP2D6.

Impact of Cytochrome P450 2D6 Function on the Chiral Blood Plasma Pharmacokinetics of 3,4-Methylenedioxymethamphetamine (MDMA) and Its Phase I and II Metabolites in Humans

3,4-methylenedioxymethamphetamine (MDMA; ecstasy) metabolism is known to be stereoselective, with preference for S-stereoisomers. Its major metabolic step involves CYP2D6-catalyzed demethylenation to 3,4-dihydroxymethamphetamine (DHMA), followed by methylation and conjugation. Alterations in CYP2D6 genotype and/or phenotype have been associated with higher toxicity. Therefore, the impact of CYP2D6 function on the plasma pharmacokinetics of MDMA and its phase I and II metabolites was tested by comparing extensive metabolizers (EMs), intermediate metabolizers (IMs), and EMs that were pretreated with bupropion as a metabolic inhibitor in a controlled MDMA administration study. Blood plasma samples were collected from 16 healthy participants (13 EMs and three IMs) up to 24 h after MDMA administration in a double-blind, placebo-controlled, four-period, cross-over design, with subjects receiving 1 week placebo or bupropion pretreatment followed by a single placebo or MDMA (125 mg) dose. Bupropion pretreatment increased the maximum plasma concentration (C_max) and area under the plasma concentration-time curve from 0 to 24 h (AUC₂₄) of R-MDMA (9% and 25%, respectively) and S-MDMA (16% and 38%, respectively). Bupropion reduced the C_max and AUC₂₄ of the CYP2D6-dependently formed metabolite stereoisomers of DHMA 3-sulfate, DHMA 4-sulfate, and 4-hydroxy-3-methoxymethamphetamine (HMMA sulfate and HMMA glucuronide) by approximately 40%. The changes that were observed in IMs were generally comparable to bupropion-pretreated EMs. Although changes in stereoselectivity based on CYP2D6 activity were observed, these likely have low clinical relevance. Bupropion and hydroxybupropion stereoisomer pharmacokinetics were unaltered by MDMA co-administration. The present data might aid further interpretations of toxicity based on CYP2D6-dependent MDMA metabolism.

Stereoselective Glucuronidation of Bupropion Metabolites In Vitro and In Vivo

Bupropion is a widely used antidepressant and smoking cessation aid in addition to being one of two US Food and Drug Administration-recommended probe substrates for evaluation of cytochrome P450 2B6 activity. Racemic bupropion undergoes oxidative and reductive metabolism, producing a complex profile of pharmacologically active metabolites with relatively little known about the mechanisms underlying their elimination. A liquid chromatography-tandem mass spectrometry assay was developed to simultaneously separate and detect glucuronide metabolites of (R,R)- and (S,S)-hydroxybupropion, (R,R)- and (S,S)-hydrobupropion (threo) and (S,R)- and (R,S)-hydrobupropion (erythro), in human urine and liver subcellular fractions to begin exploring mechanisms underlying enantioselective metabolism and elimination of bupropion metabolites. Human liver microsomal data revealed marked glucuronidation stereoselectivity [Cl(int), 11.4 versus 4.3 µl/min per milligram for the formation of (R,R)- and (S,S)-hydroxybupropion glucuronide; and Cl(max), 7.7 versus 1.1 µl/min per milligram for the formation of (R,R)- and (S,S)-hydrobupropion glucuronide], in concurrence with observed enantioselective urinary elimination of bupropion glucuronide conjugates. Approximately 10% of the administered bupropion dose was recovered in the urine as metabolites with glucuronide metabolites, accounting for approximately 40%, 15%, and 7% of the total excreted hydroxybupropion, erythro-hydrobupropion, and threo-hydrobupropion, respectively. Elimination pathways were further characterized using an expressed UDP-glucuronosyl transferase (UGT) panel with bupropion enantiomers (both individual and racemic) as substrates. UGT2B7 catalyzed the stereoselective formation of glucuronides of hydroxybupropion, (S,S)-hydrobupropion, (S,R)- and (R,S)-hydrobupropion; UGT1A9 catalyzed the formation of (R,R)-hydrobupropion glucuronide. These data systematically describe the metabolic pathways underlying bupropion metabolite disposition and significantly expand our knowledge of potential contributors to the interindividual and intraindividual variability in therapeutic and toxic effects of bupropion in humans.

Fluvoxamine-associated oscillopsia and a role for personalized medication dosing

A 60-year-old woman reported horizontal "shimmering" movement while reading crossword puzzles when using fluvoxamine, bupropion, quetiapine, lithium, and levothyroxine. This visual disturbance, likely oscillopsia, started after the fluvoxamine was added and waned as the fluvoxamine was tapered, disappearing after the drug was discontinued. Genetic testing to explore how the patient metabolizes these medications combined with YouScript® interaction analysis suggest that she may have had abnormally high plasma concentrations of fluvoxamine during this time. Oscillopsia may be a novel dose-dependent side effect of fluvoxamine. Genetic testing combined with YouScript has the potential to discover novel drug side effects, elucidate drug interactions and guide future prescribing decisions.

Metabolism of bupropion by carbonyl reductases in liver and intestine

Bupropion's metabolism and the formation of hydroxybupropion in the liver by cytochrome P450 2B6 (CYP2B6) has been extensively studied; however, the metabolism and formation of erythro/threohydrobupropion in the liver and intestine by carbonyl reductases (CR) has not been well characterized. The purpose of this investigation was to compare the relative contribution of the two metabolism pathways of bupropion (by CYP2B6 and CR) in the subcellular fractions of liver and intestine and to identify the CRs responsible for erythro/threohydrobupropion formation in the liver and the intestine. The results showed that the liver microsome generated the highest amount of hydroxybupropion (Vmax = 131 pmol/min per milligram, Km = 87 μM). In addition, liver microsome and S9 fractions formed similar levels of threohydrobupropion by CR (Vmax = 98-99 pmol/min per milligram and Km = 186-265 μM). Interestingly, the liver has similar capability to form hydroxybupropion (by CYP2B6) and threohydrobupropion (by CR). In contrast, none of the intestinal fractions generate hydroxybupropion, suggesting that the intestine does not have CYP2B6 available for metabolism of bupropion. However, intestinal S9 fraction formed threohydrobupropion to the extent of 25% of the amount of threohydrobupropion formed by liver S9 fraction. Enzyme inhibition and Western blots identified that 11β-dehydrogenase isozyme 1 in the liver microsome fraction is mainly responsible for the formation of threohydrobupropion, and in the intestine AKR7 may be responsible for the same metabolite formation. These quantitative comparisons of bupropion metabolism by CR in the liver and intestine may provide new insight into its efficacy and side effects with respect to these metabolites.

Geneva cocktail for cytochrome p450 and P-glycoprotein activity assessment using dried blood spots

The suitability of the capillary dried blood spot (DBS) sampling method was assessed for simultaneous phenotyping of cytochrome P450 (CYP) enzymes and P-glycoprotein (P-gp) using a cocktail approach. Ten volunteers received an oral cocktail capsule containing low doses of the probes bupropion (CYP2B6), flurbiprofen (CYP2C9), omeprazole (CYP2C19), dextromethorphan (CYP2D6), midazolam (CYP3A), and fexofenadine (P-gp) with coffee/Coke (CYP1A2) on four occasions. They received the cocktail alone (session 1), and with the CYP inhibitors fluvoxamine and voriconazole (session 2) and quinidine (session 3). In session 4, subjects received the cocktail after a 7-day pretreatment with the inducer rifampicin. The concentrations of probes/metabolites were determined in DBS and plasma using a single liquid chromatography–tandem mass spectrometry method. The pharmacokinetic profiles of the drugs were comparable in DBS and plasma. Important modulation of CYP and P-gp activities was observed in the presence of inhibitors and the inducer. Minimally invasive one- and three-point (at 2, 3, and 6 h) DBS-sampling methods were found to reliably reflect CYP and P-gp activities at each session.

Drug metabolites as cytochrome p450 inhibitors: a retrospective analysis and proposed algorithm for evaluation of the pharmacokinetic interaction potential of metabolites in drug discovery and development

Understanding drug-drug interactions (DDIs) is a key component of clinical practice ensuring patient safety and efficacy of medicines. The role of drug metabolites in DDIs is a developing area of science, and has been recently highlighted in a draft regulatory guidance. The guidance states that metabolites representing ≥25% of the parent drug's area under the plasma concentration/time curve and/or >10% of exposure of total drug-related material should trigger in vitro characterization of metabolites for cytochrome P450 inhibition and propensity for DDIs. The relationship between in vitro cytochrome P450 inhibitory potency, systemic exposure, and DDI potential of drug metabolites was examined using the Pfizer development database to identify compounds with pre-existing in vivo biotransformation data, where circulating metabolites were identified in humans. The database yielded 33 structurally diverse compounds with collectively 115 distinct circulating metabolites. Of these, 52% (60/115) achieved exposures >25% of parent drug levels as judged from mass balance/metabolite identification studies. It was noted that 14 metabolite standards for 12 parent drugs had been synthesized, monitored in clinical studies, and examined for cytochrome P450 inhibition. For the 14 metabolite/parent drug pairs, no clinically relevant DDIs were expected to occur against the major human cytochrome P450 isoforms. A review of the literature for parent/metabolite DDI information was also conducted to examine trends using a larger data set. Leveraging the analysis of both internal and literature-based data sets, an algorithm was devised for use in drug discovery/early development to assess cytochrome P450 inhibitory potential of drug metabolites and the propensity to cause a clinically relevant DDI.

Stereoselective inhibition of CYP2C19 and CYP3A4 by fluoxetine and its metabolite: implications for risk assessment of multiple time-dependent inhibitor systems

Recent guidance on drug-drug interaction (DDI) testing recommends evaluation of circulating metabolites. However, there is little consensus on how to quantitatively predict and/or assess the risk of in vivo DDIs by multiple time-dependent inhibitors (TDIs) including metabolites from in vitro data. Fluoxetine was chosen as the model drug to evaluate the role of TDI metabolites in DDI prediction because it is a TDI of both CYP3A4 and CYP2C19 with a circulating N-dealkylated inhibitory metabolite, norfluoxetine. In pooled human liver microsomes, both enantiomers of fluoxetine and norfluoxetine were TDIs of CYP2C19, (S)-norfluoxetine was the most potent inhibitor with time-dependent inhibition affinity constant (KI) of 7 μM, and apparent maximum time-dependent inhibition rate (k(inact,app)) of 0.059 min(-1). Only (S)-fluoxetine and (R)-norfluoxetine were TDIs of CYP3A4, with (R)-norfluoxetine being the most potent (K(I) = 8 μM, and k(inact,app) = 0.011 min(-1)). Based on in-vitro-to-in-vivo predictions, (S)-norfluoxetine plays the most important role in in vivo CYP2C19 DDIs, whereas (R)-norfluoxetine is most important in CYP3A4 DDIs. Comparison of two multiple TDI prediction models demonstrated significant differences between them in in-vitro-to-in-vitro predictions but not in in-vitro-to-in-vivo predictions. Inclusion of all four inhibitors predicted an in vivo decrease in CYP2C19 (95%) and CYP3A4 (60-62%) activity. The results of this study suggest that adequate worst-case risk assessment for in vivo DDIs by multiple TDI systems can be achieved by incorporating time-dependent inhibition by both parent and metabolite via simple addition of the in vivo time-dependent inhibition rate/cytochrome P450 degradation rate constant (λ/k(deg)) values, but quantitative DDI predictions will require a more thorough understanding of TDI mechanisms.

Bupropion for the treatment of seasonal affective disorder

INTRODUCTION

Seasonal affective disorder (SAD) is a psychiatric illness with recurring depressive episodes during particular seasons, mostly winter. Bupropion is effective in the preventive treatment of SAD and is probably also effective in the acute treatment of SAD.

AREAS COVERED

This review covers the pharmacokinetics and pharmacodynamics of bupropion. The authors also evaluate bupropion's clinical efficacy as well as its safety and tolerability.

EXPERT OPINION

Bupropion is available in an immediate release formulation, as well as a sustained release formulation and an extended release (XR) formulation. The XR formulation is recommended for SAD due to its ease of use and is the only formulation currently used as a therapy. Due to the predictable nature of SAD, the use of bupropion XR is considered a relevant treatment option. Bupropion's efficacy is shown in three trials that started in autumn at a time when SAD symptoms were not yet present although treatment effects were relatively small compared with a placebo. Bupropion was also shown to have efficacy in an open-label study. That being said, in order to reach definitive conclusions about its efficacy with acute treatment of SAD, more placebo-controlled trials are needed.

Inhibition of CYP2C19 and CYP3A4 by omeprazole metabolites and their contribution to drug-drug interactions

The aim of this study was to evaluate the contribution of metabolites to drug-drug interactions (DDI) using the inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites as a model. Of the metabolites identified in vivo, 5-hydroxyomeprazole, 5'-O-desmethylomeprazole, omeprazole sulfone, and carboxyomeprazole had a metabolite to parent area under the plasma concentration-time curve (AUC(m)/AUC(p)) ratio ≥ 0.25 when either total or unbound concentrations were measured after a single 20-mg dose of omeprazole in a cocktail. All of the metabolites inhibited CYP2C19 and CYP3A4 reversibly. In addition omeprazole, omeprazole sulfone, and 5'-O-desmethylomeprazole were time dependent inhibitors (TDI) of CYP2C19, whereas omeprazole and 5'-O-desmethylomeprazole were found to be TDIs of CYP3A4. The in vitro inhibition constants and in vivo plasma concentrations were used to evaluate whether characterization of the metabolites affected DDI risk assessment. Identifying omeprazole as a TDI of both CYP2C19 and CYP3A4 was the most important factor in DDI risk assessment. Consideration of reversible inhibition by omeprazole and its metabolites would not identify DDI risk with CYP3A4, and with CYP2C19, reversible inhibition values would only identify DDI risk if the metabolites were included in the assessment. On the basis of inactivation data, CYP2C19 and CYP3A4 inhibition by omeprazole would be sufficient to identify risk, but metabolites were predicted to contribute 30-63% to the in vivo hepatic interactions. Therefore, consideration of metabolites may be important in quantitative predictions of in vivo DDIs. The results of this study show that, although metabolites contribute to in vivo DDIs, their relative abundance in circulation or logP values do not predict their contribution to in vivo DDI risk.

Risk assessment of mechanism-based inactivation in drug-drug interactions

Drug-drug interactions (DDIs) that occur via mechanism-based inactivation of cytochrome P450 are of serious concern. Although several predictive models have been published, early risk assessment of MBIs is still challenging. For reversible inhibitors, the DDI risk categorization using [I]/K(i) ([I], the inhibitor concentration; K(i), the inhibition constant) is widely used in drug discovery and development. Although a simple and reliable methodology such as [I]/K(i) categorization for reversible inhibitors would be useful for mechanism-based inhibitors (MBIs), comprehensive analysis of an analogous measure reflecting in vitro potency for inactivation has not been reported. The aim of this study was to evaluate whether the term λ/k(deg) (λ, first-order inactivation rate at a given MBI concentration; k(deg), enzyme degradation rate constant) would be useful in the prediction of the in vivo DDI risk of MBIs. Twenty-one MBIs with both in vivo area under the curve (AUC) change of marker substrates and in vitro inactivation parameters were identified in the literature and analyzed. The results of this analysis show that in vivo DDIs with >2-fold change of object drug AUC can be identified with the cutoff value of λ/k(deg) = 1, where unbound steady-state C(max) is used for inhibitor concentration. However, the use of total C(max) led to great overprediction of DDI risk. The risk assessment using λ/k(deg) coupled with unbound C(max) can be useful for the DDI risk evaluation of MBIs in drug discovery and development.

In vivo information-guided prediction approach for assessing the risks of drug-drug interactions associated with circulating inhibitory metabolites

The in vivo drug-drug interaction (DDI) risks associated with cytochrome P450 inhibitors that have circulating inhibitory metabolites cannot be accurately predicted by conventional in vitro-based methods. A novel approach, in vivo information-guided prediction (IVIP), was recently introduced for CYP3A- and CYP2D6-mediated DDIs. This technique should be applicable to the prediction of DDIs involving other important cytochrome P450 metabolic pathways. Therefore, the aims of this study were to extend the IVIP approach to CYP2C9-mediated DDIs and evaluate the IVIP approach for predicting DDIs associated with inhibitory metabolites. The analysis was based on data from reported DDIs in the literature. The IVIP approach was modified and extended to CYP2C9-mediated DDIs. Thereafter, the IVIP approach was evaluated for predicting the DDI risks of various inhibitors with inhibitory metabolites. Although the data on CYP2C9-mediated DDIs were limited compared with those for CYP3A- and CYP2D6-mediated DDIs, the modified IVIP approach successfully predicted CYP2C9-mediated DDIs. For the external validation set, the prediction accuracy for area under the plasma concentration-time curve (AUC) ratios ranged from 70 to 125%. The accuracy (75-128%) of the IVIP approach in predicting DDI risks of inhibitors with circulating inhibitory metabolites was more accurate than in vitro-based methods (28-805%). The IVIP model accommodates important confounding factors in the prediction of DDIs, which are difficult to handle using in vitro-based methods. In conclusion, the IVIP approach could be used to predict CYP2C9-mediated DDIs and is easily modified to incorporate the additive effect of circulating inhibitory metabolites.

In vitro-to-in vivo predictions of drug-drug interactions involving multiple reversible inhibitors

INTRODUCTION

Predictions of drug-drug interactions (DDIs) are commonly performed for single inhibitors, but interactions involving multiple inhibitors also frequently occur. Predictions of such interactions involving stereoisomer pairs, parent/metabolite combinations and simultaneously administered multiple inhibitors are increasing in importance. This review provides the framework for predicting inhibitory DDIs of multiple inhibitors with any combination of reversible inhibition mechanism.

AREAS COVERED

The review provides an overview of the reliability of the in vitro determined reversible inhibition mechanism. Furthermore, the article provides a method to predict DDIs for multiple reversible inhibitors that allows substituting the inhibition constant (K(i)) with an inhibitor affinity (IC(50)) value determined at S << K(M).

EXPERT OPINION

A better understanding and the prediction methods of DDIs, resulting from multiple inhibitors, are important. The inhibition mechanism of a reversible inhibitor is often equivocal across studies and unreliable. Determination of the K(i) requires the assignment of reversible inhibition mechanism but in vitro-to-in vivo prediction of DDI risk can be achieved for multiple inhibitors from estimates of the inhibitor affinity (IC(50)) only, regardless of the inhibition mechanism.