Physiologically based modelling of inhibition of metabolism and assessment of the relative potency of drug and metabolite: dextromethorphan vs. dextrorphan using quinidine inhibition

Physiologically-based pharmacokinetic modeling of quinidine to establish a CYP3A4, P-gp, and CYP2D6 drug-drug-gene interaction network

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) and is therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P-gp, it is susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug-drug(-gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P-gp perpetrators as well as CYP2D6 and P-gp victims. The quinidine parent-metabolite model including 3-hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1-600 mg). The model covers efflux transport via P-gp and metabolic transformation to either 3-hydroxyquinidine or unspecified metabolites via CYP3A4. The 3-hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two-fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two-fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is.

Development of an enantioselective high-performance liquid chromatography-tandem mass spectrometry method for the quantitative determination of methorphan and its O-demethylated metabolite in human blood and its application to post-mortem samples

In the present work an isocratic enantioselective high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed for the separation and quantitative determination of dextro - and levo -methorphan and their pharmacologically relevant metabolites, dextrorphan and levorphanol, respectively, in human blood samples. The separation of enantiomers of methorphan and metabolites was performed on the polysaccharide-based chiral column Lux AMP in combination with acetonitrile and 5 mM aqueous ammonium bicarbonate pH 11 in the ratio 50:50 (%, v/v) as mobile phase with the flow rate 1 mL/min. The mass spectrometer was operated in scheduled multiple reaction monitoring (MRM) mode, with four transitions for each dextromethorpan, levomethorphan, dextrorphan and dextromethorphan-d3 and two transitions for each levorphanol, levorphanol-d3 and dextrorphan-d3. Application of this method to human post-mortem blood samples confirmed cases of severe overdosing with dextromethorphan, levomethorphan, and less commonly with both.

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

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

A systematic review of methods of citric acid cough reflex testing

INTRODUCTION

This systematic review summarises and appraises methods of citric acid cough reflex testing (CRT) documented in published literature.

METHODS

Electronic databases, MEDLINE, EMBASE, CINAHL, PsychINFO, Scopus were searched up to and including 11th February 2018. Studies reporting a method of citric acid CRT, published in peer-reviewed journals in English or Spanish, were assessed for the inclusion criteria. Of the selected studies, information on the instrumentation and CRT protocol was extracted.

RESULTS

A total of 129 studies were included. Instrumentation and protocols differed widely across studies. Reporting of methods of citric acid CRT was sub-standard, with many crucial methodological components omitted from published manuscripts, preventing their full replication.

CONCLUSIONS

Considerable methodological variability exists for citric acid CRT in published literature. The findings suggest that caution is warranted in comparing citric acid cough thresholds across studies. Full replication of previously published methods of citric acid CRT is limited due to crucial elements of the citric acid CRT protocol being omitted from published manuscripts. These findings have implications on the use of citric acid CRT in clinical and pharmaceutical studies to evaluate the effects of antitussive medications and cough therapies.

Application of a physiologically based pharmacokinetic model for the evaluation of single-point plasma phenotyping method of CYP2D6

PURPOSE

Determining metabolic ratio from single-point plasma is potentially a good phenotyping method of CYP2D6 to reduce the required time interval and increase the reliability of data. It is difficult to conduct large sample size clinical trials to evaluate this phenotyping method for multiple plasma points. A physiologically based pharmacokinetic (PBPK) model can be developed to do simulations based on the large virtual Chinese population and evaluate single-point plasma phenotyping method of CYP2D6.

METHODS

Pharmacokinetic data of dextromethorphan (DM) and its metabolite dextrorphan (DX) after oral administration were used for model development. The SimCYP® model incorporating Chinese demographic, physiological, and enzyme data was used to simulate DM and DX pharmacokinetics in different phenotype groups.

RESULTS

The ratios of the simulated to the observed mean AUC and Cmax of DM were 1.01 and 0.81 for extensive metabolizers (EMs), 0.90 and 0.81 for intermediate metabolizers (IMs), and 1.12 and 0.84 for poor metabolizers (PMs). The ratios of the simulated to the observed mean AUC and Cmax of DX were 1.12 and 0.89 for EMs, 0.66 and 0.62 for IMs. All ratios were within the predefined criterion of 0.5-2. The simulations of DM and DX pharmacokinetic profiles in 1000 virtual Chinese subjects with reported frequencies of different phenotypes indicated that statistically significant correlations were found between metabolic ratio of DM to DX (MRDM/DX) from AUC and from single-point plasma from 1 to 30h (all p-values <0.001).

CONCLUSION

MRDM/DX from single-point plasma from 1 to 30h after the administration of 30mg controlled-release DM could predict the MRDM/DX from AUC well and could be used as the phenotyping method of CYP2D6 for EMs, IMs, and PMs.

How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective

The use of in vitro metabolism data to predict human clearance has become more significant in the current prediction of large scale drug clearance for all the drugs. The relevant information (in vitro metabolism data and in vivo human clearance values) of thirty-five drugs that satisfied the entry criteria of probe drugs was collated from the literature. Then the performance of different in vitro systems including Escherichia coli system, yeast system, lymphoblastoid system and baculovirus system is compared after in vitro-in vivo extrapolation. Baculovirus system, which can provide most of the data, has almost equal accuracy as the other systems in predicting clearance. And in most cases, baculovirus system has the smaller CV in scaling factors. Therefore, the baculovirus system can be recognized as the suitable system for the large scale drug clearance prediction.

Population pharmacokinetic modelling to assess the impact of CYP2D6 and CYP3A metabolic phenotypes on the pharmacokinetics of tamoxifen and endoxifen

AIMS

Tamoxifen is considered a pro-drug of its active metabolite endoxifen. The major metabolic enzymes involved in endoxifen formation are CYP2D6 and CYP3A. There is considerable evidence that variability in activity of these enzymes influences endoxifen exposure and thereby may influence the clinical outcome of tamoxifen treatment. We aimed to quantify the impact of metabolic phenotype on the pharmacokinetics of tamoxifen and endoxifen.

METHODS

We assessed the CYP2D6 and CYP3A metabolic phenotypes in 40 breast cancer patients on tamoxifen treatment with a single dose of dextromethorphan as a dual phenotypic probe for CYP2D6 and CYP3A. The pharmacokinetics of dextromethorphan, tamoxifen and their relevant metabolites were analyzed using non-linear mixed effects modelling.

RESULTS

Population pharmacokinetic models were developed for dextromethorphan, tamoxifen and their metabolites. In the final model for tamoxifen, the dextromethorphan derived metabolic phenotypes for CYP2D6 as well as CYP3A significantly (P < 0.0001) explained 54% of the observed variability in endoxifen formation (inter-individual variability reduced from 55% to 25%).

CONCLUSIONS

We have shown that not only CYP2D6, but also CYP3A enzyme activity influences the tamoxifen to endoxifen conversion in breast cancer patients. Our developed model may be used to assess separately the impact of CYP2D6 and CYP3A mediated drug-drug interactions with tamoxifen without the necessity of administering this anti-oestrogenic drug and to support Bayesian guided therapeutic drug monitoring of tamoxifen in routine clinical practice.

Incorporating In Vitro Information on Drug Metabolism Into Clinical Trial Simulations to Assess the Effect of CYP2D6 Polymorphism on Pharmacokinetics and Pharmacodynamics: Dextromethorphan as a Model Application

In vitro-in vivo extrapolation of clearance, embedded in a clinical trial simulation, was used to investigate differences in the pharmacokinetics and pharmacodynamics of dextromethorphan between CYP2D6 poor and extensive metabolizer phenotypes. Information on the genetic variation of CYP2D6, as well as the in vitro metabolism and pharmacodynamics of dextromethorphan and its active metabolite dextrorphan, was integrated to assess the power of studies to detect differences between phenotypes. Whereas 6 subjects of each phenotype were adequate to achieve 80% power in showing pharmacokinetic differences, the power required to detect a difference in antitussive response was less than 80% with 500 subjects in each study arm. Combining in vitro-in vivo extrapolation with a clinical trial simulation is useful in assessing different elements of study design and could be used a priori to avoid inconclusive pharmacogenetic studies.

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.

The design and analysis of parallel experiments to produce structurally identifiable models

Pharmacokinetic analysis in humans using compartmental models is restricted with respect to the estimation of parameter values. This is because the experimenter usually is only able to apply inputs and observations in a very small number of compartments in the system. This has implications for the structural identifiability of such systems and consequently limits the complexity and mechanistic relevance of the models that may be applied to such experiments. A number of strategies are presented whereby models are rendered globally identifiable by considering a series of experiments in parallel. Examples are taken from the pharmacokinetic literature and analysed using this parallel experiment methodology. It is concluded that considering a series of pharmacokinetic experiments where some, but not all, of the parameters may be shared across the experiments can improve the identifiability of some compartmental models.

Dextromethorphan/quinidine: in pseudobulbar affect

Pseudobulbar affect is characterized by uncontrollable, inappropriate laughing and/or crying that is either unrelated or out of proportion to the emotions felt by the patient and occurs in patients with neurological disorders, such as amyotrophic lateral sclerosis (ALS), multiple sclerosis or traumatic brain injury. Dextromethorphan/quinidine is indicated in the US for the treatment of pseudobulbar affect. Dextromethorphan, when its metabolism is inhibited by the coadministration of quinidine, has been shown to have a positive effect on the symptoms of pseudobulbar affect. Dextromethorphan/quinidine 20 mg/10 mg twice daily was associated with a significantly greater decrease in the rate of pseudobulbar affect episodes per day (primary endpoint) than placebo in the 12-week, randomized, double-blind, placebo-controlled, multicentre STAR trial (Safety, Tolerability, And efficacy Results trial of AVP-923 in PBA [pseudobulbar affect]) involving patients with pseudobulbar affect and ALS or multiple sclerosis. Moreover, the mean change from baseline in Center for Neurologic Study-Lability Scale score at 12 weeks was significantly greater among recipients of dextromethorphan/quinidine 20 mg/10 mg twice daily than those receiving placebo. Dextromethorphan/quinidine 20 mg/10 mg twice daily was generally well tolerated. The drug has been shown to cause dosage-dependent corrected QT interval (QTc) prolongation; however, in the STAR trial, dextromethorphan/quinidine 20 mg/10 mg twice daily appeared to be well tolerated with regard to QTc prolongation.

Assessment of activity levels for CYP2D6*1, CYP2D6*2, and CYP2D6*41 genes by population pharmacokinetics of dextromethorphan

The pharmacokinetics of dextromethorphan (DM) is markedly influenced by cytochrome P450 2D6 (CYP2D6) enzyme polymorphisms. The aim of this study was to quantify the effects of the CYP2D6*1, *2, and *41 variants on DM metabolism in vivo and to identify other sources of pharmacokinetic variability. Concentrations of DM and dextrorphan (DO) in plasma and urine were evaluated in 36 healthy Caucasian men. These volunteers participated in three clinical studies and received a single oral dose of 30 mg DM-HBr. Data were modeled simultaneously using the population pharmacokinetics NONMEM software. A five-compartment model adequately described the data. The activity levels of the alleles assessed differed significantly. The clearance attributable to an individual CYP2D6*1 copy was 2.5-fold higher as compared with CYP2D6*2 (5,010 vs. 2,020 l/h), whereas the metabolic activity of CYP2D6*41 was very low (85 l/h). Urinary pH was confirmed as a significant covariate for DM renal clearance. These results refine genotype-based predictions of pharmacokinetics for DM and presumably for other CYP2D6 substrates as well.

Physiologically based pharmacokinetics (PBPK)

Allometric scaling is widely used to predict human pharmacokinetic parameters from preclinical species, and many different approaches have been proposed over the years to improve its predictive performance. Nevertheless, prediction errors are commonly observed in the practical application of simple allometry, for example, in cases where the hepatic metabolic clearance is mainly determined by enzyme activities, which do not scale allometrically across species. Therefore, if good correlation was noted for some drugs, poor correlation was observed for others, highlighting the need for other conceptual approaches. Physiologically based pharmacokinetic (PBPK) models are now a well-established approach to conduct extrapolations across species and to generate simulations of pharmacokinetic profiles under various physiological conditions. While conventional pharmacokinetic models are defined by drug-related data themselves, PBPK models have richer information content and integrate information from various sources, including drug-dependent, physiological, and biological parameters as they vary in between species, subjects, or with age and disease state. Therefore, the biological and mechanistic bases of PBPK models allow the extrapolation of the kinetic behavior of drugs with regard to dose, route, and species. In addition, by providing a link between tissue concentrations and toxicological or pharmacological effects, PBPK modeling represents a framework for mechanistic pharmacokinetic-pharmacodynamic models.

Contribution of the active metabolite M1 to the pharmacological activity of tesofensine in vivo: a pharmacokinetic-pharmacodynamic modelling approach

BACKGROUND AND PURPOSE

Tesofensine is a centrally acting drug under clinical development for Alzheimer's disease, Parkinson's disease and obesity. In vitro, the major metabolite of tesofensine (M1) displayed a slightly higher activity, which however has not been determined in vivo. The aims of this investigation were (i) to simultaneously accomplish a thorough characterization of the pharmacokinetic (PK) properties of tesofensine and M1 in mice and (ii) to evaluate the potency (pharmacodynamics, PD) and concentration-time course of the active metabolite M1 relative to tesofensine and their impact in vivo using the PK/PD modelling approach.

EXPERIMENTAL APPROACH

Parent compound, metabolite and vehicle were separately administered intravenously and orally over a wide dose range (0.3-20 mg kg(-1)) to 228 mice. Concentrations of tesofensine and M1 were measured; inhibition of the dopamine transporter was determined by co-administration of [(3)H]WIN35,428 as the pharmacodynamic measure.

KEY RESULTS

Pharmacokinetics of tesofensine and M1 were best described by one-compartment models for both compounds. Nonlinear elimination and metabolism kinetics were observed with increasing dose. The PK/PD relationship was described by an extended E(max) model. Effect compartments were used to resolve observed hysteresis. EC(50) values of M1, as an inhibitor of the dopamine transporter, were 4-5-fold higher than those for tesofensine in mice.

CONCLUSIONS AND IMPLICATIONS

The lower potency of M1 together with approximately 8-fold higher through steady-state concentrations suggest that M1 did contribute to the overall activity of tesofensine in mice.

Prediction of metabolic drug clearance in humans: in vitro-in vivo extrapolation vs allometric scaling

Previously in vitro-in vivo extrapolation (IVIVE) with the Simcyp Clearance and Interaction Simulator has been used to predict the clearance of 15 clinically used drugs in humans. The criteria for the selection of the drugs were that they are used as probes for the activity of specific cytochromes P450 (CYPs) or have a single CYP isoform as the major or sole contributor to their metabolism and that they do not exhibit non-linear kinetics in vivo. Where data were available for the clearance of the drugs in at least three animal species, the predictions from IVIVE have now been compared with those based on allometric scaling (AS). Adequate data were available for estimating oral clearance (CLp.o.) in 9 cases (alprazolam, sildenafil, caffeine, clozapine, cyclosporine, dextromethorphan, midazolam, omeprazole and tolbutamide) and intravenous clearance in 6 cases (CLi.v.) (cyclosporine, diclofenac, midazolam, omeprazole, theophylline and tolterodine). AS predictions were based on five different methods: (1) simple allometry (clearance versus body weight); (2) correction for maximum life-span potential (CL x MLP); (3) correction for brain weight (CL x BrW); (4) the use of body surface area; and (5) the rule of exponents. A prediction accuracy was indicated by mean-fold error and the Pearson product moment correlation coefficient. Predictions were considered successful if the mean-fold error was <or=2. IVIVE predictions were accurate in 14 of 15 cases (mean-fold error range: 1.02-4.00). All five AS methods were accurate in 13, 11, 10, 10 and 14 cases, respectively. However, in some cases the error of AS exceeded fivefold. On the basis of the current results, IVIVE is more reliable than AS in predicting human clearance values for drugs mainly metabolized by CYP450 enzymes. This suggests that the place of AS methods in pre-clinical drug development warrants further scrutiny.

Whole-body physiologically based pharmacokinetic models

This review summarizes the most recent developments in and applications of physiologically based pharmacokinetic (PBPK) modeling methodology originating from both the pharmaceutical and environmental toxicology areas. It focuses on works published in the last 5 years, although older seminal papers have also been referenced. After a brief introduction to the field and several essential definitions, the main body of the text is structured to follow the major steps of a typical PBPK modeling exercise. Various applications of the methodology are briefly described. The major future trends and perspectives are outlined. The main conclusion from the review of the available literature is that PBPK modeling, despite its obvious potential and recent incremental developments, has not taken the place it deserves, especially in pharmaceutical and drug development sciences.

Simultaneous determination of dextromethorphan, dextrorphan, and guaifenesin in human plasma using semi-automated liquid/liquid extraction and gradient liquid chromatography tandem mass spectrometry

A method for the simultaneous determination of dextromethorphan (DEX), dextrorphan (DET), and guaifenesin (GG) in human plasma was developed, validated, and applied to determine plasma concentrations of these compounds in samples from six clinical pharmacokinetic (PK) studies. Semi-automated liquid handling systems were used to perform the majority of the sample manipulation including liquid/liquid extraction (LLE) of the analytes from human plasma. Stable-isotope-labeled analogues were utilized as internal standards (ISTDs) for each analyte to facilitate accurate and precise quantification. Extracts were analyzed using gradient liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Use of semi-automated LLE with LC-MS/MS proved to be a very rugged and reliable approach for analysis of more than 6200 clinical study samples. The lower limit of quantification was validated at 0.010, 0.010, and 1.0 ng/mL of plasma for DEX, DET, and GG, respectively. Accuracy and precision of quality control (QC) samples for all three analytes met FDA Guidance criteria of +/-15% for average QC accuracy with coefficients of variation less than 15%. Data from the thorough evaluation of the method during development, validation, and application are presented to characterize selectivity, linearity, over-range sample analysis, accuracy, precision, autosampler carry-over, ruggedness, extraction efficiency, ionization suppression, and stability. Pharmacokinetic data are also provided to illustrate improvements in systemic drug and metabolite concentration-time profiles that were achieved by formulation optimization.

Potential interactions of methylphenidate and atomoxetine with dextromethorphan

OBJECTIVE

To examine the potential for drug-drug interactions to influence drug metabolism between the attention-deficit/hyperactivity disorder (ADHD) dl-methylphenidate and atomoxetine with dextromethorphan, a probe for interactions involving cytochrome P450 (CYP) 2D6 isoenzyme.

DESIGN

In vitro and ex vivo analysis of changes in metabolism of study drugs.

SETTING

Laboratory.

PATIENTS

Not applicable.

INTERVENTIONS

Pooled human liver microsomal fractions prepared at CEDRA Corporation (now CellzDirect, Austin, Tex.) by the standard differential centrifugation method (lot 821-1). Human liver microsomes were pooled from 15 donors. Recombinant CYP 2D6-containing microsomes (Supersomes; lots 20 and 24 BD Gentest; Woburn, Mass.) were prepared from a baculovirus-infected insect cell line that expressed only the human CYP 2D6 isoform. Dextromethorphan, with and without effector, was incubated with pooled human liver and recombinant CYP 2D6-containing microsomes. Atomoxetine and dl-methylphenidate were tested at 0.1x, 1x, and 10x their reported therapeutic concentrations. Paroxetine, a known inhibitor of CYP 2D6, was used as a reference agent, and quinidine was used as a positive control inhibitor of CYP 2D6.

MAIN OUTCOME MEASURES

Changes in substrate metabolism indicative of CYP 2D6-mediated interactions.

RESULTS

Atomoxetine and paroxetine inhibited the formation of dextrorphan by about 50% in human liver microsomes and by more than 80% in recombinant microsomes; the profiles of atomoxetine and the known 2D6 inhibitor paroxetine were similar. High concentrations of dextromethorphan reversed the inhibition of its metabolism, indicating a competitive mechanism of the interaction. Conversely, dextromethorphan and dextrorphan only modestly inhibited atomoxetine and paroxetine metabolism. dl-Methylphenidate did not inhibit dextrorphan formation in either microsome preparation, and dl-methylphenidate metabolism was unaffected by dextromethorphan or dextrorphan.

CONCLUSION

These results demonstrate the potential for in vivo interactions between dextromethorphan and atomoxetine in patients with ADHD. However, they do not support the plausibility of an in vivo interaction between dextromethorphan and dl-methylphenidate.

Population pharmacokinetic analysis for nelfinavir and its metabolite M8 in virologically controlled HIV-infected patients on HAART

AIMS

To describe the pharmacokinetics of nelfinavir and its main metabolite M8 in HIV-infected patients with a sustained virological response, to characterize the effect of covariates and to estimate inter- and intra-individual variability in the pharmacokinetics.

METHODS

Three hundred and twenty concentrations of both nelfinavir and M8 were measured in 46 patients enrolled in the COPHAR 1-ANRS 102 study. Blood samples were taken at a first visit (one sample before drug administration and four samples at fixed times after) and at a second visit 1 to 3 months later (one before and one 3 h after drug administration). The data from both visits on nelfinavir and M8 were modelled jointly in all patients using a population approach.

RESULTS

A one-compartment model with first-order absorption and elimination best described nelfinavir data, with an additional compartment incorporating a first order rate-constant describing the metabolism of the drug to M8. For nelfinavir, the apparent volume of distribution (V/F ) (95% confidence interval for the mean), was 309 l (185, 516), the absorption rate constant (k(a)) was 0.4 h(-1) (0.2, 0.8), and the apparent clearance (CL/F ) was 37.3 l h(-1) (32, 44). For M8, V(m) /(Fk(m)) and CL(m)/(Fk(m)) were 866 l h(-1) (351, 2161) and 1670 l (965, 2894), respectively. The interindividual variabilities were 34.9%, 34.3% and 62.2% for V/F, CL/F and CL(m)/(Fk(m)), respectively. The interoccasion variability was 27.8% for CL/F. The mean half-lives were 05.38 h and 00.44 h for nelfinavir and M8, respectively. Significant but opposite effects of comedication with zidovudine were found on nelfinavir CL/F and M8 CL(m)/(Fk(m)), but they were not considered to be clinically relevant.

CONCLUSIONS

A joint model was found to describe adequately nelfinavir and M8 concentrations and was used to estimate pharmacokinetic parameters for M8. The model can be used to build reference pharmacokinetic profiles for therapeutic drug monitoring of the drug.

Prediction of in vivo drug clearance from in vitro data. I: impact of inter-individual variability

The Simcyp Population-Based ADME Simulator was used to predict median drug clearances and their associated variance from in vitro data. Fifteen drugs satisfied the entry criteria for the study and the relevant information (in vitro metabolism data and in vivo human clearance values) were collated from the literature. Predicted values of median clearances fell within 2-fold of observed values for 73% of the drugs (oral route) and 78% of the drugs (intravenous route) when microsomal binding was disregarded, and for 93% (oral) and 100% (intravenous) when it was considered. Irrespective of whether microsomal binding was considered, the predicted fold variability fell within 2-fold of the observed variability for 80% (oral) and 67% (intravenous) of the drugs.

Application of a combined effect compartment and binding model for gastric acid inhibition of AR-HO47108: a potassium competitive acid blocker, and its active metabolite AR-HO47116 in the dog

The effect of AR-HO47108, a potassium competitive acid blocker, and its active metabolite AR-HO47116 was studied in Heidenhain pouch dogs following administration of single oral and intravenous doses of the two compounds. The histamine-stimulated acid secretion was measured in different periods after dose up to 24h. All data obtained in the different studies was pooled and analyzed by non-linear mixed effects modelling. It was found that there is a delay between the plasma concentration-time peak and the maximum inhibitory effect and that the effect persisted longer than anticipated from the plasma concentration half-lives of the compounds. In addition, it was found that the peak effect was reached earlier at higher doses. The effect data was well described by a combined effect compartment and binding model and both distribution to the biophase i.e. the canaliculus of the parietal cell and a rate limiting binding interaction between drug and enzyme appear to contribute to the observed delay. In addition, a secretion rate dependent washout from the biophase may contribute. Furthermore, because the parent compound and metabolite bind to the same enzyme, the effect is determined by competition between the two for the same enzyme. The metabolite was found to be less potent than the parent compound, with Kd values of the combined model of 125 and 11.2 nM for the metabolite and parent compound, respectively. However, the metabolite is generated in high concentrations that rapidly exceed the concentration of parent compound after oral administration of parent compound, and this together with its longer plasma half-life will make its contribution to the overall effect increase with time and slightly prolong the duration of the effect.

Polymorphisme génétique et interactions médicamenteuses : leur importance dans le traitement de la douleur

OBJECTIVES

To evaluate the impact of certain genetic polymorphisms on variable responses to analgesics

SOURCES

Systematic review, by means of a structured computerized search in the Medline database (1966-2004). Articles in English and French were selected. References in relevant articles were also retrieved.

MAIN FINDINGS

Most analgesics are metabolized by CYP isoenzymes subject to genetic polymorphism. NSAIDs are metabolized by CYP2C9; opioids described as "weak" (codeine, tramadol), anti-depressants and dextromethorphan are metabolized by CYP2D6 and some "potent" opioids (buprenorphine, methadone or fentanyl) by CYP3A4/5. After the usual doses have been administered, drug toxicity or, on the contrary, therapeutic ineffectiveness may occur, depending on polymorphism and the substance. Drug interactions mimicking genetic defects because of the existence of CYP inhibitors and inducers, also contribute to the variable response to analgesics. Some opioids are substrates of P-gp, a transmembrane transporter also subject to genetic polymorphism. However, P-gp could only play a minor modulating role in man on the central effects of morphine, methadone and fentanyl.

CONCLUSION

In the near future, pharmacogenetics should enable us to optimize therapeutics by individualizing our approach to analgesic drugs and making numerous analgesics safer and more effective. The clinical usefulness of these individualized approaches will have to be demonstrated by appropriate pharmacoeconomic studies and analyses.

Intravenous dextromethorphan to human volunteers: relationship between pharmacokinetics and anti-hyperalgesic effect

The aim of this study was to investigate the effect of dextromethorphan (DM) 0.5 mg/kg administered intravenously (i.v.) on hyperalgesia and pain after a tissue injury in human volunteers, and to describe the relationship between pharmacokinetic and pharmacodynamic data. The heat-capsaicin sensitisation model, a well-established experimental hyperalgesia model was induced in 24 healthy, male volunteers aged 21-35 years. The subjects received i.v. DM 0.5 mg/kg or isotonic saline on two separate study sessions. The primary outcome measure from 0 to 3 h was reduction in area of established secondary hyperalgesia. Secondary outcome measures were reduction in area of secondary hyperalgesia in response to brief thermal stimulation, heat pain detection thresholds and painfulness after tonic heat pain. Blood samples were collected throughout the study to describe the relationship between pharmacokinetic and pharmacodynamic data. Intravenous DM 0.5 mg/kg significantly reduced areas of established secondary hyperalgesia with an average of 39% (P<0.05). Development of secondary hyperalgesia was substantially prevented by DM (P<0.05). No significant effect was seen on either heat pain detection thresholds or after tonic heat pain. The pharmacokinetic-pharmacodynamic relationship showed a large inter-subject variation with a mean delay in effect of nearly 2 h in relation to peak serum concentration. The results strongly indicate that DM is an anti-hyperalgesic drug. The delay in effect may be explained by several mechanisms and suggests that timing of DM administration is an essential factor for using the drug in clinical settings.

Plasma profile and pharmacokinetics of dextromethorphan after intravenous and oral administration in healthy dogs

Dextromethorphan is an N-methyl-D-aspartate (NMDA) noncompetitive antagonist which has been used as an antitussive, analgesic adjunct, probe drug, experimentally to attenuate acute opiate and ethanol withdrawal, and as an anticonvulsant. A metabolite of dextromethorphan, dextrorphan, has been shown to behave pharmacodynamically in a similar manner to dextromethorphan. The pharmacokinetics of dextromethorphan were examined in six healthy dogs following intravenous (2.2 mg/kg) and oral (5 mg/kg) administration in a randomized crossover design. Dextromethorphan behaved in a similar manner to other NMDA antagonists upon injection causing muscle rigidity, ataxia to recumbency, sedation, urination, and ptyalism which resolved within 90 min. One dog repeatedly vomited upon oral administration and was excluded from oral analysis. Mean +/- SD values for half-life, apparent volume of distribution, and clearance after i.v. administration were 2.0 +/-0.6 h, 5.1 +/- 2.6 L/kg, and 33.8 +/- 16.5 mL/min/kg. Oral bioavailability was 11% as calculated from naive pooled data. Free dextrorphan was not detected in any plasma sample, however enzymatic treatment of plasma with glucuronidase released both dextromethorphan and dextrorphan indicating that conjugation is a metabolic route. The short half-life, rapid clearance, and poor bioavailability of dextromethorphan limit its potential use as a chronic orally administered therapeutic.

The effect of quinidine, used as a probe for the involvement of P-glycoprotein, on the intestinal absorption and pharmacodynamics of methadone

AIMS

There is considerable unexplained interindividual variability in the methadone dose-effect relationship. The efflux pump P-glycoprotein (P-gp) regulates brain access and intestinal absorption of many drugs. Evidence suggests that methadone is a P-gp substrate in vitro, and P-gp affects methadone analgesia in animals. However the role of P-gp in human methadone disposition and pharmacodynamics is unknown. This investigation tested the hypothesis that the intestinal absorption and pharmacodynamics of oral and intravenous methadone are greater after inhibition of intestinal and brain P-gp, using the P-gp inhibitor quinidine as an in vivo probe.

METHODS

Two randomized, double-blind, placebo-controlled, balanced crossover studies were conducted in healthy subjects. Pupil diameters and/or plasma concentrations of methadone and the primary metabolite EDDP were measured after 10 mg intravenous or oral methadone HCl, dosed 1 h after oral quinidine (600 mg) or placebo.

RESULTS

Quinidine did not alter the effects of intravenous methadone. Miosis t(max) (0.3 +/- 0.3 vs 0.3 +/- 0.2 h (-0.17, 0.22)), peak (5.3 +/- 0.8 vs 5.1 +/- 1.0 mm (0.39, 0.84)) and AUC vs time (25.0 +/- 5.7 vs 26.8 +/- 7.1 mm h (-6.1, 2.5)) were unchanged (placebo vs quinidine (95% confidence interval on the difference)). Quinidine increased (P < 0.05) plasma methadone concentrations during the absorptive phase, decreased t(max) (2.4 +/- 0.7 vs 1.6 +/- 0.9 h (0.33, 1.2)), and increased peak miosis (3.2 +/- 1.5 vs 4.3 +/- 1.6 mm (-1.96, -0.19)) after oral methadone. The C(max) (55.6 +/- 10.3 vs 59.4 +/- 14.1 ng ml(-1) (-8.5, 0.65)) and AUC of methadone (298 +/- 46 vs 316 +/- 74 ng ml(-1) h (-54, 18)) were unchanged, as were the EDDP : methadone AUC ratios. Quinidine had no effect on the rate constant for transfer of methadone between plasma and effect compartment (k(e0)) (2.6 +/- 2.6 vs 2.5 +/- 1.4 h(-1) (-3.5, 4.2)).

CONCLUSIONS

Quinidine increased the plasma concentrations of oral methadone in the absorptive phase and the miosis caused by methadone, suggesting that intestinal P-gp affects oral methadone absorption and hence its clinical effects. Quinidine had no effect on methadone pharmacodynamics after intravenous administration, suggesting that if quinidine is an effective inhibitor of brain P-gp, then P-gp does not appear to be a determinant of the access of methadone to the brain.