Challenges in translational drug research in neuropathic and inflammatory pain: the prerequisites for a new paradigm.

AIM: Despite an improved understanding of the molecular mechanisms of nociception, existing analgesic drugs remain limited in terms of efficacy in chronic conditions, such as neuropathic pain. Here, we explore the underlying pathophysiological mechanisms of neuropathic and inflammatory pain and discuss the prerequisites and opportunities to reduce attrition and high-failure rate in the development of analgesic drugs. METHODS: A literature search was performed on preclinical and clinical publications aimed at the evaluation of analgesic compounds using MESH terms in PubMed. Publications were selected, which focused on (1) disease mechanisms leading to chronic/neuropathic pain and (2) druggable targets which are currently under evaluation in drug development. Attention was also given to the role of biomarkers and pharmacokinetic-pharmacodynamic modelling. RESULTS: Multiple mechanisms act concurrently to produce pain, which is a non-specific manifestation of underlying nociceptive pathways. Whereas these manifestations can be divided into neuropathic and inflammatory pain, it is now clear that inflammatory mechanisms are a common trigger for both types of pain. This has implications for drug development, as the assessment of drug effects in experimental models of neuropathic and chronic pain is driven by overt behavioural measures. By contrast, the use of mechanistic biomarkers in inflammatory pain has provided the pharmacological basis for dose selection and evaluation of non-steroidal anti-inflammatory drugs (NSAIDs). CONCLUSION: A different paradigm is required for the identification of relevant targets and candidate molecules whereby pain is coupled to the cause of sensorial signal processing dysfunction rather than clinical symptoms. Biomarkers which enable the characterisation of drug binding and target activity are needed for a more robust dose rationale in early clinical development. Such an approach may be facilitated by quantitative clinical pharmacology and evolving technologies in brain imaging, allowing accurate assessment of target engagement, and prediction of treatment effects before embarking on large clinical trials.

Assessment of Interspecies Differences in Drug-Induced QTc Interval Prolongation in Cynomolgus Monkeys, Dogs and Humans.

BACKGROUND AND PURPOSE: The selection of the most suitable animal species and subsequent translation of the concentration-effect relationship to humans are critical steps for accurate assessment of the pro-arrhythmic risk of candidate molecules. The objective of this investigation was to assess quantitatively the differences in the QTc prolonging effects of moxifloxacin between cynomolgus monkeys, dogs and humans. The impact of interspecies differences is also illustrated for a new candidate molecule. EXPERIMENTAL APPROACH: Pharmacokinetic data and ECG recordings from pre-clinical protocols in monkeys and dogs and from a phase I trial in healthy subjects were identified for the purpose of this analysis. A previously established Bayesian model describing the combined effect of heart rate, circadian variation and drug effect on the QT interval was used to describe the pharmacokinetic-pharmacodynamic relationships. The probability of a ≥ 10 ms increase in QT was derived as measure of the pro-arrhythmic effect. KEY RESULTS: For moxifloxacin, the concentrations associated with a 50% probability of QT prolongation ≥ 10 ms (Cp50) varied from 20.3 to 6.4 and 2.6 µM in dogs, monkeys and humans, respectively. For NCE05, these values were 0.4 µM vs 2.0 µM for monkeys and humans, respectively. CONCLUSIONS AND IMPLICATIONS: Our findings reveal significant interspecies differences in the QT-prolonging effect of moxifloxacin. In addition to the dissimilarity in pharmacokinetics across species, it is likely that differences in pharmacodynamics also play an important role. It appears that, regardless of the animal model used, a translation function is needed to predict concentration-effect relationships in humans.

Prospective Evaluation of a Model-Based Dosing Regimen for Amikacin in Preterm and Term Neonates in Clinical Practice.

Based on a previously derived population pharmacokinetic model, a novel neonatal amikacin dosing regimen was developed. The aim of the current study was to prospectively evaluate this dosing regimen. First, early (before and after second dose) therapeutic drug monitoring (TDM) observations were evaluated for achieving target trough (<3 mg/liter) and peak (>24 mg/liter) levels. Second, all observed TDM concentrations were compared with model-predicted concentrations, whereby the results of a normalized prediction distribution error (NPDE) were considered. Subsequently, Monte Carlo simulations were performed. Finally, remaining causes limiting amikacin predictability (i.e., prescription errors and disease characteristics of outliers) were explored. In 579 neonates (median birth body weight, 2,285 [range, 420 to 4,850] g; postnatal age 2 days [range, 1 to 30 days]; gestational age, 34 weeks [range, 24 to 41 weeks]), 90.5% of the observed early peak levels reached 24 mg/liter, and 60.2% of the trough levels were <3 mg/liter (93.4% ≤5 mg/liter). Observations were accurately predicted by the model without bias, which was confirmed by the NPDE. Monte Carlo simulations showed that peak concentrations of >24 mg/liter were reached at steady state in almost all patients. Trough values of <3 mg/liter at steady state were documented in 78% to 100% and 45% to 96% of simulated cases with and without ibuprofen coadministration, respectively; suboptimal trough levels were found in patients with postnatal age <14 days and current weight of >2,000 g. Prospective evaluation of a model-based neonatal amikacin dosing regimen resulted in optimized peak and trough concentrations in almost all patients. Slightly adapted dosing for patient subgroups with suboptimal trough levels was proposed. This model-based approach improves neonatal dosing individualization.

Generating Virtual Patients by Multivariate and Discrete Re-Sampling Techniques.

PURPOSE: Clinical Trial Simulations (CTS) are a valuable tool for decision-making during drug development. However, to obtain realistic simulation scenarios, the patients included in the CTS must be representative of the target population. This is particularly important when covariate effects exist that may affect the outcome of a trial. The objective of our investigation was to evaluate and compare CTS results using re-sampling from a population pool and multivariate distributions to simulate patient covariates. METHODS: COPD was selected as paradigm disease for the purposes of our analysis, FEV1 was used as response measure and the effects of a hypothetical intervention were evaluated in different populations in order to assess the predictive performance of the two methods. RESULTS: Our results show that the multivariate distribution method produces realistic covariate correlations, comparable to the real population. Moreover, it allows simulation of patient characteristics beyond the limits of inclusion and exclusion criteria in historical protocols. CONCLUSION: Both methods, discrete resampling and multivariate distribution generate realistic pools of virtual patients. However the use of a multivariate distribution enable more flexible simulation scenarios since it is not necessarily bound to the existing covariate combinations in the available clinical data sets.

Prediction of disease progression, treatment response and dropout in chronic obstructive pulmonary disease (COPD).

PURPOSE: Drug development in chronic obstructive pulmonary disease (COPD) has been characterised by unacceptably high failure rates. In addition to the poor sensitivity in forced expiratory volume in one second (FEV1), numerous causes are known to contribute to this phenomenon, which can be clustered into drug-, disease- and design-related factors. Here we present a model-based approach to describe disease progression, treatment response and dropout in clinical trials with COPD patients. METHODS: Data from six phase II trials lasting up to 6 months were used. Disease progression (trough FEV1 measurements) was modelled by a time-varying function, whilst the treatment effect was described by an indirect response model. A time-to-event model was used for dropout RESULTS: All relevant parameters were characterised with acceptable precision. Two parameters were necessary to model the dropout patterns, which was found to be partly linked to the treatment failure. Disease severity at baseline, previous use of corticosteroids, gender and height were significant covariates on disease baseline whereas disease severity and reversibility to salbutamol/salmeterol were significant covariates on Emax for salmeterol active arm. CONCLUSION: Incorporation of the various interacting factors into a single model will offer the basis for patient enrichment and improved dose rationale in COPD.

Population pharmacokinetic modelling of total and unbound cefazolin plasma concentrations as a guide for dosing in preterm and term neonates.

OBJECTIVES: Cefazolin is frequently administered for antimicrobial prophylaxis and treatment of infections. In neonates, pharmacokinetic observations are limited and dosing regimens variable. The aim of this study was to describe the pharmacokinetics of cefazolin in neonates based on total and unbound concentrations to optimize cefazolin dosing. METHODS: Thirty-six neonates [median birth body weight 2720 (range 540-4200) g, current body weight (cBW) 2755 (830-4200) g and postnatal age (PNA) 9 (1-30) days] receiving intravenous cefazolin (50 mg/kg/8 h) were included. Based on 119 total and unbound plasma concentrations, a population pharmacokinetic analysis with a covariate analysis was performed. Monte Carlo simulations were performed aiming for unbound concentrations above an MIC of 8 mg/L (>60% of the time) in all patients. RESULTS: A one-compartment pharmacokinetic model was developed in which total and unbound concentrations were linked by maximum protein binding (Bmax) of 136 mg/L and a dissociation constant (KD) for cefazolin protein binding of 46.5 mg/L. cBW was identified as covariate for volume of distribution (V), bBW and PNA for clearance and albumin plasma concentration for Bmax, explaining 50%, 58% and 41% of inter-individual variability in V, clearance and Bmax, respectively. Based on Monte Carlo simulations, a body weight- and PNA-adapted dosing regimen that resulted in similar exposure across different weight and age groups was proposed. CONCLUSIONS: A neonatal pharmacokinetic model taking into account total and unbound cefazolin concentrations with saturable plasma protein binding was identified. As cBW and PNA were the most important covariates, these may be used for individualized dosing in neonates.

Semi-mechanistic modelling of the analgesic effect of gabapentin in the formalin-induced rat model of experimental pain.

PURPOSE: The formalin-induced rat model of nociception involves moderate continuous pain. Formalin-induced pain results in a typical repetitive flinching behaviour, which displays a biphasic pattern characterised by peaks of pain. Here we described the time course of pain response and the analgesic effect of gabapentin using a semi-mechanistic modelling approach. METHODS: Male Sprague-Dawley rats received gabapentin (10-100 mg/kg) or placebo 1 h prior to the formalin injection, as per standard protocol. A reduction in the frequency of the second peak of flinching was used as a behavioural measure of gabapentin-mediated anti-nociception. The flinching response was modelled using a mono-exponential function to characterise the first peak and an indirect response model with a time variant synthesis rate for the second. PKPD modelling was performed using a population approach in NONMEM v.7.1.2. RESULTS: The time course of the biphasic response was adequately described by the proposed model, which included separate expressions for each phase. Gabapentin was found to reversibly decrease, but not suppress the flinching frequency of the second response peak only. The mean IC50 estimate was 7,510 ng/ml, with relative standard error (RSE%) of 40%. CONCLUSIONS: A compartmental, semi-mechanistic model provides the basis for further understanding of the formalin-induced flinching response and consequently to better characterisation of the properties of gabapentin, such as the potency in individual animals. Moreover, despite high exposure levels, model predictions show that gabapentin does not completely suppress behavioural response in the formalin-induced pain model.

Establishing in vitro to clinical correlations in the evaluation of cardiovascular safety pharmacology.

Preclinical studies are vital in establishing the efficacy and safety of a new chemical entity (NCE) in humans. To deliver meaningful information, experiments have to be well defined and provide outcome that is relevant and translatable to humans. This review briefly surveys the various preclinical experiments that are frequently conducted to assess drug effects on cardiac conductivity in early drug development. We examine the different approaches used to establish correlations between non-clinical and clinical settings and discuss their value in the evaluation of cardiovascular risk.

Capturing the dynamics of systemic Renin-Angiotensin-Aldosterone System (RAAS) peptides heightens the understanding of the effect of benazepril in dogs.

In dogs, activation of the Renin-Angiotensin-Aldosterone System (RAAS) is an important feature of congestive heart failure (CHF). Long-term increases in angiotensin II (AII) and aldosterone (ALD) lead to the progression of heart failure to its end stage. Angiotensin-converting enzyme inhibitors (ACEIs) are the foremost therapeutic option in the management of CHF. Recent literature has challenged the efficacy of ACEIs, based on modest reduction in urinary aldosterone (UALD) excretion despite marked inhibition of ACE activity. This study was designed to heighten the understanding of the effect of benazepril, a potent ACEI, on the RAAS, using a low-sodium diet as an experimental model of RAAS activation. Time course profiles of RAAS peptides and related areas under the curve (AUC) were used for comparison between benazepril and placebo groups. Results indicated substantial changes in the dynamics of these biomarkers. At presumed benazeprilat steady state, significant differences in AUC of plasma renin activity (+90%), angiotensin I (+43%), and AII (-53%) were found between benazepril and placebo-treated dogs. ALD decreased by 73% in plasma but only by 5% in urine. In conclusion, despite modest reduction in UALD excretion, benazepril markedly influences RAAS dynamics in dogs.

Optimised protocol design for the screening of analgesic compounds in neuropathic pain.

We have previously shown how screening experiments for neuropathic pain can be optimised taking into account parameter and model uncertainty. Here we demonstrate how optimised protocols can be used to screen and rank candidate molecules. The concept is illustrated by pregabalin as a new chemical entity and gabapentin as a reference compound. ED-optimality was applied to a logistic regression model describing the relationship between drug exposure and response to evoked pain in the complete Freund's adjuvant (CFA) model in rats. Design variables for optimisation of the experimental protocol included dose levels and sampling times. Prior information from the reference compound was used in conjunction with relative in vitro potency as priors. Results from simulated scenarios were then combined with fitting of experimental data to estimate precision and bias of model parameters for the empirical and optimised designs. The pharmacokinetics of pregabalin was described by a two-compartment model. The expected value of EC(50) of pregabalin was 637.5 ng ml(-1). Model-based analysis of the data yielded median (range) of EC(50) values of 1,125 (898-2412) ng ml(-1) for the empirical protocol and 755 (189-756) ng ml(-1) for the optimised design. In contrast to current practice, optimal design entails different sampling schedule across dose levels. ED-optimised designs should become standard practice in the screening of candidate molecules. It ensures lower bias when estimating the drug potency, facilitating accurate ranking and selection of compounds for further development.

Application of ED-optimality to screening experiments for analgesic compounds in an experimental model of neuropathic pain.

In spite of the evidence regarding high variability in the response to evoked pain, little attention has been paid to its impact on the screening of drugs for inflammatory and neuropathic pain. In this study, we explore the feasibility of introducing optimality concepts to experimental protocols, enabling estimation of parameter and model uncertainty. Pharmacokinetic (PK) and pharmacodynamic data from different experiments in rats were pooled and modelled using nonlinear mixed effects modelling. Pain data on gabapentin and placebo-treated animals were generated in the complete Freund's adjuvant model of neuropathic pain. A logistic regression model was applied to optimise sampling times and dose levels to be used in an experimental protocol. Drug potency (EC(50)) and interindividual variability (IIV) were considered the parameters of interest. Different experimental designs were tested and validated by SSE (stochastic simulation and estimation) taking into account relevant exposure ranges. The pharmacokinetics of gabapentin was described by a two-compartment PK model with first order absorption (CL = 0.159 l h(-1), V(2) = 0.118 l, V(3) = 0.253 l, Ka = 0.26 h(-1), Q = 1.22 l h(-1)). Drug potency (EC(50)) for the anti-allodynic effects was estimated to be 1400 ng ml(-1). Protocol optimisation improved bias and precision of the EC50 by 6 and 11.9. %, respectively, whilst IIV estimates showed improvement of 31.89 and 14.91 %, respectively. Our results show that variability in behavioural models of evoked pain response leads to uncertainty in drug potency estimates, with potential impact on the ranking of compounds during screening. As illustrated for gabapentin, ED-optimality concepts enable analysis of discrete data taking into account experimental constraints.

Analysis of the relationship between age and treatment response in migraine.

In migraine, headache severity varies with age. As a consequence, the effectiveness of medication may also depend on a patient's age. The purpose of this study was to assess the combined effect of age and drug treatment on headache characteristics. Using data from clinical trials of sumatriptan in adolescents and adults, we show how the interaction between age and drug exposure can be parameterised as a covariate on a Markov model that describes the decline of headache severity over three clinically defined stages (no relief, relief and pain-free status). The model explains important clinical observations: (i) the rates at which the pain relief and pain-free status were attained were found to be inversely related to age; (ii) in placebo-treated patients, the mean transit time from 'no relief' to 'relief' is 3 h for young adolescents and increases to 6 h for patients aged >or= 30 years; and (iii) sumatriptan reduces the transit time to 2 h, irrespective of age. These findings indicate that the therapeutic gain over placebo increases with age. Prospective studies of antimigraine drugs should take this relationship into account when extrapolating efficacy data from adults to adolescents.

Pharmacokinetic-pharmacodynamic modelling of fluvoxamine 5-HT transporter occupancy in rat frontal cortex.

BACKGROUND AND PURPOSE: The pharmacokinetic-pharmacodynamic (PK-PD) correlation of fluvoxamine 5-HT transporter (SERT) occupancy was determined in rat frontal cortex ex vivo. EXPERIMENTAL APPROACH: Rats (n=47) with permanent arterial and venous cannulas received a 30 min intravenous infusion of fluvoxamine (1 or 7.3 mg kg(-1)). At various time points after dosing, brains were collected for determination of fluvoxamine concentration and SERT occupancy. In addition, the time course of fluvoxamine concentration in plasma was determined up to the time of brain collection. In a separate study (n=26), the time course of fluvoxamine concentration in brain extracellular fluid (ECF) and plasma was determined. The results of the investigations were interpreted by nonlinear mixed effects modeling. KEY RESULTS: Highest SERT occupancy was reached at the first time point (10 or 15 min) and maintained for 1.5 and 7 h after 1 and 7.3 mg kg(-1), respectively. Thereafter, SERT occupancy decreased linearly at a rate of 8% h(-1). SERT occupancy could be directly related to plasma, brain ECF and brain tissue concentrations by a hyperbolic function (Bmax model). Maximal SERT occupancy (Bmax) was 95%. Estimated concentrations at half-maximal SERT occupancy (EC50) in plasma, ECF and brain tissue were 0.48, 0.22 and 14.8 ng mL(-1) respectively. The minimum value of the objective function decreased 12 points for ECF and brain tissue concentrations relative to plasma (P<0.01), presumably as a result of nonlinear brain distribution. CONCLUSIONS AND IMPLICATIONS: The proposed PK-PD model constitutes a useful basis for prediction of the time course of ex vivo SERT occupancy in behavioural studies with selective serotonin reuptake inhibitors.

Population pharmacokinetic modelling of the enterohepatic recirculation of diclofenac and rofecoxib in rats.

BACKGROUND AND PURPOSE: Enterohepatic recirculation (EHC) is a common pharmacokinetic phenomenon that has been poorly modelled in animals. The presence of EHC leads to the appearance of multiple peaks in the concentration-time profile and increased exposure, which may have implications for drug effect and extrapolation across species. The aim of this investigation was to develop a population pharmacokinetic model for diclofenac and rofecoxib that describes EHC and to assess its consequence for the pharmacodynamics of both drugs. EXPERIMENTAL APPROACH: The pharmacokinetics of diclofenac and rofecoxib was characterized in male rats following intravenous, intraperitoneal and oral administration. Blood samples were collected at pre-defined time points after dosing to determine plasma concentrations over time. A parametric approach using nonlinear mixed effects modelling was applied to describe EHC, whilst simulations were used to evaluate its impact on PGE(2) inhibition. KEY RESULTS: For diclofenac, EHC was described by a compartmental model with periodic transfer rate and metabolite formation rate. For rofecoxib, EHC modelling required a conversion compartment with first-order recycling rate and lag time. Based on model predictions, EHC causes an increase of 95% in the systemic exposure to diclofenac and of 15% in the exposure to rofecoxib. In addition, EHC prolongs the inhibition of PGE(2) and increases the duration of the anti-inflammatory effect (24 h for rofecoxib 10 mg kg(-1)) without affecting maximum inhibition. CONCLUSIONS AND IMPLICATIONS: Our findings show the relevance of exploring EHC in a quantitative manner to accurately interpret pharmacodynamic findings in vivo, in particular when scaling across species.

Prediction of attack frequency in migraine treatment.

Usually limited information about the frequency of migraine episodes is derived from acute migraine trials. However, the design of some studies is such that they also provide relevant information about the attack frequency without the bias associated with patient expectations of treatment effect between attacks during prophylaxis trials. Using clinical data from repeated migraine attacks treated with placebo, naratriptan 2.5 mg or sumatriptan 100 mg, we show that attack and interictal periods can be described by a random probability distribution. Based on a gamma distribution, the mean interval between attacks was estimated to be 24 (17-34) days for placebo, 23 (18-29) days for naratriptan 2.5 mg and 22 (17-28) for sumatriptan 100 mg. These findings suggest that the interictal interval is not affected by abortive treatment with triptans. Interpretation of these results may be limited by the study type, yet the method represents a new tool for the evaluation of disease dynamics and treatment effect in the prophylaxis of migraine.

Mechanism-based PK/PD modeling of the respiratory depressant effect of buprenorphine and fentanyl in healthy volunteers.

The objective of this study was to characterize the pharmacokinetic/pharmacodynamic (PK/PD) relationship of buprenorphine and fentanyl for the respiratory depressant effect in healthy volunteers. Data on the time course of the ventilatory response at a fixed P(ET)CO(2) of 50 mm Hg and P(ET)O(2) of 110 mm Hg following intravenous administration of buprenorphine and fentanyl were obtained from two phase I studies (50 volunteers received buprenorphine: 0.05-0.6 mg/70 kg and 24 volunteers received fentanyl: 0.075-0.5 mg/70 kg). The PK/PD correlations were analyzed using nonlinear mixed effects modeling. A two- and three-compartment pharmacokinetic model characterized the time course of fentanyl and buprenorphine concentration, respectively. Three structurally different PK/PD models were evaluated for their appropriateness to describe the time course of respiratory depression: (1) a biophase distribution model with a fractional sigmoid E(max) pharmacodynamic model, (2) a receptor association/dissociation model with a linear transduction function, and (3) a combined biophase distribution-receptor association/dissociation model with a linear transduction function. The results show that for fentanyl hysteresis is entirely determined by the biophase distribution kinetics, whereas for buprenorphine hysteresis is caused by a combination of biophase distribution kinetics and receptor association/dissociation kinetics. The half-time values of biophase equilibration (t(1/2, k(eo))) were 16.4 and 75.3 min for fentanyl and buprenorphine, respectively. In addition, for buprenorphine, the value of k(on) was 0.246 ml/ng/min and the value of k(off) was 0.0102 min(-1). The concentration-effect relationship of buprenorphine was characterized by a ceiling effect at higher concentrations (intrinsic activity alpha=0.56, 95% confidence interval (CI): 0.50-0.62), whereas fentanyl displayed full respiratory depressant effect (alpha=0.91, 95% CI: 0.19-1.62).

Pharmacokinetic-pharmacodynamic modelling of S(-)-atenolol in rats: reduction of isoprenaline-induced tachycardia as a continuous pharmacodynamic endpoint.

BACKGROUND AND PURPOSE: For development of mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) models, continuous recording of drug effects is essential. We therefore explored the use of isoprenaline in the continuous measurement of the cardiovascular effects of antagonists of beta-adrenoceptors (beta-blockers). The aim was to validate heart rate as a pharmacodynamic endpoint under continuous isoprenaline-induced tachycardia by means of PK-PD modelling of S(-)-atenolol. EXPERIMENTAL APPROACH: Groups of WKY rats received a 15 min i.v. infusion of 5 mg kg(-1) S(-)-atenolol, with or without i.v. infusion of 5 microg kg(-1) h(-1) isoprenaline. Heart rate was continuously monitored and blood samples were taken. KEY RESULTS: A three-compartment model best described the pharmacokinetics of S(-)-atenolol. The PK-PD relationship was described by a sigmoid Emax model and an effect compartment was used to resolve the observed hysteresis. In the group without isoprenaline, the variability in heart rate (30 b.p.m.) approximated the maximal effect (Emax=43+/-18 b.p.m.), leaving the parameter estimate of potency (EC50=28+/-27 ng ml(-1)) unreliable. Both precise and reliable parameter estimates were obtained during isoprenaline-induced tachycardia: 517+/-13 b.p.m. (E0), 168+/-15 b.p.m. (Emax), 49+/-14 ng ml(-1) (EC50), 0.042+/-0.012 min(-1) (k(eo)) and 0.95+/-0.34 (n). CONCLUSIONS AND IMPLICATIONS: Reduction of heart rate during isoprenaline-induced tachycardia is a reliable pharmacodynamic endpoint for beta-blockers in vivo in rats. Consequently this experimental approach will be used to investigate the relationship between drug characteristics and in vivo effects of different beta-blockers.

Influence of biophase distribution and P-glycoprotein interaction on pharmacokinetic-pharmacodynamic modelling of the effects of morphine on the EEG.

BACKGROUND AND PURPOSE: The aim was to investigate the influence of biophase distribution including P-glycoprotein (Pgp) function on the pharmacokinetic-pharmacodynamic correlations of morphine's actions in rat brain. EXPERIMENTAL APPROACH: Male rats received a 10-min infusion of morphine as 4 mg kg(-1), combined with a continuous infusion of the Pgp inhibitor GF120918 or vehicle, 10 or 40 mg kg(-1). EEG signals were recorded continuously and blood samples were collected. KEY RESULTS: Profound hysteresis was observed between morphine blood concentrations and effects on the EEG. Only the termination of the EEG effect was influenced by GF120918. Biophase distribution was best described with an extended catenary biophase distribution model, with a sequential transfer and effect compartment. The rate constant for transport through the transfer compartment (k(1e)) was 0.038 min(-1), being unaffected by GF120918. In contrast, the rate constant for the loss from the effect compartment (k(eo)) decreased 60% after GF120918. The EEG effect was directly related to concentrations in the effect compartment using the sigmoidal E(max) model. The values of the pharmacodynamic parameters E(0), E(max), EC(50) and Hill factor were 45.0 microV, 44.5 microV, 451 ng ml(-1) and 2.3, respectively. CONCLUSIONS AND IMPLICATIONS: The effects of GF120918 on the distribution kinetics of morphine in the effect compartment were consistent with the distribution in brain extracellular fluid (ECF) as estimated by intracerebral microdialysis. However, the time-course of morphine concentrations at the site of action in the brain, as deduced from the biophase model, is distinctly different from the brain ECF concentrations.

Population pharmacokinetic modelling of non-linear brain distribution of morphine: influence of active saturable influx and P-glycoprotein mediated efflux.

BACKGROUND AND PURPOSE: Biophase equilibration must be considered to gain insight into the mechanisms underlying the pharmacokinetic-pharmacodynamic (PK-PD) correlations of opioids. The objective was to characterise in a quantitative manner the non-linear distribution kinetics of morphine in brain. EXPERIMENTAL APPROACH: Male rats received a 10-min infusion of 4 mg kg(-1) of morphine, combined with a continuous infusion of the P-glycoprotein (Pgp) inhibitor GF120918 or vehicle, or 40 mg kg(-1) morphine alone. Unbound extracellular fluid (ECF) concentrations obtained by intracerebral microdialysis and total blood concentrations were analysed using a population modelling approach. KEY RESULTS: Blood pharmacokinetics of morphine was best described with a three-compartment model and was not influenced by GF120918. Non-linear distribution kinetics in brain ECF was observed with increasing dose. A one compartment distribution model was developed, with separate expressions for passive diffusion, active saturable influx and active efflux by Pgp. The passive diffusion rate constant was 0.0014 min(-1). The active efflux rate constant decreased from 0.0195 min(-1) to 0.0113 min(-1) in the presence of GF120918. The active influx was insensitive to GF120918 and had a maximum transport (N(max)/V(ecf)) of 0.66 ng min(-1) ml(-1) and was saturated at low concentrations of morphine (C(50)=9.9 ng ml(-1)). CONCLUSIONS AND IMPLICATIONS: Brain distribution of morphine is determined by three factors: limited passive diffusion; active efflux, reduced by 42% by Pgp inhibition; low capacity active uptake. This implies blood concentration-dependency and sensitivity to drug-drug interactions. These factors should be taken into account in further investigations on PK-PD correlations of morphine.

Pharmacokinetic-pharmacodynamic modelling of drug-induced QTc interval prolongation in man: prediction from in vitro human ether-à-go-go-related gene binding and functional inhibition assays and conscious dog studies.

BACKGROUND AND PURPOSE: Functional measures of human ether-à-go-go-related gene (hERG; Kv 11.1) channel inhibition have been prioritized as an in vitro screening tool for candidate molecules. However, it is unclear how these results can be translated to humans. Here, we explore how data on drug binding and functional inhibition in vitro relate to QT prolongation in vivo. Using cisapride, sotalol and moxifloxacin as paradigm compounds, we assessed the relationship between drug concentrations, binding, functional measures and in vivo effects in preclinical species and humans. EXPERIMENTAL APPROACH: Pharmacokinetic-pharmacodynamic modelling was used to characterize the drug effects in hERG functional patch clamp, hERG radio-labelled dofetilide displacement experiments and QT interval in conscious dogs. Data were analysed in parallel to identify potential correlations between pharmacological activity in vitro and in vivo. KEY RESULTS: An Emax model could not be used due to large variability in the functional patch clamp assay. Dofetilide displacement revealed that binding curves are unrelated to the in vivo potency estimates for QTc prolongation in dogs and humans. Mean in vitro potency estimates ranged from 99.9 nM for cisapride to 1030 µM for moxifloxacin. CONCLUSIONS AND IMPLICATIONS: The lack of standardized protocols for in vitro assays leads to significant differences in experimental conditions, making the assessment of in vitro-in vivo correlations unreliable. Identification of an accurate safety window during the screening of candidate molecules requires a quantitative framework that disentangles system- from drug-specific properties under physiological conditions, enabling translation of the results to humans. Similar considerations will be relevant for the comprehensive in vitro pro-arrhythmia assay initiative.