F. Larsen (1), C. Bundgaard (2)
(1) Clinical Pharmacology & Pharmacokinetics, (2) Discovery ADME, H. Lundbeck A/S, Copenhagen, Denmark.
Objectives: To characterise the PK/PD relationships including inter-individual variability (IIV) of ESC-induced 5-HT response after acute administration to rats. A mechanistic turnover feedback model was assessed using a non-linear mixed effects (NLME) modelling approach.
Methods: Rats (n=17) were infused with 2.5, 5, or 10 mg/kg ESC or vehicle over 60 min.
Extracellular 5-HT in hippocampus was monitored using microdialysis. Simultaneously, serial blood was sampled for ESC unbound plasma levels. The structural PK/PD model was a turnover model with drug-induced inhibition of loss of response (kout) and an inhibitory feedback moderator function resembling the acute mechanism of action of ESC[1]. Response acted linearly on the production (ktol) of the moderator, which acted inversely on the production (kin) of response (% of basal level 5-HT normalised to 100%). Additional model parameters were RBAS (baseline 5-HT), n (Hill-factor), Imax (maximal inhibition of loss of response) and IC50 (plasma levels of ESC resulting in 50% inhibition of loss of response). The PK model was fitted and the final parameter estimates were fixed in the combined PK/PD analysis. The PD model was described by differential equations (ADVAN9). IIV was modelled using exponential errors. The residual variability was proportional for the PK and additive for the PD. The final modelwas evaluated using 95% predictive
performance plots and bootstrap analysis. NONMEM VI (Globomax) was used for the modelling.
Results: A two-compartment PK model (ADVAN3, TRANS4) adequately described the ESC plasma levels. IIV was identified for CL (17%), V1 (45%), Q (15%). Dose level on clearance was the only significant covariate. 5-HT levels were significantly increased following drug
administration. However, at high doses, the mean response-time curves were almost identical.
Therefore, a simple intrinsic turnover model was considered inappropriate. The final model included no further covariates and fitted all the response-data well and resulted in parameter estimates with acceptable precision. IIV was identified for RBAS (16%), Imax (14%) and IC50 (82%).
The residual variability was 18% for the PK and 30 response units (%) for the PD.
Poster: Applications- CNS
Mathilde Marchand Supporting the recommended paediatric dosing regimen for
rufinamide using clinical trial simulation
Mathilde Marchand (1, 2), Eliane Fuseau (1), David Critchley (3)
(1) EMF consulting, Aix en Provence, France; (2) EA3286 Laboratoire de Toxicocinétique et Pharmacocinétique, Marseille, France; (3) EISAI Global Clinical development, UK
Background: Rufinamide marketing application was reviewed recently by the CHMP (Committee for medicinal products for human use), for the treatment of seizures associated with Lennox-Gastaut syndrome (LGS) as adjunctive therapy in patients 4 years and older. Relationships between
pharmacokinetics, efficacy and safety parameters have been established. However, only one study had been conducted in patients with Lennox-Gastaut syndrome. To document the exposure in a larger population, simulations of exposure and efficacy under the proposed dosing regimen were performed, so that the main sources of variability could be understood and dosing regimens found to give exposure similar to that shown to be safe and efficacious in larger populations of patients with others types of epilepsy.
Methods: Monte Carlo simulations were used to investigate the effect on rufinamide exposure and efficacy in the patient population of different proposed dosing regimens. Four dosing regimens, varying in term of initial dose, dose increment and maximum daily dose were defined based on patient body weight from 4 to 35 years of age. Since exposure variability appeared to increase in children with body weight less than 30 kg, additional simulations of exposure were carried out in that population.
Results/Conclusions: The simulations of the different dosing regimen resulted in rufinamide exposure similar to that observed during clinical trials. The results of the simulated total seizure frequency per day show a large variability, which was also observed in the LGS clinical study. The concentrations simulated in patients with a body weight less than 30 kg presented a large
interindividual variability than other patients. Additional simulations demonstrated that this
increased variability was due to greater valproate concentration in some of the children treated with rufinamide. Complementary investigations of maximum daily dose lead to propose maximum daily dose for patients less than 30 kg receiving antiepileptic drugs: rufinamide and valproate. This recommendation would ensure that children (less than 30 kg) treated with rufinamide and valproate concomitantly would not be overexposed to rufinamide.
Poster: Applications- CNS
Gianluca Nucci Population pharmacokinetic modelling of pimozide and its relation
to CYP2D6 genotype.
Gianluca Nucci, Keith Muir and Roberto Gomeni
Clinical Pharmacokinetics Modelling & Simulation, GlaxoSmithKline, Verona Italy Background: Pimozide is a dopamine receptor antagonist used to treat obsessive compulsive disorder associated with Tourette's syndrome. In humans, pimozide is believed to be primarily metabolised by cytochrome P450 enzyme system CYP3A4 [1, 2] although CYP2D6 may also play a role .
Objectives: The objectives of the population pharmacokinetic analysis were to model the
pharmacokinetics of pimozide in subjects of different CYP2D6 phenotypes in order to elucidate the role of CYP2D6 in pimozide disposition.
Methods: A two-compartment model with first-order absorption, and lag-time was implemented for Pimozide as basic model. It was fitted to the data of 32 healthy volunteers using NONMEM.
Individual covariate used to refine the model estimates were age, weight, sex and CYP2D6 polymorphisms.
Results: Based on CYP2D6 genotype, the subjects had the following predicted metabolizer status:
Extensive (EM) N=26, Intermediate (IM) N=4, and Poor (PM) N=2. CYP2D6 genotype was found to highly significantly improve model fitting to the data, with average population clearance of 14, 36 and 55 L/h in PM, IM and EM respectively. The variability of pimozide plasma concentrations was caused to a relevant degree by CYP2D6 (CVb% is decreased from 60% to 30% when CYP2D6 activity was taken into consideration). Individual body weight was found to be significantly linked to pimozide volume of distribution.
Conclusions: These population PK results suggest that pimozide CYP2D6 metaboliser status impacts significantly on the PK of pimozide, and CYP2D6 is at least as important as CYP3A4 in pimozide metabolism.
References:
[1] Desta Z, Kerbusch T, Flockhart DA. Effect of clarithromycin on the pharmacokinetics and pharmacodynamics of pimozide in healthy poor and extensive metabolizers of cytochrome P450
Poster: Applications- CNS
Gijs Santen Comparing treatment effect in depression trials: Mixed Model for
Repeated Measures vs Linear Mixed Model
Gijs Santen(1), Meindert Danhof(1), Oscar Della Pasqua(1,2)
1) Division of Pharmacology, LACDR, Leiden University, Leiden, the Netherlands. (2) Department of Clinical Pharmacokinetics/Modeling & Simulation, GlaxoSmithKline, Greenford, UK Objectives: It is a well known fact that depression trials may fail in 50% of the cases even if effective doses of an antidepressant drug are administered. A high placebo effect, large variability between patients and inadequate endpoints are commonly given as reasons for this high failure rate.
Therefore, investigations into alternative endpoints, novel study designs and statistical methods using historical data could lead to a reduction in the failure rate in clinical trials with anti-depressant drugs. In previous work we have explored the sensitivity of the Hamilton Depression Rating Scale (HAM-D) to treatment effect. The current work focuses on the impact of standard statistical analysis used to evaluate effect size in clinical trials, the Linear Mixed Model for Repeated Measures (MMRM) and compares it with a Linear Mixed Model (LMM).
Methods: Data from several double blind randomised placebo-controlled trials in Major Depression were extracted from GlaxoSmithKline's clinical database. Basically, the MMRM models repeated measures within a single individual as multivariate data with an unstructured covariance matrix that is assumed to identical across individuals. Treatment-time and baseline-time interactions are
modelled as fixed effects. The LMM models HAMD response with the interactions treatment-time and baseline-time as fixed effects, but includes a subject-specific effect. MMRM analysis was performed in SAS using proc mixed, whilst LMM was also fitted in SAS using proc mixed and WinBUGS, with missing data replacement by the posterior predictive distribution for the specific individual.
Results: Re-analysis of study data revealed minor differences for the estimates obtained with either method. However, when diagnostic plots are evaluated, it is clear that the MMRM shows a bias relative to LMM. Model bias was especially evident across the range of responses in the observed vs predicted plots and over the time course of response of an individual patient. In a few occasions, MMRM resulted in incorrect estimates of significance level and consequently wrong conclusions about treatment effect.
Conclusions: The analysis of HAM-D data with an identical unstructured covariance matrix across individuals may not be appropriate. The use of the LMM with subject-specific random effects and missing data replacement based on posterior prediction distributions may offer a better alternative to current methodology for the assessment of treatment effect in depression.
Poster: Applications- CNS
Armel Stockis Dose-response population modeling of the new antiepileptic drug
brivaracetam in add-on treatment of partial onset seizures.
Christian Laveille(1), Eric Snoeck(1), Brigitte Lacroix(2), Maria Laura Sargentini-Maier(2), Armel Stockis(2)
(1) Exprimo, Lummen, Belgium; (2)UCB Pharma, Braine-l'Alleud, Belgium.
Objectives: To describe the individual change in seizure frequency from baseline after treatment with brivaracetam or placebo, to model the dose-response relationship and to assess the impact of potential covariates.
Methods: Efficacy data were used from two double-blind, placebo-controlled parallel-group phase-IIB trials in 363 patients aged 16-65 years. Brivaracetam dose levels were 0, 5, 20, 50 and 150 mg/day. Individual seizure frequency was modeled with NONMEM (version V) as a Poisson process, expressed as a function of baseline seizures, drug treatment, placebo effect and subject specific-random effects. The Mixture function was used for partitioning the population in two subgroups of patients exhibiting decreased or increased seizure frequency compared to baseline. In the first group, the drug effect was modeled using an Emax dose-response function on top of the placebo effect, whereas the change in seizure frequency in non-improving patients was
dose-independent. In a second step, the dose was replaced by individual posterior estimates of AUCtau in the Emax model.
Results: 73% of the patients were classified as improving on brivaracetam, compared to 57% on placebo. In improving patients, the ED50 was predicted to be 21 mg/day and the maximum seizure reduction from baseline was 70%. The mean seizure reduction in patients improving on placebo was 41%. The mean increase in non-improving patients was 11%. Age, bodyweight, gender, carbamazepine, phenytoin, and the number of concomitant AEDs were found to neither affect the percentage of patients who are likely to improve nor the extent of change in seizure frequency, while country and concomitant levetiracetam influenced the effect size. The concentration-response model did not result in any improvement over the dose-response model.
Conclusions: Emax-modeling of Poisson-transformed seizure count data allowed to demonstrate a dose-response relationship for brivaracetam in 73% of the patients with refractory partial seizures.
A dose of 20 mg daily is expected to decrease the seizure frequency by 50% of the maximum from baseline.
Poster: Applications- CNS
Nathalie Toublanc Retrospective population pharmacokinetic analysis of
seletracetam in epileptic and healthy adults
Marc-Antoine Fabre, Eliane Fuseau(1), Maria-Laura Sargentini-Maier, Nathalie Toublanc(2) (1) EMF consulting, Aix-en-Provence, France ; (2) UCB S.A., Braine-l’Alleud, Belgium Objectives: Characterization of population pharmacokinetics of the novel SV2A ligand
seletracetam (ucb 44212) in healthy and epileptic adult populations to identify covariates that may have a clinically significant influence on its pharmacokinetics (PK) and simulation of the PK profiles in patients with the formulation planned for phase IIb-III studies.
Methods: 233 subjects received single or multiple twice daily doses of instant release formulation of seletracetam in 4 clinical pharmacology studies and 3 phase IIa studies. Seletracetam
concentration-time data were analyzed using NONMEM. Food, age, gender, race, body weight (BW), body surface area, treatment duration, dose and concomitant antiepileptic drug (AED), health status and creatinine clearance were tested as possible covariates. Absorption parameters for once a day (o.d) formulation were derived under fasted and fed conditions from a pilot study. They were added to the final model to simulate the profiles after o.d administration, using demographic covariates of the phase IIa patients with appropriate replications.
Results: 194 subjects were Caucasians, 109 females, 24 elderly (above 65) and 124 epileptic subjects, with median (range) for BW and age of 74.5 (43-133) kg, and 36 (17-86) years.
Seletracetam plasma concentrations were adequately described by a one-compartment model. BW, sex, age and enzyme inducing AEDs were identified as covariates affecting CL/F, resulting in a reduction of inter-individual variability (IIV) from 22% to 15%. The influence of the statistically significant covariates ranged between 16% (inducer AEDs) and 70 % (BW). BW and gender were also identified as covariates on V/Fresulting in a reduction of IIV from 14% to 7%. The population mean of V/F was 0.6 and 0.5 L/kg for males and females. Food also had a significant effect on the absorption rate.Based on simulation of the o.d formulation in a population consisting of replication of phase IIa patients, in both fasted and fed conditions, Cmaxss, Cavss, and Cminss increased in females, by 27% to 43%. The influence of food on the o.d formulation was less than 15% on all parameters.
The effect of inducing AEDs was relevant only on Cminss (decrease ca. 27%)..
Conclusions: Although some covariates were statistically significant, based on simulations of concentration vs. time profiles in patients of an o.d. formulation, the only ones that may have a relevant effect on exposure are BW, sex, and enzyme inducing AEDs.
Poster: Applications- CNS
Maud Vernaz-Gris Pooled PK analysis of a new CNS drug, in healthy subjects.
M. Vernaz-Gris (1), E. Fuseau (1), L. Del Frari (2), V. Brunner (2), P. Hermann (2) (1) EMF Consulting, France ; (2) IRPF, France
Objectives: The objectives of the pooled data analysis were to describe the PK of a new drug developed in the CNS area, to evaluate variability in a population of healthy subjects and to provide a simulation model for optimising study design in patients.
Methods: The population PK analysis was performed on a pooled database, including 121 healthy subjects in 6 phase I studies. Subjects received single or repeated oral dose as a solution (0.075 to 2.5 mg) or as a capsule (1 to 2.25 mg). 2490 plasma concentrations were available. The structural PK model was chosen through individual PK modelling on a subset of subjects. Thereafter, population PK modelling on the complete database was used to estimate the parameters (FOCE interaction estimation method).
Results and Conclusion: A two compartment disposition model with first order elimination and a proportional residual error model were used. The drug often displayed either a large peak or two main peaks of plasma concentrations following single and repeated oral dose administration. The absorption was best described by two different processes separated by a lag time: one fraction of the dose is absorbed into the central compartment by a zero order process; the remaining fraction of the dose is absorbed through a first order process. The structural model includes various covariates, including the effect of the dose, food, formulation and time on apparent volumes of distribution (V2/F, V3/F), apparent inter-compartmental clearance (Q/F), duration of zero order absorption process (D2). The absorption was rapid although D2 was increased with administration of a capsule and with food intake. Inter individual variability (IIV) was evaluated for apparent clearance (CL/F), V2/F, V3/F, Q/F and D2. The magnitude of IIV was estimated between 30 and 47 CV% with exponential error models. Based on these results, simulations will be performed for optimising study design in patients.
Poster: Applications- CNS
Sandra Visser Modeling the time-course of the antipyretic effects and prostaglandin
inhibition in relation the analgesic effects of naproxen: a compound selection
strategy
Sandra Visser(1), Elke Krekels(1), Kristina Ängeby Möller(2), Marie Angesjö(1), Ingemo Sjögren(1) and Odd-Geir Berge(2)
(1)DMPK and (2)Disease Biology, Local Discovery, AstraZeneca R&D Södertälje, SE-151 85 Södertälje, Sweden
Objectives: This study aimed to characterize the pharmacokinetic-pharmacodynamic (PKPD) relationship between plasma concentrations, inhibition of TXB2 and PGE2 synthesis, and the antipyretic and analgesic effects of naproxen in rats in order to investigate whether analgesic measurements could be replaced by endpoints that are more sensitive for compound selection.
Methods: Analgesic effects: naproxen (0, 7.5 and 30 µmol/kg p.o.) was given 1h after an intra-articular injection of carrageenan. Weight bearing was assessed at 5 time points per rat using the PawPrint method and plasma concentrations were measured at 25h.
Antipyretic effects: fever was induced by a 2 g/kg s.c. injection of brewer's yeast 4h before naproxen (0, 7.5, 30 and 90 µmol/kg p.o.). Body temperature was measured continuously using telemetry up to 25h after dosing and plasma concentrations were measured at 25h.
Prostaglandin synthesis: TXB2 and PGE2 synthesis over time was measured ex vivo in separate animals using ELISA. Satellite animals were used to obtain the complete PK profile. The naproxen concentrations were analyzed using LC-ESI-MS/MS. Nonmem V was used for all PKPD modelling procedures.
Results: A two-compartment PK model described the concentrations of naproxen best. Fever was identified as a covariate on CL. Individual parameter estimates were used to predict the
pharmacokinetic profiles to the analgesic and antipyretic effects.
A sigmoidal relationship between the naproxen concentrations and the inhibition of TXB2 and PGE2
synthesis was observed. Population estimates for potency were 5±1 and 13±4 µM, respectively.
Inter-individual variation was around 35% whereas the residual variation was 15%.
A linear model was used to describe the relationship between weight bearing on the affected limb and the concentrations. A tolerance pool model was used to describe the concentration dependent reduction of fever and the observed rebound.
Naproxen was equipotent with respect to the antipyretic and analgesic effects. However, the
variability in measurements was much larger and dose separation less clear for the analgesic effects.
Conclusions: The time-courses of the naproxen concentration, inhibition of TXB2 and PGE2
synthesis, antipyretic and analgesic effects in rats were quantified and correlated. Endpoints such as antipyretic effects or the inhibition of TXB2/PGE2 could serve as alternatives to analgesic
measurements for identifying differences between compounds in lead optimization.
Poster: Applications- CNS
Katarina Vucicevic Population Pharmacokinetic Modelling of Amitriptyline in
Depression Patients
K. Vucicevic(1), B. Miljkovic(1), M. Pokrajac (1), I. Grabnar(2)
(1) Department of Pharmacokinetics, Faculty of Pharmacy, University of Belgrade, Serbia; (2) Faculty of Pharmacy, University of Ljubljana, Slovenia
Objectives: This study aimed to characterize population pharmacokinetics of amitriptyline (AMT), in order to identify possible influential covariates and to assess the linearity of AMT kinetics.
Methods: In total 428 plasma samples were obtained from 28 patients diagnosed with major depression after single AMT dose of 75mg or 150mg, and in steady-state achieved with t.i.d. doses.
Population PK analysis was performed using NONMEM and Visual-NM. Data were fitted with one and two compartment models for both AMT and its active metabolite nortriptyline (NT), while FOCE INTERACTION was used for estimation. The influences of patients’ weight, age, sex, co-therapy with fluvoxamine or lithium, daily dose of AMT on PK parameters were examined.
Results: The analysis showed that kinetics of AMT followed two-compartment model with first-order absorption and lag-time. No effect of dose on pharmacokinetic parameters was observed and the individual parameters estimated from steady state data were comparable to parameters estimated from single dose data. Mean (s.e.) parameter estimates were: CL=64.6 (1.5) L/h, Vc=896 (95) L ,Vp=641 (134) L, Q=114 (21) L/h, Ka=0.73 (0.13) h-1, Tlag=0.634 (0.032) h. Interindividual variability of AMT parameters was low and was best described by exponential error model, while proportional error model the most adequately characterized residual variability in AMT
concentrations. NT kinetics was formation rate limited. Simultaneous fitting of parent drug and metabolite was a further step in modeling process.
Conclusions: The NONMEM analysis showed linear kinetics of AMT with no significant effect of tested covariates on AMT PK parameters.