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ObjectivesMacrophage activation syndrome (MAS) is a severe, life-threatening complication of systemic juvenile idiopathic arthritis (sJIA) and adult onset Still’s disease (AOSD). The objective of this study was to confirm the adequacy of an emapalumab dosing regimen in relation to interferon-γ (IFNγ) activity by assessing efficacy and safety. The efficacy outcome was MAS remission by week 8, based on clinical and laboratory criteria.MethodsWe studied emapalumab, a human anti–IFNγ antibody, administered with background glucocorticoids, in a prospective open-label, single-group trial involving patients who had MAS secondary to sJIA or AOSD and had previously failed high-dose glucocorticoids. The study foresaw 4-week treatment that could be shortened or prolonged based on investigator’s assessment of response. Patients could enter a long-term (12 months) follow-up study.ResultsFourteen patients received emapalumab. All patients completed the trial, entered the long-term follow-up and were alive at the end of the follow-up. The investigated dosing regimen, based on an initial loading dose followed by maintenance doses, was appropriate, as shown by rapid neutralisation of IFNγ activity, demonstrated by prompt decrease in serum C-X-C motif chemokine ligand 9 (CXCL9) levels. By week 8, remission of MAS was achieved in 13 of the 14 patients at a median time of 25 days. Viral infections and positive viral tests were observed during the trial and during the long-term follow-up.ConclusionsNeutralisation of IFNγ with emapalumab was efficacious in inducing remission of MAS secondary to sJIA or AOSD in patients who had failed high-dose glucocorticoids.KEY MESSAGESWhat is already known on this topic?Macrophage activation syndrome (MAS) is a severe and potentially life-threatening complication of systemic juvenile idiopathic arthritis and adult-onset Still’s disease. There are no therapeutic options that have been prospectively investigated in MAS. Data in animal models andex vivodata from humans with MAS led to the hypothesis that interferon-γ (IFNγ) has a pathogenic role in MAS.What does this study add?This open-label multicentre trial using emapalumab, an anti–IFNγ antibody, in patients who have failed to respond to high-dose glucocorticoids, demonstrates that IFNγ has a pathogenic role in MAS and that its neutralisation leads to MAS remission.How might this affect research, clinical practice or policy?The results of this study show that neutralisation of IFNγ with emapalumab is a therapeutic option for patients with severe MAS who have failed standard of care with high-dose glucocorticoids.

Primary haemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening, hyperinflammatory syndrome generally occurring in early childhood. The monoclonal antibody emapalumab binds and neutralises interferon γ (IFNγ). This study aimed to determine an emapalumab dosing regimen when traditional dose-finding approaches are not applicable, using pharmacokinetic-pharmacodynamic analyses to further clarify HLH pathogenesis and confirm IFNγ neutralisation as the relevant therapeutic target in pHLH.Initial emapalumab dosing (1 mg/kg) for pHLH patients participating in a pivotal multicentre, open-label, single-arm, phase 2/3 study was based on anticipated IFNγ levels and allometrically scaled pharmacokinetic parameters estimated in healthy volunteers. Emapalumab dosing was adjusted based on estimated IFNγ-mediated clearance and HLH clinical and laboratory criteria. Frequent dosing and emapalumab dose adaptation were used to account for highly variable IFNγ levels and potential target-mediated drug disposition.High inter- and intra-individual variability in IFNγ production (assessed by total IFNγ levels, range: 10The variable and unanticipated extremely high IFNγ concentrations in patients with pHLH are reflected in parameters of disease activity. Improved outcomes can be achieved by neutralising IFNγ using frequent emapalumab dosing and dose adaptation guided by clinical and laboratory observations.

Tacrolimus, the cornerstone of transplantation immunosuppression, is a narrow therapeutic index drug with a low and highly variable bioavailability. Therapeutic drug monitoring based on trough level assessment is mandatory in order to target a personalised exposure and avoid both rejection and toxicity. Population pharmacokinetic (POPPK) models might be a useful tool for improving early attainment of target range by guiding initial doses until steady state is reached and trough levels can be reliably used as surrogate marker of exposure. Here we present the first POPPK for predicting the initial doses of the once-daily prolonged release tacrolimus Envarsus (LCPT) in adult kidney recipients. The model was developed exploiting the data from a recent pharmacokinetic randomised clinical study, in which 69 de novo kidney recipients, 33 of whom treated with LCPT, underwent an intensive blood sampling strategy for tacrolimus including four complete pharmacokinetic profiles. The complex and prolonged absorption of LCPT is well described by the three-phase model that incorporates body weight and CYP3A5 genotype as significant covariates accounting for a great proportion of the inter-patient variability: in particular, CYP3A5*1/*3 expressors had a 66% higher LCPT clearance. We have then generated by simulation a personalised dosing strategy based on the model that could improve the early attainment of therapeutic trough levels by almost doubling the proportion of patients within target range (69.3% compared to 36.1% with the standard body weight-based approach) on post-transplantation day 4 and significantly reduce the proportion of overexposed patients at risk of toxicity. A POPPK model was successfully developed for LCPT in de novo kidney recipients. The model could guide a personalised dosing strategy early after transplantation. For the model to be translated into clinical practice, its beneficial impact of earlier attainment of therapeutic trough levels should be demonstrated on hard clinical outcomes in further studies.

The free and open-source package nlmixr implements pharmacometric nonlinear mixed effects model parameter estimation in R. It provides a uniform language to define pharmacometric models using ordinary differential equations. Performances of the stochastic approximation expectation-maximization (SAEM) and first order-conditional estimation with interaction (FOCEI) algorithms in nlmixr were compared with those found in the industry standards, Monolix and NONMEM, using the following two scenarios: a simple model fit to 500 sparsely sampled data sets and a range of more complex compartmental models with linear and nonlinear clearance fit to data sets with rich sampling. Estimation results obtained from nlmixr for FOCEI and SAEM matched the corresponding output from NONMEM/FOCEI and Monolix/SAEM closely both in terms of parameter estimates and associated standard errors. These results indicate that nlmixr may provide a viable alternative to existing tools for pharmacometric parameter estimation.

International audience; Abetalipoproteinemia (ABL) and chylomicron retention disease (CMRD) are extremely rare recessive forms of hypobetalipoproteinemia characterized by intestinal lipid malabsorption and severe vitamin E deficiency. Vitamin E is often supplemented in the form of fat-soluble vitamin E acetate, but fat malabsorption considerably limits correction of the deficiency. In this crossover study, we administered two different forms of vitamin E, tocofersolan (a water-soluble derivative of RRR-alpha-tocopherol) and alpha-tocopherol acetate, to three patients with ABL and four patients with CMRD. The aims of this study were to evaluate the intestinal absorption characteristics of tocofersolan versus alpha-tocopherol acetate by measuring the plasma concentrations of alpha-tocopherol over time after a single oral load and to compare efficacy by evaluating the ability of each formulation to restore vitamin E storage after 4 months of treatment. In patients with ABL, tocofersolan and alpha-tocopherol acetate bioavailabilities were extremely low (2.8% and 3.1%, respectively). In contrast, bioavailabilities were higher in patients with CMRD (tocofersolan, 24.7%; alpha-tocopherol acetate, 11.4%). Plasma concentrations of alpha-tocopherol at 4 months were not significantly different by formulation type in ABL or CMRD. This study provides new insights about vitamin E status in ABL and CMRD and suggests the potential of different formulations as treatment options.

Introduction: Primary hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening, immune disorder characterized by a hyperinflammatory state in which interferon gamma (IFNγ) is considered a key cytokine. The treatment goal of primary HLH is to stabilize the disease by controlling the associated hyperinflammation to bring patients to allogeneic hematopoietic stem cell transplantation (HSCT), the only curative therapy so far. Current conventional therapy for HLH is based on immunochemotherapies, namely etoposide and glucocorticoids; this treatment, however, is associated with opportunistic infections and severe myelotoxicity. Emapalumab, a fully human, anti-IFNγ monoclonal antibody that neutralizes IFNγ, is the only FDA-approved treatment for primary HLH patients with refractory, recurrent or progressive disease, or intolerance to conventional HLH therapy. In patients with primary HLH, the pharmacokinetics (PK) of emapalumab is highly influenced by body weight, and also by IFNγ production due to target-mediated drug disposition. In the pivotal trial (Locatelli et al NEJM 2020;382:1811-22), treatment of primary HLH patients with emapalumab was associated with a favorable safety and tolerability profile, with no unexpected safety concerns. Objective: To describe prespecified exploratory exposure-safety analyses that were performed on data from patients with primary HLH receiving emapalumab in the pivotal trial. Methods: Data from a multicenter, open-label, pivotal phase 2/3 study (NCT01818492) and its long-term follow-up study (NCT02069899) were included in this analysis. The safety of emapalumab was assessed in 34 patients (27 treatment experienced; 7 treatment naïve) with active primary HLH. Emapalumab was initiated at a dose of 1 mg/kg administered intravenously every 3 days, on a background of dexamethasone 5-10 mg/kg/day. Subsequent doses could be increased to 3, 6 and 10 mg/kg, if required, based on predefined laboratory and clinical response parameters. Treatment duration was up to 8 weeks, with possible shortening to a minimum of 4 weeks, or extension up to time of transplantation if needed. Exploratory graphical analyses were performed to determine the incidence of adverse events (AEs) as a function of the exposure parameters at the time of the AE. The relationship between emapalumab exposure and the incidence of treatment-emergent AEs, serious AEs, severe AEs, and AEs related to infections and infusion-related reactions (IRRs) was explored by logistic regression analyses. Selected parameters of renal (creatine clearance [CRCL]) and liver (total bilirubin [TBIL] and alanine aminotransferase [ALT]) function were explored graphically. Exposure parameters were obtained from the population PK/pharmacodynamic (PD) data file that was used for the population PK and PK/PD analyses. Observed individual concentration-time data were used to derive the individual exposure parameters as a function of time. The analyses considered AEs that emerged after the start of the first infusion until last infusion and prior to initiation of HSCT conditioning. Results: Exploratory graphical exposure-safety analyses did not reveal any apparent relationship between the number of AEs and exposure to emapalumab. Logistic exposure-safety regression analyses using the observed exposure to emapalumab at the time of an AE for patients experiencing an event and the highest observed exposure to emapalumab for those patients experiencing no AE, indicated that the incidence of AEs did not increase as a function of increasing emapalumab concentration. In fact, a statistically significant decrease in the incidence of severe AEs and the incidence of AEs related to IRRs was observed. No multivariate effects were identified in the multivariate regression analyses. No clear trend was observed for TBIL, ALT or CRCL as a function of the duration of emapalumab treatment. The exposure of emapalumab did not appear to influence the levels of TBIL, ALT or CRCL in individual patients during treatment. Conclusion: In this study, the exposure-safety evaluation did not reveal any significant relationships between exposure to emapalumab and observed incidence rates of AEs, serious AEs, infections, or IRRs. These findings support the primary evidence of a favorable benefit-risk profile of emapalumab across the dose range used in this fragile patient population. Disclosures Jordan: Sobi: Consultancy. Locatelli: Amgen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Miltenyi: Speakers Bureau; Medac: Speakers Bureau; Jazz Pharamceutical: Speakers Bureau; Takeda: Speakers Bureau. Jacqmin: Sobi: Consultancy. Laveille: Sobi: Consultancy. Snoeck: Sobi: Consultancy. de Min: Sobi: Consultancy, Ended employment in the past 24 months.

Objectives To quantify the relationship between exposure to lacosamide monotherapy and seizure probability, and to simulate the effect of changing the dose regimen. Methods Structural time-to-event models for dropouts (not because of a lack of efficacy) and seizures were developed using data from 883 adult patients newly diagnosed with epilepsy and experiencing focal or generalized tonic–clonic seizures, participating in a trial (SP0993; ClinicalTrials.gov identifier: NCT01243177) comparing the efficacy of lacosamide and carbamazepine controlled-release monotherapy. Lacosamide dropout and seizure models were used for simulating the effect of changing the initial target dose on seizure freedom. Results Repeated time-to-seizure data were described by a Weibull distribution with parameters estimated separately for the first and subsequent seizures. Daily area under the plasma concentration–time curve was related linearly to the log-hazard. Disease severity, expressed as the number of seizures during the 3 months before the trial (baseline), was a strong predictor of seizure probability: patients with 7–50 seizures at baseline had a 2.6-fold (90% confidence interval 2.01–3.31) higher risk of seizures compared with the reference two to six seizures. Simulations suggested that a 400-mg/day, rather than a 200-mg/day initial target dose for patients with seven or more seizures at baseline could potentially result in an additional 8% of seizure-free patients for 6 months at the last evaluated dose level. Patients receiving lacosamide had a slightly lower dropout risk compared with those receiving carbamazepine. Conclusion Baseline disease severity was the most important predictor of seizure probability. Simulations suggest that an initial target dose >200 mg/day could potentially benefit patients with greater disease severity. Electronic supplementary material The online version of this article (doi:10.1007/s40262-017-0530-8) contains supplementary material, which is available to authorized users.

Introduction: Primary hemophagocytic lymphohistiocytosis (HLH) is a rare syndrome characterized by pathologic immune activation and hyperinflammation. It typically manifests during infancy and is invariably fatal if untreated. Interferon gamma (IFNy) is considered a key contributor to the hyperinflammation of HLH. Thus, neutralization of IFNy could help control the disease until haematopoietic stem cell transplantation, the only curative treatment. Emapalumab, a fully human, anti-IFNy monoclonal antibody, binds to and neutralizes IFNy. Emapalumab is the first and only approved (FDA) treatment for primary HLH. It is indicated for the treatment of adult and pediatric patients with HLH with refractory, recurrent, or progressive disease, or intolerance to conventional HLH therapy. Objective: To develop a population pharmacokinetic (PK) model to describe the PK profile of emapalumab. Methods: PK data were obtained from patients with primary HLH administered emapalumab intravenously during an open-label, single-group, phase 2/3 clinical trial (NCT01818492) and as part of a compassionate use program. A population PK analysis was performed using nonlinear mixed effects modeling (NONMEM® version 7.3.0). Predictive performance of the model was assessed using a visual predictive check. Results: The PK of emapalumab was adequately described by a two-compartment model. All model parameters were estimated with good precision. Central and peripheral volumes of distribution were 0.059 and 0.079 L/kg, respectively. Exploratory graphical analysis showed that (i) IFNy production varied significantly between and within patients as a function of time; (ii) the higher the IFNy production, the faster the elimination of emapalumab due to target-mediated drug disposition; and (iii) the higher the IFNy production, the higher the dose of emapalumab required to reach the neutralizing concentration of IFNy (evidenced by a higher target-mediated clearance of emapalumab). Of the parameters examined, only body weight and total IFNy (free and bound) levels were found to significantly influence the PK of emapalumab. The allometric exponents of body weight for the volume of distribution and clearance were 1 (fixed) and 0.886 (95% confidence interval 0.68, 1.09), respectively. These values support the bodyweight-based dosing of emapalumab (i.e. mg/kg). At values of total IFNy from 103 to 106 pg/mL, the total clearance (linear + target mediated) of emapalumab ranged from 0.0012 to 0.0140 L/h for a bodyweight of 5 kg, with corresponding terminal half-lives from 17.5 to 2.3 days. This wide variance in clearances and half-lives partly explains the emapalumab dose adaptations that are required for treating primary HLH patients. Conclusion: The population PK model reliably predicted serum concentrations of emapalumab in patients with primary HLH. The central and peripheral volumes of distribution were low, clearance was slow, and the terminal half-life long. The expected dynamic of the biology of IFNy was confirmed and included in the population PK model. Simulations using this model supported the proposed dosing scheme of emapalumab in patients with primary HLH. Disclosures Laveille: Sobi: Consultancy. Jacqmin:Sobi: Consultancy. de Min:Sobi: Consultancy.

The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps.

Certolizumab pegol (CZP), an anti–tumor necrosis factor α agent, is an effective therapy for Crohn's disease (CD). A population pharmacokinetic (PK) analysis of subcutaneously administered CZP was performed using data from 2157 CD patients from 9 separate studies. The aim was to determine which covariates influence the disposition of CZP. The final CZP population PK model consisted of a baseline, first‐order absorption, and 1‐compartment disposition. CZP antibodies were treated as a structural model covariate and caused apparent clearance (CL/F) to increase from 0.685 to 2.74 L/day. Body surface area (BSA) influenced both CL/F and apparent volume of distribution (V/F) in a linear fashion; both parameters increased by more than 53% and 49%, respectively, across the range of BSA measurements in the data. Albumin influenced CZP CL/F in a nonlinear fashion; CL/F decreased from 1.05 to 0.613 L/day with increasing albumin concentrations in antibody‐negative patients. C‐reactive protein (CRP) had a borderline influence and CL/F increased by more than 20% across the range of CRP measurements in the data set. Race had a minor influence on V/F. The determined covariates' impact on CZP disposition may be of clinical utility in CZP therapy of CD patients when the PK/pharmacodynamic relationship becomes available.

Incretin hormone analogs such as glucagon-like peptide-1 (GLP-1) receptor agonists have emerged as promising new options for the treatment of type 2 diabetes mellitus (T2DM), targeting several of its pathophysiological traits, including reduced insulin sensitivity, inadequate insulin secretion, and loss of β-cell mass (BCM). This article describes the semi-mechanistic modeling of lixisenatide dose-response over time using fasting plasma glucose (FPG), fasting serum insulin (FSI) and glycated hemoglobin (HbA1c) data from two Phase II and four Phase III clinical trials, for a total of 2470 T2DM patients. Previously published models for FPG, FSI, and BCM as well as HbA1c were adapted and expanded to describe the available data. The model incorporated aspects describing disease progression, standard-of-care, FPG-dependent and -independent HbA1c synthesis, and covariate effects of body size, race, and sex. The final model described lixisenatide effects on β-cell responsiveness, insulin sensitivity and FPG-independent HbA1c synthesis, was able to describe the observed FPG, FSI, and HbA1c data accurately, and was successful in predicting data from an unseen Phase III clinical study.

A symposium called “Contribution of modelling in the paediatric drug development” was organized at Paris on July 5-6, 2007 under the auspices of INSERM. The following issues were highlighted and discussed by the participants at the end of the meeting during a round table: • What is the place of modelling at a preclinical stage in the paediatric development? • What is the place of modelling at a clinical stage in the paediatric development? • What are the requirements for an evaluation based on modelling? • What are the recommendations and guidelines need to be established to facilitate the use of modelling techniques in paediatrics? This paper summarizes the discussion around these four questions.

International audience; PURPOSE: The aim of this study is to define and illustrate metrics for the external evaluation of a population model. MATERIALS AND METHODS: In this paper, several types of metrics are defined: based on observations (standardized prediction error with or without simulation and normalized prediction distribution error); based on hyperparameters (with or without simulation); based on the likelihood of the model. All the metrics described above are applied to evaluate a model built from two phase II studies of gliclazide. A real phase I dataset and two datasets simulated with the real dataset design are used as external validation datasets to show and compare how metrics are able to detect and explain potential adequacies or inadequacies of the model. RESULTS: Normalized prediction errors calculated without any approximation, and metrics based on hyperparameters or on objective function have good theoretical properties to be used for external model evaluation and showed satisfactory behaviour in the simulation study. CONCLUSIONS: For external model evaluation, prediction distribution errors are recommended when the aim is to use the model to simulate data. Metrics through hyperparameters should be preferred when the aim is to compare two populations and metrics based on the objective function are useful during the model building process.

The objective of this paper is to determine optimal blood sampling time windows for the estimation of pharmacokinetic (PK) parameters by a population approach within the clinical constraints. A population PK model was developed to describe a reference phase II PK dataset. Using this model and the parameter estimates, D-optimal sampling times were determined by optimising the determinant of the population Fisher information matrix (PFIM) using PFIM_ _M 1.2 and the modified Fedorov exchange algorithm. Optimal sampling time windows were then determined by allowing the D-optimal windows design to result in a specified level of efficiency when compared to the fixed-times D-optimal design. The best results were obtained when K(a) and IIV on K(a) were fixed. Windows were determined using this approach assuming 90% level of efficiency and uniform sample distribution. Four optimal sampling time windows were determined as follow: at trough between 22 h and new drug administration; between 2 and 4 h after dose for all patients; and for 1/3 of the patients only 2 sampling time windows between 4 and 10 h after dose, equal to [4 h-5 h 05] and [9 h 10-10 h]. This work permitted the determination of an optimal design, with suitable sampling time windows which was then evaluated by simulations. The sampling time windows will be used to define the sampling schedule in a prospective phase II study.

Aims To study the relationship between the pharmacokinetics (PK) of gliclazide and its long-term pharmacodynamic (PD) effect in a large population of Type 2 diabetic patients and to identify factors predicting intersubject variability. Methods A PKPD database of 634 Type 2 diabetic patients with a total of 5258 fasting plasma glucose (FPG) samples was built up from the data collected during the clinical development of a modified release formulation of gliclazide (gliclazide MR). The PKPD analysis used a nonlinear mixed effect modelling approach. A mixture model was used to identify patients with a FPG response to treatment. In patients identified as responders, the decrease in FPG was related to gliclazide exposure (AUC) by an Emax relationship. An effect compartment was used to describe the link between PK and PD. A linear disease-progression model was used to assess the glycaemic deterioration observable over several months of treatment. Simulations were performed to evaluate the predictive performance of the PKPD model and to illustrate the time course of the antidiabetic effect of gliclazide MR. Results Disease state was found to be the main explanatory factor for intersubject variability in response to gliclazide. The percentage of responders to gliclazide, used as monotherapy, increased inversely to the number of classes of antidiabetic agents received prior to entry in the studies. In responders, the initial dose (30 mg) of the gliclazide MR dosing regimen induced half of the maximum hypoglycaemic effect. The equilibration half-life between the PK and PD steady states was 3 weeks (intersubject variability of 84%). The rate of disease progression was 0.84 mmol l−1 year−1 (intersubject variability 143%). The PKPD model adequately predicted the FPG profiles of 234 patients who received the current formulation of gliclazide. Simulation of a 1-year parallel dose ranging clinical trial illustrated the influence of dose, time and type of previous antidiabetic treatment on the percentage of patients with clinically significant improvement of blood glucose control. Conclusions This population PKPD analysis has characterized the relationship between the exposure to gliclazide and its long-term hypoglycaemic effect, and has established that the intersubject variability in response is mostly related to disease state. These results underline the clinical interest of quickly increasing the dose of gliclazide MR according to the response to treatment in order to achieve effective blood glucose control.

Ivabradine is a novel bradycardic agent that has been developed for the prevention of angina. Ivabradine has an active metabolite S-18982. The aim of this study is to develop a pharmacokinetic simulation model. Pharmacokinetic data from two studies were pooled and included data from a total of 66 healthy male volunteers. The data were collected following single dose intravenous and multiple dose oral administration of ivabradine. The multiple dose regimens were administered every 12 h and there were seven active dosing levels. The modelling was performed using the NONMEM software. The model was assessed in terms of its ability to describe the original data set used in its construction and also data arising from a different clinical pharmacology study involving 12 additional subjects. The pharmacokinetics of ivabradine and S-18982 were best described by two linked two compartment intravenous bolus and first-order input, with first-pass loss, and first-order output model. When the model was used for simulation it produced an adequate description of both the original data and data arising from a different clinical pharmacology study.

The standard two-stage analysis of separate preclinical pharmacokinetic (PK) and toxicokinetic (TK) studies may lead to good information on the bioavailability in the rat at a low (pharmacologic) dose but only an idea on the dose/exposure relationship, on gender, and on time effect. In view of these drawbacks, we decided therefore to explore the usefulness of the implementation of a meta-analysis in preclinical studies in a given species (the rat in this case) taking as an example S 20342, an investigational new drug with potential antipsychotic properties. A nonlinear mixed-effect PK model was built from all intravenous (IV) and oral (PO) data collected until the completion of the 4-week toxicity study. The database included data from 201 Wistar rats (161 males and 40 females). Forty animals received the drug IV and 161 PO. The treatment duration ranged from 1 day to 4 weeks. IV doses were 3, 5, and 20 mg/kg, and 11 different oral doses were tested in the range of 5 to 200 mg/kg. Three different salts were administered PO: hydrochloride, sulfate, and mesylate. The modeling was performed with NONMEM IV. The best pharmacokinetic model was a two-compartment model with simultaneous first-order and zero-order absorption. The combination of these two input functions allowed the model to fit the peak plasma concentrations observed in the first hour (first order), especially after oral administration of low doses, and to take into account the prolonged absorption phase when the dose increased (zero order). A significant gender effect was found on CL. In addition, significant positive correlations were found between weight and CL, weight and Vc, and dose and the dose fraction after a zero-order absorption. No covariate significantly influenced the other parameters. In conclusion, the meta-analysis of preclinical data allowed for an objective assessment of statistically significant effects throughout the model-building process, leading to a better knowledge (and thus a better understanding) of preclinical PK in the rat. Moreover, the model obtained could be used to interpret further preclinical specific studies involving a sparse sampling design (e.g., further TK studies and PK/PD studies). Although this meta-analysis is more complicated than the noncompartmental approach and requires a case-by-case effort, it could be very useful to integrate this approach in the preclinical development process.

Objective Ivabradine (S-16257) is a new bradycardic agent with a direct effect on the sinus node. Its N-dealkylated metabolite, S-18982, has shown a bradycardic activity in animals. The aim of this trial was to study the correlation between drug bradycardic activity and plasma levels of the parent compound and its metabolite in healthy volunteers. Methods Eighteen healthy volunteers participated in three successive study periods: an oral double-blind period with two parallel groups of doses (10 or 20 mg, single and repeated); a 10 mg intravenous bolus open period; and a final control period. The effects of ivabradine on heart rate were studied at rest and during bicycle exercise tests (at 85% of maximum workload) during 24-hour postdosing, and ivabradine and S-18982 plasma levels were determined simultaneously. Results The maximal reductions of exercise heart rate were 11% ± 4% (10 mg) and 18% ± 6% (20 mg) after single oral doses (p < 0.05) and 18% ± 4% (10 mg) and 27% ± 6% (20 mg) after repeated doses (p < 0.01). Maximum heart rate reduction after the intravenous bolus was 19% ± 4%. After oral administrations an indirect relationship between the bradycardic effect and the plasma concentrations of the two compounds was found. A pharmacokinetic/pharmacodynamic population analysis done with the NONMEM computer program showed that S-18982 contributes in part to the overall activity of ivabradine: modeling suggested that the metabolite is responsible for the initial bradycardic effect, whereas the parent compound is responsible for the duration of action. Conclusion This study shows that ivabradine exerts a dose-dependent bradycardic effect and that its N-dealkylated metabolite contributes to this bradycardic effect. Clinical Pharmacology & Therapeutics (1998) 64, 192–203; doi

AIMS: A descriptive survey of published population pharmacokinetic and/or pharmacodynamic (PK/PD) analyses from 2002 to 2004 was conducted and an evaluation made of how model building was performed and reported. METHODS: We selected 324 articles in Pubmed using defined keywords. A data abstraction form (DAF) was then built comprising two parts: general characteristics including article identification, context of the analysis, description of clinical studies from which the data arose, and model building, including description of the processes of modelling. The papers were examined by two readers, who extracted the relevant information and transmitted it directly to a MySQL database, from which descriptive statistical analysis was performed. RESULTS: Most published papers concerned patients with severe pathology and therapeutic classes suffering from narrow therapeutic index and/or high PK/PD variability. Most of the time, modelling was performed for descriptive purposes, with rich rather than sparse data and using NONMEM software. PK and PD models were rarely complex (one or two compartments for PK; E(max) for PD models). Covariate testing was frequently performed and essentially based on the likelihood ratio test. Based on a minimal list of items that should systematically be found in a population PK-PD analysis, it was found that only 39% and 8.5% of the PK and PD analyses, respectively, published from 2002 to 2004 provided sufficient detail to support the model-building methodology. CONCLUSIONS: This survey allowed an efficient description of recent published population analyses, but also revealed deficiencies in reporting information on model building.

Model evaluation is an important issue in population analyses. We aimed to perform a systematic review of all population pharmacokinetic and/or pharmacodynamic analyses published between 2002 and 2004 to survey the current methods used to evaluate models and to assess whether those models were adequately evaluated. We selected 324 articles in MEDLINE using defined key words and built a data abstraction form composed of a checklist of items to extract the relevant information from these articles with respect to model evaluation. In the data abstraction form, evaluation methods were divided into three subsections: basic internal methods (goodness-of-fit [GOF] plots, uncertainty in parameter estimates and model sensitivity), advanced internal methods (data splitting, resampling techniques and Monte Carlo simulations) and external model evaluation. Basic internal evaluation was the most frequently described method in the reports: 65% of the models involved GOF evaluation. Standard errors or confidence intervals were reported for 50% of fixed effects but only for 22% of random effects. Advanced internal methods were used in approximately 25% of models: data splitting was more often used than bootstrap and cross-validation; simulations were used in 6% of models to evaluate models by a visual predictive check or by a posterior predictive check. External evaluation was performed in only 7% of models. Using the subjective synthesis of model evaluation for each article, we judged the models to be adequately evaluated in 28% of pharmacokinetic models and 26% of pharmacodynamic models. Basic internal evaluation was preferred to more advanced methods, probably because the former is performed easily with most software. We also noticed that when the aim of modelling was predictive, advanced internal methods or more stringent methods were more often used.

The uncertainty associated with parameter estimations is essential for population model building, evaluation, and simulation. Summarized by the standard error (SE), its estimation is sometimes questionable. Herein, we evaluate SEs provided by different non linear mixed-effect estimation methods associated with their estimation performances. Methods based on maximum likelihood (FO and FOCE in NONMEMTM, nlme in SplusTM, and SAEM in MONOLIX) and Bayesian theory (WinBUGS) were evaluated on datasets obtained by simulations of a one-compartment PK model using 9 different designs. Bootstrap techniques were applied to FO, FOCE, and nlme. We compared SE estimations, parameter estimations, convergence, and computation time. Regarding SE estimations, methods provided concordant results for fixed effects. On random effects, SAEM and WinBUGS, tended respectively to under or over-estimate them. With sparse data, FO provided biased estimations of SE and discordant results between bootstrapped and original datasets. Regarding parameter estimations, FO showed a systematic bias on fixed and random effects. WinBUGS provided biased estimations, but only with sparse data. SAEM and WinBUGS converged systematically while FOCE failed in half of the cases. Applying bootstrap with FOCE yielded CPU times too large for routine application and bootstrap with nlme resulted in frequent crashes. In conclusion, FO provided bias on parameter estimations and on SE estimations of random effects. Methods like FOCE provided unbiased results but convergence was the biggest issue. Bootstrap did not improve SEs for FOCE methods, except when confidence interval of random effects is needed. WinBUGS gave consistent results but required long computation times. SAEM was in-between, showing few under-estimated SE but unbiased parameter estimations.

To be able to estimate accurately parameters entering a non-linear mixed effects model taking into account that one or more subpopulations of patients can exist rather than assuming that the entire population is best described by unimodal distributions for the random effects, we proposed a methodology based on the likelihood approximation using the Gauss–Hermite quadrature. The idea is to combine the estimation of the model parameters and the detection of homogeneous subgroups of patients in a given population using a Gaussian mixture for the distribution of the random effects. As the accuracy of the likelihood approximation is likely to govern the quality of the estimation of the different parameters entering the nonlinear mixed effects model, we based this approximation on the use of an adjustable Gauss– Hermite quadrature. Moreover, to complete this methodology, we propose a strategy allowing the detection and explanation of heterogeneity based on the Kullback–Leibler test, which was used to estimate the number of components in the Gaussian mixture. In order to evaluate the capability of the method to take into account heterogeneity, this strategy was performed in a PK/PD analysis using the database and the structural model selected in a previous analysis. In this analysis, non-responders were found out using NONMEM [Beal and Sheiner. NONMEM Users Guides. NONMEM Project Group, University of California, San Francisio, 1992] in a population of diabetic patients treated with a once-a-day new formulation of an antidiabetic drug. The authors looked for a subpopulation of patients for whom the therapeutic effect would vanish. In this paper, we looked for subpopulations of patients exhibiting specificities with respect to different parameters entering the description of the effect. The results obtained with our approach are compared in terms of parameter estimation and heterogeneity detection to those obtained in the previous analysis.

A short introduction to the principles of pharmacokinetic-pharmacodynamic (PK-PD) modelling and population approaches is provided in this article. The importance of implementing these techniques in the drug development process is illustrated by an example from experience at the Servier International Research Institute. This example demonstrates how the use of PK-PD modelling can rationalise the development process and save valuable time. Population approaches significantly contribute to the integration of PK-PD modelling into the different drug development phases by expanding the possibilities of application.