Population Pharmacokinetics of the Anti-Interferon-Gamma Monoclonal Antibody Emapalumab: An Updated Analysis.

INTRODUCTION: Emapalumab is a fully human monoclonal antibody that targets free and receptor-bound interferon-gamma (IFNγ), neutralizing its biological activity. IFNγ levels differ by orders of magnitude between patients with primary hemophagocytic lymphohistiocytosis (HLH) and macrophage activation syndrome (MAS; a form of secondary HLH) in systemic juvenile idiopathic arthritis (sJIA). Therefore, this study aimed to develop a population pharmacokinetic model for emapalumab across a patient population with a wide range of total (free and emapalumab-bound) IFNγ levels using observations from patients with primary HLH or MAS in sJIA in clinical trials. METHODS: Pharmacokinetic data were pooled (n = 58; 2709 observations) from studies enrolling patients administered emapalumab for primary HLH or MAS in sJIA. Patients with primary HLH were administered emapalumab 1 mg/kg (potentially increasing to 3, 6, and up to 10 mg/kg based on clinical response) every 3 days. Patients with MAS in sJIA were administered emapalumab 6 mg/kg, followed by 3 mg/kg every 3 days until day 15 and twice weekly until day 28. An earlier population PK model was re-parameterized using this data. RESULTS: The final model for emapalumab comprised a 2-compartment model with first-order elimination. Emapalumab clearance remains constant when the total IFNγ concentration (free and emapalumab-bound) is < ~ 10,000 pg/ml but increases proportionally to total IFNγ concentration above this threshold. Emapalumab clearance was estimated to be 0.00218, 0.00308, 0.00623 and 0.01718 l/h at total serum IFNγ concentrations of 103, 104, 105 and 106 pg/ml, respectively, with corresponding terminal half-lives of 19.2, 13.8, 7.18 and 3.12 days for a 1-year-old patient weighing 10 kg with primary HLH. The median terminal half-life for emapalumab in patients with MAS in sJIA was estimated to be 24.0 (range, 6.13-32.4) days, which is similar to observations in healthy volunteers. CONCLUSIONS: Emapalumab pharmacokinetics in patients with primary HLH and MAS in sJIA were described by a two-compartment model with fixed allometric exponents and an age-related effect. Differences in total IFNγ levels between patients with primary HLH and MAS may affect emapalumab pharmacokinetics, suggesting that each indication may require different dosing to rapidly control hyperinflammation. TRIAL REGISTRATION: Clinicaltrials.gov identifiers: NCT01818492, NCT03311854 and NCT02069899.

Patients with a rare condition called hemophagocytic lymphohistiocytosis (HLH) produce excessive amounts of a molecule called interferon-gamma. Excessive interferon-gamma causes extreme (or hyper) inflammation, which can be fatal. A drug called emapalumab can be used to block the action of interferon-gamma. However, we need to understand how the concentration of emapalumab in the blood changes over time to ensure that the correct dose is administered when attempting to control interferon-gamma-driven hyperinflammation in patients with HLH. Because HLH is a rare condition, data from a small number of patients were used to create a mathematical model that predicts emapalumab concentrations in the blood at various times after it is administered. Importantly, the amount of interferon-gamma observed in patients with different types of HLH is highly variable, which can alter how quickly emapalumab is removed from the blood. The higher interferon-gamma levels go above a certain threshold, the faster emapalumab is removed. In particular, interferon-gamma levels generally only exceed this threshold in patients with a familial or genetic form of HLH (primary HLH). Interferon-gamma levels in patients with a type of HLH called macrophage activation syndrome, which can occur in patients with systemic juvenile idiopathic arthritis (sJIA), do not usually cross the threshold associated with faster removal of emapalumab. This means that higher dosing may be required for patients with primary HLH compared with patients who have macrophage activation syndrome in sJIA to expedite control of hyperinflammation because of differences in the rate at which emapalumab is removed from the blood.

Efficacy and safety of emapalumab in macrophage activation syndrome.

OBJECTIVES: Macrophage 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. METHODS: We studied emapalumab, a human anti-IFNγ antibody, administered with background glucocorticoids, in a prospective single-arm trial involving patients who had MAS secondary to sJIA or AOSD and had previously failed high-dose glucocorticoids, with or without anakinra and/or ciclosporin. The study foresaw 4-week treatment that could be shortened or prolonged based on investigator's assessment of response. Patients entered a long-term (12 months) follow-up study. RESULTS: Fourteen patients received emapalumab. All patients completed the trial, entered the long-term follow-up and were alive at the end of 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 a prompt decrease in serum C-X-C motif chemokine ligand 9 (CXCL9) levels. By week 8, MAS remission was achieved in 13 of the 14 patients at a median time of 25 days. Viral infections and positive viral tests were observed. CONCLUSIONS: Neutralisation of IFNγ with emapalumab was efficacious in inducing remission of MAS secondary to sJIA or AOSD in patients who had failed high-dose glucocorticoids. Screening for viral infections should be performed, particularly for cytomegalovirus. TRIAL REGISTRATION NUMBER: NCT02069899 and NCT03311854.

Emapalumab in primary haemophagocytic lymphohistiocytosis and the pathogenic role of interferon gamma: A pharmacometric model-based approach.

AIM: 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. METHODS: 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. RESULTS: High inter- and intra-individual variability in IFNγ production (assessed by total IFNγ levels, range: 102 -106  pg/mL) was observed in pHLH patients. Administering emapalumab reduced IFNγ activity, resulting in significant improvements in clinical and laboratory parameters and a reduced risk of adverse events, mainly related to pHLH. Modelled outcomes supported dose titration starting from 1 mg/kg, with possible increases to 3, 6 or 10 mg/kg based on re-evaluation of parameters of disease activity every 3 days. CONCLUSIONS: The 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.

Therapeutic Drug Monitoring Strategies for Envarsus in De Novo Kidney Transplant Patients Using Population Modelling and Simulations.

INTRODUCTION: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Farnesoid X receptor agonist for the treatment of chronic hepatitis B: A safety study.

The nuclear farnesoid X receptor (FXR) regulates bile acid homeostasis and is a drug target for metabolic liver diseases. FXR also plays an important role in hepatitis B virus (HBV) DNA transcription. In vitro and in mice, FXR agonist treatment leads to inhibition of viral replication and a decline in viral proteins, pregenomic RNA (pgRNA) and HBV DNA levels. We aimed to translate this to a clinical use by primarily evaluating the safety and secondary the anti-viral effect of Vonafexor, a FXR agonist, in chronic hepatitis B (CHB) patients. In total, 73 CHB patients were enrolled in a two-part Phase Ib double-blind, placebo-controlled trial. Patients were randomized to receive oral Vonafexor (100, 200 and 400 mg once daily, or 200 mg twice daily), placebo, or entecavir (Part A, n = 48) or to receive Vonafexor (300 mg once daily or 150 mg twice daily), or placebo, combined with pegylated-interferon-α2a (Part B, n = 25) for 29 days. Patients were followed up for 35 days. Enrolled CHB patients were mostly HBeAg-negative. Vonafexor was overall well tolerated and safe. The most frequent adverse events were moderate gastrointestinal events. Pruritus was more frequent with twice-daily compared with once-daily regimens (56%-67% vs. 16%, respectively, p < 0.05). Vonafexor monotherapy of 400 mg once daily decreased HBsAg concentrations (-0.1 log10  IU/mL, p < 0.05), and Vonafexor/pegylated-IFN-α2a combination therapy decreased HBcrAg and pgRNA. In conclusion, Vonafexor was safe with a decline in HBV markers observed in CHB patients suggesting a potential anti-viral effect the therapeutic potential of which has to be evaluated in larger trials.

Performance of the SAEM and FOCEI Algorithms in the Open-Source, Nonlinear Mixed Effect Modeling Tool nlmixr.

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.

Efficacy of two vitamin E formulations in patients with abetalipoproteinemia and chylomicron retention disease.

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-α-tocopherol) and α-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 α-tocopherol acetate by measuring the plasma concentrations of α-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 α-tocopherol acetate bioavailabilities were extremely low (2.8% and 3.1%, respectively). In contrast, bioavailabilities were higher in patients with CMRD (tocofersolan, 24.7%; α-tocopherol acetate, 11.4%). Plasma concentrations of α-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.

Time-to-Seizure Modeling of Lacosamide Used in Monotherapy in Patients with Newly Diagnosed Epilepsy.

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.

Population pharmacokinetic analysis of certolizumab pegol in patients with Crohn's disease.

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.

A drug and disease model for lixisenatide, a GLP-1 receptor agonist in type 2 diabetes.

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 ß-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 ß-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.

Minutes from the round table held in Paris on July 6, 2007: 'Contribution of modelling in the paediatric drug development'.

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.

Are population pharmacokinetic and/or pharmacodynamic models adequately evaluated? A survey of the literature from 2002 to 2004.

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.

Evaluation of uncertainty parameters estimated by different population PK software and methods.

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 NONMEM, nlme in Splus, 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.

Mixture modeling for the detection of subpopulations in a pharmacokinetic/pharmacodynamic analysis.

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 non-linear 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.

Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide.

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.

Optimal blood sampling time windows for parameter estimation using a population approach: design of a phase II clinical trial.

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.

Pharmacokinetics-pharmacodynamics during drug development--an example from Servier: ivabradine.

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.