F. Bouzom and W. B. , Pharmacokinetic predictions in children by using the physiologically based pharmacokinetic modelling, Fundamental & Clinical Pharmacology, vol.42, issue.6, pp.579-87, 2008.
DOI : 10.1111/j.1472-8206.2008.00648.x

F. Mentré, C. Dubruc, and J. Thénot, Population pharmacokinetic analysis and optimization of the experimental design for mizolastine solution in children, Journal of Pharmacokinetics and Pharmacodynamics, vol.28, issue.3, pp.299-319, 2001.
DOI : 10.1023/A:1011583210549

M. Tod, V. Jullien, and G. Pons, Facilitation of Drug Evaluation in Children by??Population Methods and Modelling???, Clinical Pharmacokinetics, vol.116, issue.4, pp.231-274, 2008.
DOI : 10.2165/00003088-200847040-00002

F. Mentré, A. Mallet, and D. Baccar, Optimal design in random-effects regression models, Biometrika, vol.84, issue.2, pp.429-471, 1997.
DOI : 10.1093/biomet/84.2.429

C. Bazzoli, S. Retout, and F. Mentré, Fisher information matrix for nonlinear mixed effects multiple response models: Evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model, Statistics in Medicine, vol.60, issue.14, pp.1940-56, 2009.
DOI : 10.1111/j.0006-341X.2004.00148.x

URL : https://hal.archives-ouvertes.fr/inserm-00371363

S. Retout, F. Mentré, and R. Bruno, Fisher information matrix for non-linear mixed-effects models: evaluation and application for optimal design of enoxaparin population pharmacokinetics, Statistics in Medicine, vol.26, issue.6, pp.2623-2662, 2002.
DOI : 10.1002/sim.1041

I. Gueorguieva, K. Ogungbenro, and G. Graham, A program for individual and population optimal design for univariate and multivariate response pharmacokinetic???pharmacodynamic models, Computer Methods and Programs in Biomedicine, vol.86, issue.1, pp.51-61, 2007.
DOI : 10.1016/j.cmpb.2007.01.004

F. Mentré, Y. Burtin, and Y. Merlé, Sparse-Sampling Optimal Designs in Pharmacokinetics and Toxicokinetics, Therapeutic Innovation & Regulatory Science, vol.29, issue.3, pp.997-1019, 1995.
DOI : 10.1177/009286159502900321

S. Retout, S. Duffull, and F. Mentré, Development and implementation of the population Fisher information matrix for the evaluation of population pharmacokinetic designs, Computer Methods and Programs in Biomedicine, vol.65, issue.2, pp.141-51, 2001.
DOI : 10.1016/S0169-2607(00)00117-6

C. Bazzoli, S. Retout, and F. Mentré, Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0, Computer Methods and Programs in Biomedicine, vol.98, issue.1, pp.55-65, 2010.
DOI : 10.1016/j.cmpb.2009.09.012

URL : https://hal.archives-ouvertes.fr/inserm-00431457

M. Jamei, S. Marciniak, and K. Feng, Population-based ADME Simulator, Expert Opinion on Drug Metabolism & Toxicology, vol.45, issue.2, pp.211-234, 2009.
DOI : 10.1080/00498250701620726

T. Johnson, A. Rostami-hodjegan, and T. G. , Prediction of the Clearance of Eleven Drugs and Associated Variability in Neonates, Infants and Children, Clinical Pharmacokinetics, vol.45, issue.1, pp.931-56, 2006.
DOI : 10.2165/00003088-200645090-00005

T. Johnson and A. Rostami-hodjegan, Resurgence in the use of physiologically based pharmacokinetic models in pediatric clinical pharmacology: parallel shift in incorporating the knowledge of biological elements and increased applicability to drug development and clinical practice, Pediatric Anesthesia, vol.49, issue.3, pp.291-301, 2011.
DOI : 10.1111/j.1460-9592.2010.03323.x

A. Rostami-hodjega and G. Tucker, Simulation and prediction of in vivo drug metabolism in human populations from in vitro data, Nature Reviews Drug Discovery, vol.36, issue.2, pp.140-188, 2007.
DOI : 10.1038/nrd2173

M. Rowland, C. Peck, and G. Tucker, Physiologically-Based Pharmacokinetics in Drug Development and Regulatory Science, Annual Review of Pharmacology and Toxicology, vol.51, issue.1, pp.45-73, 2011.
DOI : 10.1146/annurev-pharmtox-010510-100540

P. Zhao, L. Zhang, and J. Grillo, Applications of Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation During Regulatory Review, Clinical Pharmacology & Therapeutics, vol.41, issue.2, pp.259-67, 2011.
DOI : 10.1046/j.0306-5251.2001.00031.x

S. Huang and R. M. , The Role of Physiologically Based Pharmacokinetic Modeling in Regulatory Review, Clinical Pharmacology & Therapeutics, vol.9, issue.3, pp.542-591, 2012.
DOI : 10.1038/clpt.2011.320

M. Rowland, L. Balant, and C. Peck, Physiologically-Based Pharmacokinetics in Drug Development and Regulatory Science, Annual Review of Pharmacology and Toxicology, vol.51, issue.1, pp.6-12, 2002.
DOI : 10.1146/annurev-pharmtox-010510-100540

S. Bjorkman, Prediction of drug disposition in infants and children by means of physiologically based pharmacokinetic (PBPK) modelling: theophylline and midazolam as model drugs, British Journal of Clinical Pharmacology, vol.37, issue.6, pp.691-704, 2006.
DOI : 10.1007/BF01065191

A. Edginton, W. Schmitt, and S. Willmann, Development and Evaluation of a Generic Physiologically Based Pharmacokinetic Model for Children, Clinical Pharmacokinetics, vol.42, issue.1, pp.1013-1047, 2006.
DOI : 10.2165/00003088-200645100-00005

F. Yang, X. Tong, and D. Mccarver, Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model, Journal of Pharmacokinetics and Pharmacodynamics, vol.4, issue.4, pp.485-518, 2006.
DOI : 10.1007/s10928-006-9018-0

R. Alemzadeh, R. Hoffmann, and M. Dasgupta, Development of Optimal Kids Insulin Dosing System (KIDS) Formulas for Young Children with Type 1 Diabetes Mellitus (T1DM)., Diabetes Technol Ther, vol.14, pp.418-440, 2012.
DOI : 10.1210/endo-meetings.2010.PART3.P11.P3-512

M. Bouillon-pichault, V. Jullien, and C. Bazzoli, Pharmacokinetic design optimization in children and estimation of maturation parameters: example of cytochrome P450 3A4, Journal of Pharmacokinetics and Pharmacodynamics, vol.67, issue.1, pp.25-40, 2011.
DOI : 10.1007/s10928-010-9173-1

K. Ogungbenro, I. Matthews, and M. Looby, Population pharmacokinetics and optimal design of paediatric studies for famciclovir, British Journal of Clinical Pharmacology, vol.48, issue.4, pp.546-60, 2009.
DOI : 10.1111/j.1365-2125.2009.03479.x

N. Perdaems, H. Blasco, and C. Vinson, Predictions of Metabolic Drug-Drug Interactions Using Physiologically Based Modelling, Clinical Pharmacokinetics, vol.283, issue.10, pp.239-58, 2010.
DOI : 10.2165/11318130-000000000-00000

M. Chenel, F. Bouzom, L. Aarons, and K. Ogungbenro, Drug???drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes, Journal of Pharmacokinetics and Pharmacodynamics, vol.28, issue.3, pp.635-59, 2008.
DOI : 10.1007/s10928-008-9104-6

URL : https://hal.archives-ouvertes.fr/inserm-00383725

J. Ahn, M. Karlsson, and A. Dunne, Likelihood based approaches to handling data below the quantification limit using NONMEM VI, Journal of Pharmacokinetics and Pharmacodynamics, vol.34, issue.4, pp.401-422, 2008.
DOI : 10.1007/s10928-008-9094-4

A. Samson, M. Lavielle, and F. Mentré, Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model, Computational Statistics & Data Analysis, vol.51, issue.3, pp.1562-74, 2006.
DOI : 10.1016/j.csda.2006.05.007

URL : https://hal.archives-ouvertes.fr/inserm-00182360

J. Rochon, Application of GEE procedures for sample size calculations in repeated measures experiments, Statistics in Medicine, vol.17, issue.14, pp.1643-58, 1998.
DOI : 10.1002/(SICI)1097-0258(19980730)17:14<1643::AID-SIM869>3.0.CO;2-3

K. Ogungbenro, L. Aarons, and G. Graham, Sample Size Calculations Based on Generalized Estimating Equations for Population Pharmacokinetic Experiments, Journal of Biopharmaceutical Statistics, vol.16, issue.2, pp.135-50, 2006.
DOI : 10.1002/sim.4780111406

T. Rodgers, D. Leahy, and R. M. , Physiologically Based Pharmacokinetic Modeling 1: Predicting the Tissue Distribution of Moderate-to-Strong Bases, Journal of Pharmaceutical Sciences, vol.94, issue.6, pp.1259-76, 2005.
DOI : 10.1002/jps.20322

T. Johnson and A. Rostami-hodjegan, Resurgence in the use of physiologically based pharmacokinetic models in pediatric clinical pharmacology: parallel shift in incorporating the knowledge of biological elements and increased applicability to drug development and clinical practice, Pediatric Anesthesia, vol.49, issue.3, pp.291-301, 2011.
DOI : 10.1111/j.1460-9592.2010.03323.x

S. Beal and L. Sheiner, NONMEM users guide University of California, 1992.

Y. Wang, Derivation of various NONMEM estimation methods, Journal of Pharmacokinetics and Pharmacodynamics, vol.80, issue.5, pp.575-93, 2007.
DOI : 10.1007/s10928-007-9060-6

J. Bertrand, E. Comets, and F. Mentré, Comparison of Model-Based Tests and Selection Strategies to Detect Genetic Polymorphisms Influencing Pharmacokinetic Parameters, Journal of Biopharmaceutical Statistics, vol.5, issue.6, pp.1084-1102, 2008.
DOI : 10.1111/j.1525-1438.2006.00593.x

URL : https://hal.archives-ouvertes.fr/inserm-00339183

K. Brendel, E. Comets, and C. Laffont, Metrics for External Model Evaluation with an Application to the Population Pharmacokinetics of Gliclazide, Pharmaceutical Research, vol.91, issue.9, pp.2036-2085, 2006.
DOI : 10.1007/s11095-006-9067-5

URL : https://hal.archives-ouvertes.fr/inserm-00189557

S. Retout, E. Comets, and A. Samson, Design in nonlinear mixed effects models: Optimization using the Fedorov???Wynn algorithm and power of the Wald test for binary covariates, Statistics in Medicine, vol.39, issue.28, pp.5162-79, 2007.
DOI : 10.1002/sim.2910

URL : https://hal.archives-ouvertes.fr/hal-00263513

C. Dumont, M. Chenel, and F. Mentré, Design evaluation in nonlinear mixed effect models: influence of covariance between random effects [abstract no. 2158], Population Approach Group in EuropePAGE, vol.7, issue.10, pp.page-meeting, 2011.

C. Dumont, M. Chenel, and F. Mentré, Influence of covariance between random effects in design for nonlinear mixed effect models with an illustration in paediatric pharmacokinetics, J Biopharm Stat