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.1940-1956, 2009.
DOI : 10.1111/j.0006-341X.2004.00148.x

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

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

K. Brendel, C. Gaynor, C. Dumont, A. Blesius, and M. Chenel, Using Modelling & Simulation techniques to optimise the design of a paediatric PK/PD study, Population Approach Group in Europe, 2010.

A. Dubois, J. Bertrand, and F. Mentré, Mathematical expressions of the pharmacokinetic and pharmacodynamic models implemented in the PFIM software

J. Guedj, R. Thiébaut, and D. Commenges, Practical Identifiability of HIV Dynamics Models, Bulletin of Mathematical Biology, vol.48, issue.8, pp.2493-2513, 2007.
DOI : 10.1007/s11538-007-9228-7

URL : https://hal.archives-ouvertes.fr/inserm-00204273

I. Gueorguieva, K. Ogungbenro, G. Graham, S. Glatt, and L. Aarons, 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

A. Hooker and P. Vicini, Simultaneous population optimal design for pharmacokineticpharmacodynamic experiments, American Association of Pharmaceutical Scientists Journal, vol.7, issue.4, pp.759-785, 2005.

M. Jamei, S. Marciniak, K. Feng, A. Barnett, G. Tucker et al., Population-based ADME Simulator, Expert Opinion on Drug Metabolism & Toxicology, vol.45, issue.2, pp.211-223, 2009.
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J. T. Rostami-hodjegan, A. , and T. G. , Prediction of the clearance of eleven drugs and associated variability in neonates, infants and children, Clinical Pharmacokinetics, vol.45, issue.9, pp.931-956, 2006.

F. Mentré, A. Mallet, and D. Baccar, Optimal design in random-effects regression models, Biometrika, vol.84, issue.2, pp.429-442, 1997.
DOI : 10.1093/biomet/84.2.429

F. Mentré, J. Nyberg, K. Ogungbenro, S. Leonov, A. Aliev et al., Comparison of results of the different software for design evaluation in population pharmacokinetics and pharmacodynamics, Population Approach Group in Europe, 2011.

T. Mielke and R. Schwabe, Some Considerations on the Fisher Information in Nonlinear Mixed Effects Models, Proceedings of the 9th International Workshop in Model-Oriented Design and Analysis, 2010.
DOI : 10.1007/978-3-7908-2410-0_17

T. Nguyen, C. Bazzoli, and F. Mentré, Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models, Statistics in Medicine, vol.30, issue.11-12, 2011.
DOI : 10.1002/sim.4191

URL : https://hal.archives-ouvertes.fr/inserm-00629594

J. Nyberg, M. Karlsson, and A. Hooker, Simultaneous optimal experimental design on dose and sample times, Journal of Pharmacokinetics and Pharmacodynamics, vol.17, issue.5, pp.125-145, 2009.
DOI : 10.1007/s10928-009-9114-z

J. Nyberg, J. Ringblom, M. Karlsson, and A. Hooker, Different approximations and methods for calculating the FIM and their consequences, Population Optimum Design of Experiments, 2008.

K. Ogungbenro, G. Graham, I. Gueorguieva, and L. Aarons, Incorporating Correlation in Interindividual Variability for the Optimal Design of Multiresponse Pharmacokinetic Experiments, Journal of Biopharmaceutical Statistics, vol.12, issue.2, pp.342-358, 2008.
DOI : 10.1007/s10928-005-0026-2

N. Perdaems, H. Blasco, C. Vinson, M. Chenel, S. Whalley et al., Predictions of Metabolic Drug-Drug Interactions Using Physiologically Based Modelling, Clinical Pharmacokinetics, vol.283, issue.10, pp.239-258, 2010.
DOI : 10.2165/11318130-000000000-00000

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.141-151, 2001.
DOI : 10.1016/S0169-2607(00)00117-6

S. Retout, E. Comets, A. Samson, and F. Mentré, 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.5162-5179, 2007.
DOI : 10.1002/sim.2910

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

S. Retout and F. Mentré, Further Developments of the Fisher Information Matrix in Nonlinear Mixed Effects Models with Evaluation in Population Pharmacokinetics, Journal of Biopharmaceutical Statistics, vol.13, issue.2, pp.209-227, 2003.
DOI : 10.1081/BIP-100101009

A. Samson, M. Lavielle, and F. Mentré, Extension of the SAEM algorithm to left-censored data in non- Figure 3: Influence of covariance on SE (left, ) and RSE (right, ?) of covariance for the single-response model (top), and influence of covariance on criterion for the single-response model (bottom)