A global sensitivity analysis approach for morphogenesis models, BMC Systems Biology, vol.316, issue.8, p.85, 2015. ,
DOI : 10.1016/j.yexcr.2010.04.001
GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models, Bioinformatics, vol.24, issue.17, pp.1453-1454, 2009. ,
DOI : 10.1093/bioinformatics/btn338
URL : https://hal.archives-ouvertes.fr/ineris-00961935
An effective screening design for sensitivity analysis of large models, Environmental Modelling & Software, vol.22, issue.10, 2007. ,
DOI : 10.1016/j.envsoft.2006.10.004
Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice, Int. J. Nanomed, vol.10, pp.6277-6292, 2015. ,
Physiologically Based Pharmacokinetic (PBPK) Modeling of Interstrain Variability in Trichloroethylene Metabolism in the Mouse, Environmental Health Perspectives, vol.122, pp.456-463, 2014. ,
DOI : 10.1289/ehp.1307623
Characterizing uncertainty and population variability in the toxicokinetics of trichloroethylene and metabolites in mice, rats, and humans using an updated database, physiologically based pharmacokinetic (PBPK) model, and Bayesian approach, Toxicology and Applied Pharmacology, vol.241, issue.1, pp.36-60, 2009. ,
DOI : 10.1016/j.taap.2009.07.032
Sensitivity analysis of the rice model WARM in Europe: Exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters, Environmental Modelling & Software, vol.25, issue.4, pp.479-488, 2010. ,
DOI : 10.1016/j.envsoft.2009.10.005
Identifiability of PBPK models with applications to dimethylarsinic acid exposure, Journal of Pharmacokinetics and Pharmacodynamics, vol.64, issue.4, pp.591-609, 2015. ,
DOI : 10.1111/1467-9868.00353
Physiological Pharmacokinetic Analysis Using Population Modeling and Informative Prior Distributions, Journal of the American Statistical Association, vol.55, issue.436, 1996. ,
DOI : 10.2307/2533402
, , pp.1400-1412
Bayesian Data Analysis, Boca Raton, 2013. ,
Inference from Iterative Simulation Using Multiple Sequences, Statistical Science, vol.7, issue.4, pp.457-472, 1992. ,
DOI : 10.1214/ss/1177011136
Comparison of Nonmem 7.2 estimation methods and parallel processing efficiency on a target-mediated drug disposition model, Journal of Pharmacokinetics and Pharmacodynamics, vol.98, issue.1, pp.17-35, 2012. ,
DOI : 10.1016/j.cmpb.2009.09.012
Technical Note: Method of Morris effectively reduces the computational demands of global sensitivity analysis for distributed watershed models, Hydrology and Earth System Sciences, vol.17, issue.7, pp.2893-2903, 2013. ,
DOI : 10.5194/hess-17-2893-2013-supplement
SALib: An open-source Python library for Sensitivity Analysis, The Journal of Open Source Software, vol.2, issue.9, 2017. ,
DOI : 10.1016/j.matcom.2009.01.023
Analysis of variance designs for model output, Computer Physics Communications, vol.117, issue.1-2, pp.35-43, 1999. ,
DOI : 10.1016/S0010-4655(98)00154-4
Basic Concepts in Physiologically Based Pharmacokinetic Modeling in Drug Discovery and Development, CPT: Pharmacometrics & Systems Pharmacology, vol.13, issue.8, 2013. ,
DOI : 10.1124/dmd.110.032649
Linking preclinical and clinical whole-body physiologically based pharmacokinetic models with prior distributions in NONMEM, European Journal of Clinical Pharmacology, vol.13, issue.5, pp.485-498, 2007. ,
DOI : 10.1177/074823379701300401
Global Sensitivity Analysis for Systems with Independent and/or Correlated Inputs, The Journal of Physical Chemistry A, vol.114, issue.19, pp.6022-6032, 1021. ,
DOI : 10.1021/jp9096919
Assessing the arsenic-contaminated rice (Oryza sativa) associated children skin lesions, Journal of Hazardous Materials, vol.176, issue.1-3, pp.239-251, 2010. ,
DOI : 10.1016/j.jhazmat.2009.11.019
The application of global sensitivity analysis in the development of a physiologically based pharmacokinetic model for m-xylene and ethanol co-exposure in humans, Frontiers in Pharmacology, vol.6, 2015. ,
DOI : 10.3389/fphar.2015.00135
Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system, Frontiers in Pharmacology, vol.89, issue.31, 2015. ,
DOI : 10.1038/clpt.2010.298
ABSTRACT, Antimicrobial Agents and Chemotherapy, vol.57, issue.4, pp.1763-1771, 2013. ,
DOI : 10.1128/AAC.01567-12
-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation, Journal of Toxicology, vol.57, issue.1, p.760281, 2012. ,
DOI : 10.1016/j.tox.2010.06.007
A Workflow for Global Sensitivity Analysis of PBPK Models, Frontiers in Pharmacology, vol.2, 2011. ,
DOI : 10.3389/fphar.2011.00031
Factorial Sampling Plans for Preliminary Computational Experiments, Technometrics, vol.1, issue.2, pp.161-174, 1991. ,
DOI : 10.2307/1266468
Better estimation of small sobol' sensitivity indices, ACM Transactions on Modeling and Computer Simulation, vol.23, issue.2, 2013. ,
DOI : 10.1145/2457459.2457460
URL : http://arxiv.org/pdf/1204.4763
Identification of Intestinal Loss of a Drug through Physiologically Based Pharmacokinetic??Simulation of Plasma??Concentration-Time Profiles, Clinical Pharmacokinetics, vol.41, issue.4, pp.245-259, 2008. ,
DOI : 10.1016/j.bbagen.2004.08.013
Sensitivity analysis of environmental models: A systematic review with practical workflow, Environmental Modelling & Software, vol.79, pp.214-232, 2016. ,
DOI : 10.1016/j.envsoft.2016.02.008
Modeling Interindividual Variation in Physiological Factors Used in PBPK Models of Humans, Critical Reviews in Toxicology, vol.10, issue.3, pp.469-503, 1080. ,
DOI : 10.1088/0143-0815/10/3/001
Sensitivity: Global Sensitivity Analysis of Model Outputs Available online at: https://cran.r-project, 2017. ,
Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology, Hydrology and Earth System Sciences, vol.11, issue.4, pp.1249-1266, 2007. ,
DOI : 10.5194/hess-11-1249-2007
URL : https://hal.archives-ouvertes.fr/hal-00298778
, Computational Toxicology, vol.I, 2012.
Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability, Environment International, vol.106, pp.105-118, 2017. ,
DOI : 10.1016/j.envint.2017.06.004
URL : https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6116525
Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model, Geoscientific Model Development, vol.8, issue.7, pp.1899-1918, 2015. ,
DOI : 10.5194/gmd-8-1899-2015-supplement
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index, Computer Physics Communications, vol.181, issue.2, pp.259-270, 2010. ,
DOI : 10.1016/j.cpc.2009.09.018
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output, Technometrics, vol.60, issue.1, pp.39-56, 1999. ,
DOI : 10.2307/2371267
Global Sensitivity Analysis of environmental models: Convergence and validation, Environmental Modelling & Software, vol.79, 2016. ,
DOI : 10.1016/j.envsoft.2016.02.005
URL : https://doi.org/10.1016/j.envsoft.2016.02.005
Structural Identifiability of PBPK Models: Practical Consequences for Modeling Strategies and Study Designs, Critical Reviews in Toxicology, vol.48, issue.3, pp.261-272, 1997. ,
DOI : 10.1007/978-1-4684-0374-9
Boa: Bayesian Output Analysis Program (BOA) for MCMC Available online at: https://cran.r-project.org, 2016. ,
Combining the ???bottom up??? and ???top down??? approaches in pharmacokinetic modelling: fitting PBPK models to observed clinical data, British Journal of Clinical Pharmacology, vol.39, issue.Suppl. 2, pp.48-55, 2015. ,
DOI : 10.1007/s10928-012-9280-2
Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods, Journal of Hydrology, vol.522, pp.339-352, 2015. ,
DOI : 10.1016/j.jhydrol.2014.12.056
URL : https://iris.unipa.it/bitstream/10447/150574/1/VAnrolleghemetal_JHydrology2015pdf.pdf
Reduction of a Whole-Body Physiologically Based Pharmacokinetic Model to Stabilise the Bayesian Analysis of Clinical Data, The AAPS Journal, vol.18, issue.1, pp.196-209, 2015. ,
DOI : 10.1208/s12248-015-9840-7
Optimization issues in physiological toxicokinetic modeling: a case study with benzene, Toxicology Letters, vol.69, issue.2, pp.181-196, 1993. ,
DOI : 10.1016/0378-4274(93)90103-5
Structural Identifiability of Physiologically Based Pharmacokinetic Models, Journal of Pharmacokinetics and Pharmacodynamics, vol.148, issue.10, pp.421-439, 2006. ,
DOI : 10.1161/01.RES.65.4.997
Sobol Sensitivity Analysis: A Tool to Guide the Development and Evaluation of Systems Pharmacology Models, CPT: Pharmacometrics & Systems Pharmacology, vol.67, issue.2, pp.69-79, 2015. ,
DOI : 10.1158/0008-5472.CAN-07-0238
Physiologically based modeling of the pharmacokinetics of acetaminophen and its major metabolites in humans using a Bayesian population approach Characterizing the effects of race/ethnicity on acetaminophen pharmacokinetics using physiologically based pharmacokinetic modeling, Eur. J. Drug Metab. Pharmacokinet. Eur. J. Drug Metab. Pharmacokinet, vol.41, issue.42, pp.143-153, 2016. ,