R. Weaver, Assessment of drug-drug interactions: concepts and approaches, Xenobiotica, vol.31, issue.1, pp.499-538, 2001.
DOI : 10.3109/03602539709037591

O. Pelkonen, M. Turpeinen, J. Uusitalo, A. Rautio, and H. Raunio, Prediction of Drug Metabolism and Interactions on the Basis of in vitro Investigations, Basic <html_ent glyph="@amp;" ascii="&"/> Clinical Pharmacology <html_ent glyph="@amp;" ascii="&"/> Toxicology, vol.26, issue.3, pp.167-175, 2005.
DOI : 10.1146/annurev.pharmtox.40.1.133

O. Pelkonen, M. Turpeinen, J. Hakkola, P. Honkakoski, J. Hukkanen et al., Inhibition and induction of human cytochrome P450 enzymes: current status, Archives of Toxicology, vol.9, issue.2, pp.667-715, 2008.
DOI : 10.1007/s00204-008-0332-8

F. Bois, P. Gravil, P. Vasseur, and P. Isoard, Optimal pollution control strategies in the presence of interacting toxicants, Water Research, vol.22, issue.11, pp.1443-1447, 1988.
DOI : 10.1016/0043-1354(88)90102-9

J. Barrett, L. Labbé, and M. Pfister, Application and Impact of Population Pharmacokinetics in the Assessment of Antiretroviral Pharmacotherapy, Clinical Pharmacokinetics, vol.5, issue.5
DOI : 10.2165/00003088-200544060-00003

D. Jonker, S. Visser, P. Van-der-graaf, R. Voskuyl, and M. Danhof, Towards a mechanism-based analysis of pharmacodynamic drug?drug interactions in vivo, Pharmacology & Therapeutics, vol.106, issue.1, pp.1-18, 2005.
DOI : 10.1016/j.pharmthera.2004.10.014

P. Bonnabry, J. Sievering, T. Leemann, and P. Dayer, Quantitative Drug Interactions Prediction System (Q-DIPS), Clinical Pharmacokinetics, vol.I, issue.9, pp.631-640, 2001.
DOI : 10.2165/00003088-200140090-00001

N. Isoherranen, H. Hachad, C. Yeung, and R. Levy, Qualitative Analysis of the Role of Metabolites in Inhibitory Drug???Drug Interactions: Literature Evaluation Based on the Metabolism and Transport Drug Interaction Database, Chemical Research in Toxicology, vol.22, issue.2, pp.294-298, 2009.
DOI : 10.1021/tx800491e

H. Refsgaard, B. Jensen, I. Christensen, N. Hagen, and P. Brockhoff, In silico prediction of cytochrome P450 inhibitors, Drug Development Research, vol.21, issue.5, pp.417-429, 2006.
DOI : 10.1002/ddr.20108

D. Schuster, T. Steindl, and T. Langer, Predicting Drug Metabolism Induction In Silico, Current Topics in Medicinal Chemistry, vol.6, issue.15, pp.1627-1640, 2006.
DOI : 10.2174/156802606778108924

A. Vedani, M. Dobler, and M. Lill, The Challenge of Predicting Drug Toxicity in silico, Basic & Clinical Pharmacology & Toxicology, vol.6, issue.3, pp.195-208, 2006.
DOI : 10.1021/jm021080f

S. Ekins, S. Andreyev, A. Ryabov, E. Kirillov, E. Rakhmatulin et al., A COMBINED APPROACH TO DRUG METABOLISM AND TOXICITY ASSESSMENT, Drug Metabolism and Disposition, vol.34, pp.495-503, 2006.
DOI : 10.1124/dmd.105.008458

O. Demin and I. Goryanin, Kinetic Modelling in Systems Biology, 2009.

D. Leahy, Progress in Simulation Modelling for Pharmacokinetics, Current Topics in Medicinal Chemistry, vol.3, issue.11, pp.1257-1268, 2003.
DOI : 10.2174/1568026033451961

N. Parrott, H. Jones, N. Paquereau, and T. Lavé, Application of Full Physiological Models for Pharmaceutical Drug Candidate Selection and Extrapolation of Pharmacokinetics to Man, Basic <html_ent glyph="@amp;" ascii="&"/> Clinical Pharmacology <html_ent glyph="@amp;" ascii="&"/> Toxicology, vol.42, issue.3, pp.193-196, 2005.
DOI : 10.1016/S0378-4274(02)00374-0

H. Barton, W. Chiu, W. Setzer, M. Andersen, A. Bailer et al., Characterizing Uncertainty and Variability in Physiologically Based Pharmacokinetic Models: State of the Science and Needs for Research and Implementation, Toxicological Sciences, vol.99, issue.2, pp.395-402, 2007.
DOI : 10.1093/toxsci/kfm100
URL : https://hal.archives-ouvertes.fr/ineris-00963075

M. Bouvier-d-'yvoire, P. Prieto, B. Blaauboer, F. Bois, A. Boobis et al., Physiologically-based kinetic modelling (PBK modelling): meeting the 25 Physiologically based pharmacokinetic analyses of simple mixtures, Environmental Health Perspectives, vol.102, pp.151-155, 1994.

H. El-masri, R. Thomas, S. Benjamin, and R. Yang, Physiologically based pharmacokinetic/pharmacodynamic modeling of chemical mixtures and possible applications in risk assessment, Toxicology, vol.105, issue.2-3, pp.275-282, 1995.
DOI : 10.1016/0300-483X(95)03222-2

H. El-masri, J. Tessari, and R. Yang, Exploration of an interaction threshold for the joint toxicity of trichloroethylene and 1,1-dichloroethylene: utilization of a PBPK model, Archives of Toxicology, vol.37, issue.2, pp.527-539, 1996.
DOI : 10.1007/s002040050310

X. Yu, G. Johanson, G. Ichihara, E. Shibata, M. Kamijima et al., Physiologically Based Pharmacokinetic Modeling of Metabolic Interactions between n-Hexane and Toluene in Humans., Journal of Occupational Health, vol.40, issue.4, pp.293-301, 1998.
DOI : 10.1539/joh.40.293

J. Simmons, Application of Physiologically Based Pharmacokinetic Modelling to Combination Toxicology, Food and Chemical Toxicology, vol.34, issue.11-12, pp.1067-1073, 1996.
DOI : 10.1016/S0278-6915(97)00076-8

S. Haddad and K. Krishnan, Physiological modeling of toxicokinetic interactions: implications for mixture risk assessment, Environmental Health Perspectives, vol.106, issue.Suppl 6, pp.1377-84, 1998.
DOI : 10.1289/ehp.98106s61377

S. Haddad, R. Tardif, G. Charest-tardif, and K. Krishnan, Physiological Modeling of the Toxicokinetic Interactions in a Quaternary Mixture of Aromatic Hydrocarbons, Toxicology and Applied Pharmacology, vol.161, issue.3, pp.249-257, 1999.
DOI : 10.1006/taap.1999.8803

S. Haddad, M. Beliveau, R. Tardif, and K. Krishnan, A PBPK Modeling-Based Approach to Account for Interactions in the Health Risk Assessment of Chemical Mixtures, Toxicological Sciences, vol.63, issue.1, pp.125-131, 2001.
DOI : 10.1093/toxsci/63.1.125

J. Chien, M. Mohutsky, and S. Wrighton, Physiological Approaches to the Prediction of Drug-Drug Interactions in Study Populations, Current Drug Metabolism, vol.4, issue.5, pp.347-356, 2003.
DOI : 10.2174/1389200033489307

M. Kato, T. Tachibana, K. Ito, and Y. Sugiyama, Evaluation of Methods for Predicting Drug-drug Interactions by Monte Carlo Simulation, Drug Metabolism and Pharmacokinetics, vol.18, issue.2, pp.121-127, 2003.
DOI : 10.2133/dmpk.18.121

A. Rostami-hodjegan and G. Tucker, ???In silico??? simulations to assess the ???in vivo??? consequences of ???in vitro??? metabolic drug???drug interactions, Drug Discovery Today: Technologies, vol.1, issue.4, pp.441-448, 2004.
DOI : 10.1016/j.ddtec.2004.10.002

I. Dobrev, M. Andersen, and R. Yang, Assessing interaction thresholds for trichloroethylene in combination with tetrachloroethylene and 1,1,1-trichloroethane using gas uptake studies and PBPK modeling, Archives of Toxicology, vol.75, issue.3, pp.134-144, 2001.
DOI : 10.1007/s002040100216

S. Lee, Y. Ou, and R. Yang, Comparison of Pharmacokinetic Interactions and Physiologically Based Pharmacokinetic Modeling of PCB 153 and PCB 126 in Nonpregnant Mice, Lactating Mice, and Suckling Pups, Toxicological Sciences, vol.65, issue.1, pp.26-34, 2002.
DOI : 10.1093/toxsci/65.1.26

K. Isaacs, M. Evans, and T. Harris, Visualization-Based Analysis for a Mixed-Inhibition Binary PBPK Model: Determination of Inhibition Mechanism, Journal of Pharmacokinetics and Pharmacodynamics, vol.31, issue.3, pp.215-242, 2004.
DOI : 10.1023/B:JOPA.0000039565.11358.94

J. Campbell and J. Fisher, -Xylene and Ethylbenzene, Inhalation Toxicology, vol.144, issue.3, pp.265-273, 2007.
DOI : 10.1007/s002040050292
URL : https://hal.archives-ouvertes.fr/halshs-01407951

H. Einolf, Comparison of different approaches to predict metabolic drug-drug interactions, Xenobiotica, vol.37, pp.1257-1294, 2007.

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.635-659, 2008.
DOI : 10.1007/s10928-008-9104-6
URL : https://hal.archives-ouvertes.fr/inserm-00383725

J. Buur, R. Baynes, G. Smith, and J. Riviere, A physiologically based pharmacokinetic model linking plasma protein binding interactions with drug disposition, Research in Veterinary Science, vol.86, issue.2, pp.293-301, 2009.
DOI : 10.1016/j.rvsc.2008.07.003

M. Hucka, A. Finney, H. Sauro, H. Bolouri, J. Doyle et al., The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models, Bioinformatics, vol.19, issue.4, pp.524-531, 2003.
DOI : 10.1093/bioinformatics/btg015

D. Nickerson and M. Buist, A physiome standards-based model publication paradigm, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.77, issue.1, pp.1823-1844, 2009.
DOI : 10.1161/01.CIR.99.18.2466

F. Bois, Modeling physiological of metabolic interactions]. Env Risque Sante in press
URL : https://hal.archives-ouvertes.fr/ineris-00970469

F. Bois and D. Maszle, MCSim: a simulation program, Journal of Statistical Software, vol.2, issue.9, 1997.

F. Bois and . Mcsim, GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models, Bioinformatics, vol.25, issue.11, pp.1453-1454, 2009.
DOI : 10.1093/bioinformatics/btp162
URL : https://hal.archives-ouvertes.fr/ineris-00961935

F. Bois, L. Zeise, and T. Tozer, Precision and sensitivity of pharmacokinetic models for cancer risk assessment: Tetrachloroethylene in mice, rats, and humans, Toxicology and Applied Pharmacology, vol.102, issue.2, pp.300-315, 1990.
DOI : 10.1016/0041-008X(90)90029-T

G. Van-der-molen, S. Kooijman, and W. Slob, A Generic Toxicokinetic Model for Persistent Lipophilic Compounds in Humans: An Application to TCDD, Toxicological Sciences, vol.31, issue.1, pp.83-94, 1996.
DOI : 10.1093/toxsci/31.1.83