GNU MCSim is a simulation and statistical inference tool for algebraic or differential equation systems, optimized for performing Monte Carlo analysis.

Discussions with Stuart Beal at UCSF School of Pharmacy, led the team to investigate the use of Markov chain Monte Carlo techniques for PBPK models' calibration.

Additional code written by Ken Revzan allowed the definition and Bayesian calibration of hierarchical (multilevel) statistical models.

Covington T.R., Gentry P.R., et al., 2007, The use of Markov chain Monte Carlo uncertainty analysis to support a Public Health Goal for perchloroethylene, Regulatory Toxicology and Pharmacology, 47:1-18.

Hack E.C., Chiu W.A, et al., 2006, Bayesian population analysis of a harmonized physiologically based pharmacokinetic model of trichloroethylene and its metabolites, Regulatory Toxicology and Pharmacology, 46:63-83.

2008, Computational toxicology of chloroform: reverse dosimetry using Bayesian inference, Markov chain Monte Carlo simulation, and human biomonitoring data, Environmental Health Perspectives, 116:1040-1046.

Marino, D. J., H. Clewell, et al., 2006, Revised assessment of cancer risk to dichloromethane: part I Bayesian PBPK and dose-response modeling in mice, Regulatory Toxicology and Pharmacology 45:44-54.