Estimation of Lead Elimination Rates for Liver and Kidney Using a Physiologically- Based Pharmacokinetic Model for Improved Human Risk Analysis

ABSTRACT ABSTRACT This research has studied the uncertainties in a physiologically-based pharmacokinetic (PBPK) model that describes uptake, accumulation, and elimination of Pb in the human body and to estimate the model's parameters. The model's application required probabilistic Pb exposure to humans which was accomplished by determining Pb content in various food items and food consumption patterns in a rural site near Kanpur, India. The important model parameters that varied were excretion constants, KELI and KEKI (1/d), for elimination of Pb from liver and kidney. For estimating these parameters, the PBPK model's equations were reorganized by incorporating steady state conditions. Measured blood and urine Pb levels were used for estimating these parameters. A significant variability was observed in estimated parameters, KELI (0.112 to 0.248/day) and KEKI (0.390 to 0.794/day). This research suggested that excretion parameters must be taken in a stochastic sense for obtaining proper estimates of human risk. In addition to KELI and KEKI, variability (food quantity, Pb concentration in food items, and bodyweight) was considered for estimating blood Pb concentrations through PBPK modeling and Monte-Carlo simulation. It was demonstrated that by not considering the variability, health risk was underestimated (compare 8.98 × 10−5 [no variability] to 9.34 × 10−3 [with variability]). Key Words: leadexcretion constantsPBPK modelliverkidneyrisk analysis. ACKNOWLEDGMENTS The authors thank Dr. O.P. Misra, Medical Officer, IIT Kanpur Hospital, for organizing a team of specialist pathologists for collection of blood and urine samples and for explaining to the participating subjects about the importance of the study. Further, we gratefully acknowledge the volunteering participants for this study from Pratap Pur Hari, Kanpur. The authors also express their gratitude to the anonymous reviewers for providing valuable comments and insight into the PBPK model's variability.