APPLICATIONS OF SENSITIVITY ANALYSIS TO A PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODEL FOR CARBON-TETRACHLORIDE IN RATS

Physiologically based pharmacokinetic (PBPK) models developed from gas uptake experiments have been used to estimate metabolic parameters fo r volatile organic compounds. Due to the potential application of PBPK models to estimate metabolic bioactivation constants in humans, it is important to understand the complex nature of these models and the re sulting estimates. Adult male F344 rats (165-205 g) were individually exposed to carbon tetrachloride (CC1(4)) in gas uptake systems. Three rats at each concentration were exposed for 6 hr to initial concentrat ions of 25, 100, 250, and 1000 ppm CCl4. Partition coefficient determi nations were performed by the vial equilibration technique and used as model inputs. Computer optimizations with the means of each initial c hamber concentration at each time point resulted in an estimate of V-m ax of 0.11 mg/hr (V-maxc = 0.37 mg/hr/kg) and K-m of 1.3 mg/liter. To determine the effect of individual animal variation in V-max optimizat ions were also performed with the mean +/- SD, resulting in V-max esti mates of 0.09 and 0.12 mg/hr, respectively. Similar analysis resulted in K-m estimates of 0.98 and 1.58 mg/liter. The results of the sensiti vity analysis were concentration dependent for CCl4. These results sho w V-max and K-m to be most accurately detected at lower initial chambe r concentrations. Results of the sensitivity analysis at the lowest co ncentration established the following model input hierarchy: blood to air partition > fat partition and fat volume fraction > slowly perfuse d partition, ventilation rate, cardiac output, fat blood flow percenta ge > liver blood flow percentage and slowly perfused blood flow percen tage. Further sensitivity analysis determined V-max and K-m to be high ly correlated when using gas uptake technology and point to the need t o an independent estimate for either constant. In summary, the applica tion of sensitivity analysis to PBPK modeling resulted in an increased understanding of factors governing the estimation of metabolic parame ters. (C) 1994 Academic Press, Inc.