In assessing the distribution and metabolism of toxic compounds in the body, measurements are not always feasible for ethical or technical reasons. Computer modeling oﬀers a reasonable alternative, but the variability and complexity of biological systems pose unique challenges in model building and adjustment. Recent tools from population pharmacokinetics, Bayesian statistical inference, and physiological modeling can be brought together to solve these problems. As an example, we modeled the distribution and metabolism of tetrachloroethylene (PERC) in humans. We derive statistical distributions for the parameters of a physiological model of PERC, on the basis of data from Monster et al. (1979). The model adequately ﬁts both prior physiological information and experimental data. An estimate of the relationship between PERC exposure and fraction metabolized is obtained. Our median population estimate for the fraction of inhaled tetrachloroethylene that is metabolized, at exposure levels exceeding current occupational standards, is 1.5% [95% conﬁdence interval (0.52%, 4.1%)]. At levels approaching ambient inhalation exposure (0.001 ppm), the median estimate of the fraction metabolized is much higher, at 36% [95% conﬁdence interval (15%, 58%)]. This disproportionality should be taken into account when deriving safe exposure limits for tetrachloroethylene and deserves to be veriﬁed by further experiments.

10ahuman metabolism10apharmacokinetics10apopulation toxicokinetics10atetrachloroethylene1 aBois, Frédéric, Y.1 aGelman, Andrew1 aJiang, Jiming1 aMaszle, Don1 aZeise, Lauren1 aAlexeeff, George uhttps://indoor.lbl.gov/publications/population-toxicokinetics02258nas a2200217 4500008004100000245009300041210006900134260001200203300001200215490000700227520154300234653002001777653003201797653002801829653002901857653001901886100002501905700001801930700001801948856007401966 1995 eng d00aHuman interindividual variability in metabolism and risk: the example of 4-aminobiphenyl0 aHuman interindividual variability in metabolism and risk the exa c04/1195 a205-2130 v153 aWe investigate, through modeling, the impact of interindividual heterogeneity in the metabolism of 4-aminobiphenyl (ABP) and in physiological factors on human cancer risk: A physiological pharmacokinetic model was used to quantify the time course of the formation of the proximate carcinogen, N-hydroxy-4-ABP and the DNA-binding of the active species in the bladder. The metabolic and physiologic model parameters were randomly varied, via Monte Carlo simulations, to reproduce interindividual variability. The sampling means for most parameters were scaled from values developed by Kadlubar et al. (Cancer Res., 51: 4371, 1991) for dogs; variances were obtained primarily from published human data (e.g., measurements of ABP N-oxidation, and arylamine N-acetylation in human liver tissue). In 500 simulations, theoretically representing 500 humans, DNA-adduct levels in the bladder of the most susceptible individuals are ten thousand times higher than for the least susceptible, and the 5th and 95th percentiles differ by a factor of 160. DNA binding for the most susceptible individual (with low urine pH, low N-acetylation and high N-oxidation activities) is theoretically one million-fold higher than for the least susceptible (with high urine pH, high N-acetylation and low N-oxidation activities). The simulations also suggest that the four factors contributing most significantly to interindividual differences in DNA-binding of ABP in human bladder are urine pH, ABP N-oxidation, ABP N-acetylation and urination frequency.

10a4-Aminobiphenyl10ainterindividual variability10aMonte Carlo Simulations10apopulation heterogeneity10atoxicokinetics1 aBois, Frédéric, Y.1 aKrowech, Gail1 aZeise, Lauren uhttps://indoor.lbl.gov/publications/human-interindividual-variability