Evaluating the absence of allometric scaling for hepatic microsomal Phase I and Phase II xenobiotic biotransformation among mammals

Elucidating consistent patterns for xenobiotic biotransformation among mammals is challenging because of intrinsic species differences. At the organism level, pharmacokinetic rate constants are believed to scale allometrically to body weight with a power of ¾, akin to metabolic rate constants, but the mechanism for biotransformation scaling is unclear. Predicting xenobiotic biotransformation through a quantitative in vitro to in vivo extrapolation (QIVIVE) approach combining allometric scaling relationships related to liver physiology and in vitro xenobiotic biotransformation could be promising. This study explores the previously unexplored potential of allometric scaling for hepatic microsomal Michaelis-Menten parameters. Hepatic microsomal Michaelis-Menten parameters, viz., affinity (K_m), maximum velocity (V_max), and in vitro clearance (CL_int), were examined for the xenobiotic biotransformation enzymes Cytochrome P450 (CYP) and UDP-glucuronosyl transferase (UGT). To ensure validity, data for ≥ 4 mammals per substrate biotransformation pathway were collected through a literature search and available databases. Ordinary linear regressions per pathway for each parameter showed that only a few individual regressions scaled statistically significantly to body weight. Averaging all scaling exponents of significant regressions revealed that hepatic microsomal Michaelis-Menten parameters are independent of body weight. Although not statistically significant, the average scaling exponent for each Michaelis-Menten parameter was close to 0. Therefore, differences in enzyme abundance or liver physiology between species are likely contributors to the observed ¾ exponent for allometric scaling relationships of in vivo xenobiotic clearance. Characterisation of underlying mechanisms at an enzyme-substrate level might ultimately improve understanding and estimation of xenobiotic clearance for mammals in QIVIVE approaches.