Understanding Interindividual Variability in Biotransformation and Renal Clearance to Improve Personalized Toxicokinetic Modeling in Chemical Assessments

Human toxicokinetics vary widely across individuals due to differences in physiological and biochemical factors. Yet, since such interindividual variability is difficult to quantify, most chemical risk assessment models rely on an "average" individual, potentially under-protecting those with disproportionately high susceptibility. Here, using the case of nicotine and its metabolites, we performed personalized mechanistic toxicokinetic simulations on the PROTEX model for 1,801 Americans to characterize interindividual variability in biotransformation and renal clearance capacities. We quantified interindividual variability by calculating fold deviations in each individual's biotransformation and renal clearance rates, denoted as semiempirical, effective scaling factors α and β, from expected values based on demographic (age, sex) and anthropometric (body weight, height, body fat percentage) features. Results showed an approximately 40-fold range (5th-95th percentile; same after) in α and a 10-fold range in β. When individuals are exposed to the same absorbed chemical dose, interindividual variability in toxicokinetics can result in 15- to 18-fold differences in serum concentrations, of which ∼5-fold can be attributed to physiological variability linked to differences in demographics and anthropometry, while an additional 3- to 3.5-fold can be attributed to variability in α and β. A key implication of this work is to improve personalized reverse dosimetry modeling in the "new approach methodologies" framework. Using the derived α and β values, we estimated average daily absorbed doses of nicotine and compared them with self-reported smoking status. The highest doses were observed among individuals reporting both active and passive smoking, while evidence of underreporting was also detected among some individuals who reported no exposure.