Inter-individual exposure variability interpretation through reflection of biological age algorithm in physiologically based toxicokinetic model: Application to human risk assessment of di-isobutyl-phthalate

Abstract

Age-related changes and interindividual variability in the degree of exposure to hazardous substances in the environment are pertinent factors to be considered in human risk assessment. Existing risk assessments remain in a one-size-fits-all approach, often without due consideration of inter-individual toxicokinetic variability factors, such as age. The purpose of this study was to advance from the existing risk assessment of hazardous substances based on toxicokinetics to a precise human risk assessment by additionally considering the effects of physiologic and metabolic fluctuations and interindividual variability in age. Qualitative age-associated physiologic and metabolic changes in humans, obtained through a meta-analysis, were quantitatively modeled to produce the final biological age algorithm (BAA). The developed BAAs (for males) were extended and applied to the reported testicular reproductive toxicity-focused di-isobutyl-phthalate (DiBP)-mono-isobutyl-phthalate (MiBP) physiologically based toxicokinetic (PBTK) model in males. The advanced PBTK model combined with the BAA was applied to the human risk assessment based on MiBP biomonitoring data. As a result, the specialized DiBP external exposure values for each age could be estimated. Additionally, by applying the Monte Carlo simulation, the distribution of internal exposure diversity among individuals according to the same external exposure dose could be estimated. The contributions of physiologic and metabolic factors to the age-dependent toxicokinetic changes were approximately 93.41-99.99 and 0.01-6.59%, respectively. In addition, the relative contribution of metabolic factors was major in infants and continued to decrease as age increased (up to about age 30 years). This study provides a step-by-step platform that can be widely applied to overcome the limitations of existing toxicokinetic models that still require interindividual pharmacokinetic variability explanations. This will be important for the rationalization and explanation of inter-individual variability in the pharmacokinetics of many substances.

Keywords: Biological age algorithm; Human risk assessment; Inter-individual exposure variability; Model platform; Physiologically based toxicokinetic model.