The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment.

Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.

Framework for risk assessment of PFAS utilizing experimental studies and in-silico models.

Perfluoroalkyl substances (PFAS), especially PFOS and PFOA, are two widely used synthetic chemicals that can impact human health based on evidence from animal and epidemiologic studies. In this paper, we have reviewed and summarized the influence of PFAS exposure on health, pointing the quality of evidence, and applied translational techniques to integrate evidence for PFAS policy making. This is the first review where highly referred articles on PFAS used for policymaking by several regulatory agencies were collected and evaluated based on the review guidelines developed by the US National Toxicology Program's Office of Health Assessment and Translation (OHAT) review guidelines. Several limitations were observed, including co-exposure to multiple chemicals and limited measurement of primary and secondary outcomes related to specific toxicity. However, data from all the studies provided a moderate to strong level of confidence for link between PFAS exposure and different adverse outcomes. Secondly, for translating the risk to humans, an in-silico model and scaling approach was utilized. Physiologically based pharmacokinetic model (PBPK) was used to calculate the human equivalent dose (HED) from two widely accepted studies and compared with tolerable daily intakes (TDIs) established by various regulatory agencies. Inter-species dose extrapolation was done to compare with human the relevance of dosing scenarios used in animals. Overall, a framework for translation of risk was proposed based on the conclusions of this review with the goal of improving policymaking. The current paper can improve the methodological protocols for PFAS experimental studies and encourage the utilization of in-silico models for translating risk.

Risk Assessment of Perfluorooctane Sulfonate (PFOS) using Dynamic Age Dependent Physiologically based Pharmacokinetic Model (PBPK) across Human Lifetime.

The widespread use of Perfluorooctane sulfonate (PFOS) in everyday life, its long half-life, and the lipophilicity that makes it easily accumulate in the body, raises the question of its safe exposure among different population groups. There are currently enough epidemiological studies showing evidence of PFOS exposure and its associated adverse effects on humans. Moreover, it is already known that physiological changes along with age e.g. organ volume, renal blood flow, cardiac output and albumin concentrations affect chemicals body burden. Human biomonitoring cohort studies have reported PFOS concentrations in blood and autopsy tissue data with PFOS present in sensitive organs across all human lifespan. However, to interpret such biomonitoring data in the context of chemical risk assessment, it is necessary to have a mechanistic framework that explains show the physiological changes across age affects the concentration of chemical inside different tissues of the human body. PBPK model is widely and successfully used in the field of risk assessment. The objective of this manuscript is to develop a dynamic age-dependent PBPK model as an extension of the previously published adult PFOS model and utilize this model to predict and compare the PFOS tissue distribution and plasma concentration across different age groups. Different cohort study data were used for exposure dose reconstruction and evaluation of time-dependent concentration in sensitive organs. Predicted plasma concentration followed trends observed in biomonitoring data and model predictions showed the increased disposition of PFOS in the geriatric population. PFOS model is sensitive to parameters governing renal resorption and elimination across all ages, which is related to PFOS half-life in humans. This model provides an effective framework for improving the quantitative risk assessment of PFOS throughout the human lifetime, particularly in susceptible age groups. The dynamic age-dependent PBPK model provides a step forward for developing such kind of dynamic model for other perfluoroalkyl substances.