Background: Physiologically based pharmacokinetic (PBPK) models utilize computer-based simulations to predict the pharmacokinetics of drugs. By using mathematical modeling techniques consisting of differential equations to simulate blood flow, tissue compositions, and organ properties, the pharmacokinetic properties of drugs can be better understood. Specifically, PBPK models can provide predictive information about drug absorption, distribution, metabolism, and excretion (ADME). The information gained from PBPK models can be useful in both drug discovery, development, and regulatory science. PBPK models can help to address some of the ethical dilemmas that arise during the drug development process, particularly when examining patient populations where testing a new drug may have significant ethical concerns. Patient populations where significant physiological change (i.e., pregnancy, pediatrics, geriatrics, organ impairment populations, etc.) and pathophysiological influences resulting in PK changes can also benefit from PBPK modeling. Additionally, PBPK models can be utilized to predict variations in drug metabolism resulting from genetic polymorphisms, age, and disease states. Methods: In this mini-review, we examine the various applications of PBPK models in drug metabolism. Current research articles related to drug metabolism in genetics, life-stages, and disease states were reviewed. Results: Several key factors in genetics, life-stage, and disease states that affect metabolism in PBPK models are identified. In genetics, the role of CYP enzymes, genetic polymorphisms, and ethnicity may influence metabolism. Metabolism generally changes over time from neonate, pediatric, adult, geriatric, and perinatal populations. Disease states such as renal and hepatic impairment, weight and other acute and chronic diseases also can also alter metabolism. Several examples of PBPK models applying these physiological changes have been published. Conclusions: The utilization and recognition of these specific areas in PBPK modeling can aid in personalized dosing strategy, clinical trial optimization, and regulatory submission.

Chemical release incidents in the United States involve hazardous chemicals that can harm nearby communities. A historical tracking of these chemical release incidents from 1991 to 2014 across up to 16 states has been conducted by The Agency for Toxic Substances and Disease Registry (ATSDR), utilizing the Hazardous Substances Emergency Events Surveillance (HSEES) and the National Toxic Substance Incidents Program (NTSIP) systems. By analyzing surveillance data, patterns of these different chemical releases can be identified to develop and construct a health-protective course of action. Physiologically Based Pharmacokinetic (PBPK) models can simulate chemical exposures during acute chemical incidents. For a retrospective study of an acute chemical release in 2012, we examined the components necessary to integrate PBPK-modeled exposure assessments in ATSDR’s Assessment of Chemical Exposure (ACE) program. We focused on data from a published investigation of vinyl chloride (VC) exposure to assess the utility of PBPK in evaluating exposures among residential populations near the release site. The initial estimate from the real-time air monitoring at the release site revealed that air levels greatly exceeded the Acute Exposure Guideline Levels (AEGL) of 1200 ppm, with PBPK models predicting corresponding VC blood levels of 3.17 mg/L. “Real-time” and “after-action” air modeling estimated VC levels at various distances from the release site over time. PBPK modeling provided insight into possible residential blood levels of VC over several days following the incident. These findings indicate that PBPK modeling could be valuable for reconstructing exposure scenarios associated with acute chemical releases.