Use of the Same Model or Modeling Strategy Across Multiple Submissions: Focus on Complex Drug Products.

Evidence shows that there is an increasing use of modeling and simulation to support product development and approval for complex generic drug products in the USA, which includes the use of mechanistic modeling and model-integrated evidence (MIE). The potential for model reuse was the subject of a workshop session summarized in this review, where the session included presentations and a panel discussion from members of the U.S. Food and Drug Administration (FDA), academia, and the generic drug product industry. Concepts such as platform performance assessment and MIE standardization were introduced to provide potential frameworks for model reuse related to mechanistic models and MIE, respectively. The capability of models to capture formulation and product differences was explored, and challenges with model validation were addressed for drug product classes including topical, orally inhaled, ophthalmic, and long-acting injectable drug products. An emphasis was placed on the need for communication between FDA and the generic drug industry to continue to foster maturation of modeling and simulation that may support complex generic drug product development and approval, via meetings and published guidance from FDA. The workshop session provided a snapshot of the current state of modeling and simulation for complex generic drug products and offered opportunities to explore the use of such models across multiple drug products.

Regulatory utility of mechanistic modeling to support alternative bioequivalence approaches: A workshop overview.

On September 30 and October 1, 2021, the US Food and Drug Administration (FDA) and the Center for Research on Complex Generics cosponsored a live virtual workshop titled "Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches." The overall aims of the workshop included (i) engaging the generic drug industry and other involved stakeholders regarding how mechanistic modeling and simulation can support their product development and regulatory submissions; (ii) sharing the current state of mechanistic modeling for bioequivalence (BE) assessment through case studies; (iii) establishing a consensus on best practices for using mechanistic modeling approaches, such as physiologically based pharmacokinetic modeling and computational fluid dynamics modeling, for BE assessment; and (iv) introducing the concept of a Model Master File to improve model sharing between model developers, industry, and the FDA. More than 1500 people registered for the workshop. Based on a postworkshop survey, the majority of participants reported that their fundamental scientific understanding of mechanistic models was enhanced, there was greater consensus on model validation and verification, and regulatory expectations for mechanistic modeling submitted in abbreviated new drug applications were clarified by the workshop.

Physiologically Based Pharmacokinetic Modeling in Risk Assessment: Case Study With Pyrethroids.

The assessment of potentially sensitive populations is an important application of risk assessment. To address the concern for age-related sensitivity to pyrethroid insecticides, life-stage physiologically based pharmacokinetic (PBPK) modeling supported by in vitro to in vivo extrapolation was conducted to predict age-dependent changes in target tissue exposure to 8 pyrethroids. The purpose of this age-dependent dosimetry was to calculate a Data-derived Extrapolation Factor (DDEF) to address age-related pharmacokinetic differences for pyrethroids in humans. We developed a generic human PBPK model for pyrethroids based on our previously published rat model that was developed with in vivo rat data. The results demonstrated that the age-related differences in internal exposure to pyrethroids in the brain are largely determined by the differences in metabolic capacity and in physiology for pyrethroids between children and adults. The most important conclusion from our research is that, given an identical external exposure, the internal (target tissue) concentration is equal or lower in children than in adults in response to the same level of exposure to a pyrethroid. Our results show that, based on the use of the life-stage PBPK models with 8 pyrethroids, DDEF values are essentially close to 1, resulting in a DDEF for age-related pharmacokinetic differences of 1. For risk assessment purposes, this indicates that no additional adjustment factor is necessary to account for age-related pharmacokinetic differences for these pyrethroids.

Application of a combined aggregate exposure pathway and adverse outcome pathway (AEP-AOP) approach to inform a cumulative risk assessment: A case study with phthalates.

Advancements in measurement and modeling capabilities are providing unprecedented access to estimates of chemical exposure and bioactivity. With this influx of new data, there is a need for frameworks that help organize and disseminate information on chemical hazard and exposure in a manner that is accessible and transparent. A case study approach was used to demonstrate integration of the Adverse Outcome Pathway (AOP) and Aggregate Exposure Pathway (AEP) frameworks to support cumulative risk assessment of co-exposure to two phthalate esters that are ubiquitous in the environment and that are associated with disruption of male sexual development in the rat: di(2-ethylhexyl) phthalate (DEHP) and di-n-butyl phthalate (DnBP). A putative AOP was developed to guide selection of an in vitro assay for derivation of bioactivity values for DEHP and DnBP and their metabolites. AEPs for DEHP and DnBP were used to extract key exposure data as inputs for a physiologically based pharmacokinetic (PBPK) model to predict internal metabolite concentrations. These metabolite concentrations were then combined using in vitro-based relative potency factors for comparison with an internal dose metric, resulting in an estimated margin of safety of ~13,000. This case study provides an adaptable workflow for integrating exposure and toxicity data by coupling AEP and AOP frameworks and using in vitro and in silico methodologies for cumulative risk assessment.

Development and Application of a Life-Stage Physiologically Based Pharmacokinetic (PBPK) Model to the Assessment of Internal Dose of Pyrethroids in Humans.

To address concerns around age-related sensitivity to pyrethroids, a life-stage physiologically based pharmacokinetic (PBPK) model, supported by in vitro to in vivo extrapolation (IVIVE) was developed. The model was used to predict age-dependent changes in target tissue exposure of 8 pyrethroids; deltamethrin (DLM), cis-permethrin (CPM), trans-permethrin, esfenvalerate, cyphenothrin, cyhalothrin, cyfluthrin, and bifenthrin. A single model structure was used based on previous work in the rat. Intrinsic clearance (CLint) of each individual cytochrome P450 or carboxylesterase (CES) enzyme that are active for a given pyrethroid were measured in vitro, then biologically scaled to obtain in vivo age-specific total hepatic CLint. These IVIVE results indicate that, except for bifenthrin, CES enzymes are largely responsible for human hepatic metabolism (>50% contribution). Given the high efficiency and rapid maturation of CESs, clearance of the pyrethroids is very efficient across ages, leading to a blood flow-limited metabolism. Together with age-specific physiological parameters, in particular liver blood flow, the efficient metabolic clearance of pyrethroids across ages results in comparable to or even lower internal exposure in the target tissue (brain) in children than that in adults in response to the same level of exposure to a given pyrethroid (Cmax ratio in brain between 1- and 25-year old = 0.69, 0.93, and 0.94 for DLM, bifenthrin, and CPM, respectively). Our study demonstrated that a life-stage PBPK modeling approach, coupled with IVIVE, provides a robust framework for evaluating age-related differences in pharmacokinetics and internal target tissue exposure in humans for the pyrethroid class of chemicals.

Incorporation of in vitro metabolism data and physiologically based pharmacokinetic modeling in a risk assessment for chloroprene.

Objective: To develop a physiologically based pharmacokinetic (PBPK) model for chloroprene in the mouse, rat and human, relying only on in vitro data to estimate tissue metabolism rates and partitioning, and to apply the model to calculate an inhalation unit risk (IUR) for chloroprene.Materials and methods: Female B6C3F1 mice were the most sensitive species/gender for lung tumors in the 2-year bioassay conducted with chloroprene. The PBPK model included tissue metabolism rate constants for chloroprene estimated from results of in vitro gas uptake studies using liver and lung microsomes. To assess the validity of the PBPK model, a 6-hr, nose-only chloroprene inhalation study was conducted with female B6C3F1 mice in which both chloroprene blood concentrations and ventilation rates were measured. The PBPK model was then used to predict dose measures - amounts of chloroprene metabolized in lungs per unit time - in mice and humans.Results: The mouse PBPK model accurately predicted in vivo pharmacokinetic data from the 6-hr, nose-only chloroprene inhalation study. The PBPK model was used to conduct a cancer risk assessment based on metabolism of chloroprene to reactive epoxides in the lung, the target tissue in mice. The IUR was over100-fold lower than the IUR from the EPA Integrated Risk Information System (IRIS), which was based on inhaled chloroprene concentration. The different result from the PBPK model risk assessment arises from use of the more relevant tissue dose metric, amount metabolized, rather than inhaled concentrationDiscussion and conclusions: The revised chloroprene PBPK model is based on the best available science, including new test animal in vivo validation, updated literature review and a Markov-Chain Monte Carlo analysis to assess parameter uncertainty. Relying on both mouse and human metabolism data also provides an important advancement in the use of quantitative in vitro to in vivo extrapolation (QIVIVE). Inclusion of the best available science is especially important when deriving a toxicity value based on species extrapolation for the potential carcinogenicity of a reactive metabolite.

Evaluating opportunities for advancing the use of alternative methods in risk assessment through the development of fit-for-purpose in vitro assays.

An evolving regulatory, scientific, and legislative landscape is driving a fundamental change in how chemical safety decisions are made. As we move to implement changes, regulatory agencies and industry are beginning to adopt tiered approaches, which leverage high-throughput screening technologies for prioritization and read across, followed by interrogation of "hit chemicals" with more rigorous dose-response assessment either in fit-for-purpose human cell-based assays or with traditional in vivo tests. However, to date, suitable in vitro alternatives do not exist for the vast majority of the organ toxicities that form the basis of current regulatory decisions. To successfully support safety decisions, biologically relevant, quantitative, cell-based assays that evaluate dose-response and identify regions of safety for chemical exposure are required. This review evaluates the current state of the science in the development of such assays, identifies key gaps in the current tests, and recommends areas where research efforts may be focused to help move the risk assessment community towards more wide-spread use of in vitro methods. Our analysis suggests that a key shortcoming in the current efforts is the ability to test volatile compounds and to predict pulmonary toxicity. We present a mechanistically-based path forward for the development of a fit-for-purpose lung toxicity assay.

Excretion of Di-2-ethylhexyl phthalate (DEHP) metabolites in urine is related to body mass index because of higher energy intake in the overweight and obese.

A higher body mass index (BMI) has been positively associated with the rate of excretion of di-2-ethylhexyl phthalate (DEHP) metabolites in urine in data from the National Health and Nutrition Examination Survey (NHANES), suggesting an association between DEHP exposure and BMI. The association, however, may be due to the association between body mass maintenance and higher energy intake, with higher energy intake being accompanied by a higher intake of DEHP. To examine this hypothesis, we ran a Monte Carlo simulation with a DEHP physiologically-based pharmacokinetic (PBPK) model for adult humans. A realistic exposure sub-model was used, which included the relation of body weight to energy intake and of energy intake to DEHP intake. The model simulation output, when compared with urinary metabolite data from NHANES, supported good model validity. The distribution of BMI in the simulated population closely resembled that in the NHANES population. This indicated that the simulated subjects and DEHP exposure model were closely aligned with the NHANES population of interest. In the simulated population, the ordinary least squares regression coefficient for log(BMI) as a function of log(DEHP nmol/min) was 0.048 (SE 0.001), as compared with the reported value of 0.019 (SE 0.005). In other words, given our model structure, the higher energy intake in the overweight and obese, and the concomitant higher DEHP exposure, describes the reported relationship between BMI and DEHP.

Determination of Human Hepatic CYP2C8 and CYP1A2 Age-Dependent Expression to Support Human Health Risk Assessment for Early Ages.

Predicting age-specific metabolism is important for evaluating age-related drug and chemical sensitivity. Multiple cytochrome P450s and carboxylesterase enzymes are responsible for human pyrethroid metabolism. Complete ontogeny data for each enzyme are needed to support in vitro to in vivo extrapolation (IVIVE). This study was designed to determine age-dependent human hepatic CYP2C8 expression, for which only limited ontogeny data are available, and to further define CYP1A2 ontogeny. CYP2C8 and 1A2 protein levels were measured by quantitative Western blotting using liver microsomal samples prepared from 222 subjects with ages ranging from 8 weeks gestation to 18 years after birth. The median CYP2C8 expression was significantly greater among samples from subjects older than 35 postnatal days (n = 122) compared with fetal samples and those from very young infants (fetal to 35 days postnatal, n = 100) (0.00 vs. 13.38 pmol/mg microsomal protein; p < 0.0001). In contrast, the median CYP1A2 expression was significantly greater after 15 months postnatal age (n = 55) than in fetal and younger postnatal samples (fetal to 15 months postnatal, n = 167) (0.0167 vs. 2.354 pmol/mg microsomal protein; p < 0.0001). CYP2C8, but not CYP1A2, protein levels significantly correlated with those of CYP2C9, CYP2C19, and CYP3A4 (p < 0.001), consistent with CYP2C8 and CYP1A2 ontogeny probably being controlled by different mechanisms. This study provides key data for the physiologically based pharmacokinetic model-based prediction of age-dependent pyrethroid metabolism, which will be used for IVIVE to support pyrethroid risk assessment for early life stages.

Quantitative bias analysis for epidemiological associations of perfluoroalkyl substance serum concentrations and early onset of menopause.

An association between increased serum concentrations of perfluoroalkyl substances (PFAS) such as perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA) and early menopause has been reported (Knox et al., 2011; Taylor et al., 2014). This association may be explained by the fact that women who underwent menopause no longer excrete PFAS through menstruation. Our objective was to assess how much of the epidemiologic association between PFAS and altered timing of menopause might be explained by reverse causality. We extended a published population life-stage physiologically-based pharmacokinetic (PBPK) model of PFOS and PFOA characterized by realistic distributions of physiological parameters including age at menopause. We then conducted Monte Carlo simulations to replicate the Taylor population (Taylor et al., 2014) and the Knox population (Knox et al., 2011). The analysis of the simulated data overall showed a pattern of results that was comparable to those reported in epidemiological studies. For example, in the simulated Knox population (ages 42-51) the odds ratio (OR) for menopause in the fifth quintile of PFOA compared to those in the first quintile was 1.33 (95% CI 1.26-1.40), whereas the reported OR was 1.4 (95% CI 1.1-1.8). Using our model structure, a substantial portion of the associations reported can be explained by pharmacokinetics.

Pharmacokinetic bias analysis of the epidemiological associations between serum polybrominated diphenyl ether (BDE-47) and timing of menarche.

BACKGROUND: Associations between serum levels of polybrominated diphenyl ether (PBDE) and timing of pubertal development in adolescent girls (e.g., menarche) have been reported in both a cross-sectional and in a longitudinal study. The associations may be biased by growth dilution and pharmacokinetic changes during pubertal development. OBJECTIVES: To use a physiologically-based pharmacokinetic (PBPK) model to assess how much of the epidemiologic association between PBDE and altered timing of menarche might be attributable to growth dilution and pubertal maturation. METHODS: We developed a PBPK model of BDE-47, a major congener of PBDE, to perform Monte Carlo (MC) simulation of plasma BDE-47 levels in a hypothetical target population aged 2 to 22 years old. The model used realistic distributions of physiological parameters including timing of growth spurts and menarche. The simulated data were analyzed as if they had come from an epidemiologic study. We compared the results based on the simulated population to those reported. RESULTS: The population characteristics, including age and body mass index (BMI) were similar between the simulated and reported groups. In the cross-sectional study design, the association between proportion of subjects with menarche before age 12 years and BDE-47 serum concentration was inverse in our simulated population, whereas the reported association was positive. In the longitudinal study design, simulated data were not suggestive of an association, whereas a delay in pubertal onset with higher concentrations of BDE-47 was observed in the epidemiologic study. CONCLUSION: Results of our simulation suggest that in the previous cross-sectional study there was a small negative bias due to pharmacokinetics in the reported relationship between BDE-47 and age at menarche. However, in the longitudinal study there was little evidence of bias. Our study showed how PBPK modeling can be used to quantify the potential bias in epidemiological studies and also suggested that further studies on the optimal approach to modeling exposure are warranted to better understand and quantify the potential bias in the epidemiological associations with BDE-47 due to pharmacokinetics.

Reconstructing exposures from biomarkers using exposure-pharmacokinetic modeling--A case study with carbaryl.

Sources of uncertainty involved in exposure reconstruction for short half-life chemicals were characterized using computational models that link external exposures to biomarkers. Using carbaryl as an example, an exposure model, the Cumulative and Aggregate Risk Evaluation System (CARES), was used to generate time-concentration profiles for 500 virtual individuals exposed to carbaryl. These exposure profiles were used as inputs into a physiologically based pharmacokinetic (PBPK) model to predict urinary biomarker concentrations. These matching dietary intake levels and biomarker concentrations were used to (1) compare three reverse dosimetry approaches based on their ability to predict the central tendency of the intake dose distribution; and (2) identify parameters necessary for a more accurate exposure reconstruction. This study illustrates the trade-offs between using non-iterative reverse dosimetry methods that are fast, less precise and iterative methods that are slow, more precise. This study also intimates the necessity of including urine flow rate and elapsed time between last dose and urine sampling as part of the biomarker sampling collection for better interpretation of urinary biomarker data of short biological half-life chemicals. Resolution of these critical data gaps can allow exposure reconstruction methods to better predict population-level intake doses from large biomonitoring studies.

Associations of Perfluoroalkyl Substances (PFAS) with Lower Birth Weight: An Evaluation of Potential Confounding by Glomerular Filtration Rate Using a Physiologically Based Pharmacokinetic Model (PBPK).

BACKGROUND: Prenatal exposure to perfluoroalkyl substances (PFAS) has been associated with lower birth weight in epidemiologic studies. This association could be attributable to glomerular filtration rate (GFR), which is related to PFAS concentration and birth weight. OBJECTIVES: We used a physiologically based pharmacokinetic (PBPK) model of pregnancy to assess how much of the PFAS-birth weight association observed in epidemiologic studies might be attributable to GFR. METHODS: We modified a PBPK model to reflect the association of GFR with birth weight (estimated from three studies of GFR and birth weight) and used it to simulate PFAS concentrations in maternal and cord plasma. The model was run 250,000 times, with variation in parameters, to simulate a population. Simulated data were analyzed to evaluate the association between PFAS levels and birth weight due to GFR. We compared simulated estimates with those from a meta-analysis of epidemiologic data. RESULTS: The reduction in birth weight for each 1-ng/mL increase in simulated cord plasma for perfluorooctane sulfonate (PFOS) was 2.72 g (95% CI: -3.40, -2.04), and for perfluorooctanoic acid (PFOA) was 7.13 g (95% CI: -8.46, -5.80); results based on maternal plasma at term were similar. Results were sensitive to variations in PFAS level distributions and the strength of the GFR-birth weight association. In comparison, our meta-analysis of epidemiologic studies suggested that each 1-ng/mL increase in prenatal PFOS and PFOA levels was associated with 5.00 g (95% CI: -21.66, -7.78) and 14.72 g (95% CI: -8.92, -1.09) reductions in birth weight, respectively. CONCLUSION: Results of our simulations suggest that a substantial proportion of the association between prenatal PFAS and birth weight may be attributable to confounding by GFR and that confounding by GFR may be more important in studies with sample collection later in pregnancy.

Update on a Pharmacokinetic-Centric Alternative Tier II Program for MMT-Part II: Physiologically Based Pharmacokinetic Modeling and Manganese Risk Assessment.

Recently, a variety of physiologically based pharmacokinetic (PBPK) models have been developed for the essential element manganese. This paper reviews the development of PBPK models (e.g., adult, pregnant, lactating, and neonatal rats, nonhuman primates, and adult, pregnant, lactating, and neonatal humans) and relevant risk assessment applications. Each PBPK model incorporates critical features including dose-dependent saturable tissue capacities and asymmetrical diffusional flux of manganese into brain and other tissues. Varied influx and efflux diffusion rate and binding constants for different brain regions account for the differential increases in regional brain manganese concentrations observed experimentally. We also present novel PBPK simulations to predict manganese tissue concentrations in fetal, neonatal, pregnant, or aged individuals, as well as individuals with liver disease or chronic manganese inhalation. The results of these simulations could help guide risk assessors in the application of uncertainty factors as they establish exposure guidelines for the general public or workers.