Biology subjects

Wambaugh, J. F.

Publications and source records attributed to Wambaugh, J. F..

3 recordsLinked to original sources

bioRxiv2024

Enabling Transparent Toxicokinetic Modeling for Public Health Risk Assessment

Toxicokinetics describes the absorption, distribution, metabolism, and elimination of chemicals by the body. Predictions from toxicokinetic models provide key information for chemical risk assessment. Traditionally, these predictions extrapolate from experimental animal species data (for example, in rats) to humans. More recently, toxicokinetics has been used for extrapolation from in vitro "new approach methods (NAMs)" for toxicology to in vivo. Chemical-specific in vivo toxicokinetic data are often unavailable for the thousands of chemicals in commerce. Therefore, large amounts of in vitro data measuring chemical-specific toxicokinetics have been collected. These data enable "high-throughput toxicokinetic" or HTTK modeling. The httk R package provides a library of chemical-specific data from peer-reviewed HTTK studies. httk further provides a suite of tools for parameterizing and evaluating toxicokinetic models. httk uses the open-source language MCSim to describe models for compartmental and physiologically based toxicokinetics (PBTK), MCSim can convert the model descriptions into a high-speed C code script. New models are integrated into httk using the open-source package development functionality in R, a model documentation file (R script), and the HTTK model description code file (C script). In addition to HTTK models, httk provides a series of functionalities such as unit conversion, model parameterization, Monte Carlo simulations for uncertainty propagation and biological variability, in vivo-derived data for evaluating model predictions, and other model utility functions. Here, we describe in detail how to add new HTTK models to httk and take advantage of the pre-existing data and functionality in the package. As a demonstration, we describe the integration of the gas inhalation PBTK model into httk. Modern modeling approaches, as exemplified by httk, allow for clear communication, reproducibility, and public scrutiny. The intention of httk is to provide a transparent, open-source tool for toxicokinetics, bioinformatics, and public health risk assessment. Author SummaryWe describe the integration and evaluation of new physiologically based toxicokinetic (PBTK) models into an open-source R package. Adding a new model to the R package allows a modeler to use the existing tools and data for in vitro to in vivo extrapolation (IVIVE). Integration with the R statistical analysis environment further allows model assessment. This workflow is designed to create a more transparent and reproducible approach to toxicokinetic models developed for various exposure scenarios. Here, we demonstrate the model integration and evaluation workflow with an inhalation model. Additionally, we provide an evaluation of the overall package performance as new models, data, and functionality are added over time. Our results show that transparent development of models, and use of existing data within the open-source R package format, allows for improvement of in vitro to in vivo extrapolation estimations. IVIVE is vital for advancement of 21st century human health risk assessment.

pharmacology and toxicology↗

bioRxiv2022

Chemical screening of food-related chemicals for human fatty liver risk: Combining high content imaging of cellular responses with in vitro to in vivo extrapolation

1Nonalcoholic fatty liver disease (NAFLD) is an increasingly prevalent human disease with accumulating evidence linking its pathophysiology and co-morbidities to chemical exposures. The complex pathophysiology of NAFLD has limited the elucidation of potential chemical etiologies. In this study we generated a high-content imaging analysis method for the simultaneous quantification of sentinel steatosis cellular markers in chemically exposed human liver cells in vitro combined with a computational model for the extrapolation of human oral equivalent doses (OED). First, the in vitro test method was generated using 14 reference chemicals with known capacities to induce cellular alterations in nuclear morphology, lipid accumulation, mitochondrial membrane potential and oxidative stress. These effects were quantified on a single cell- and population-level, and then, using physiologically based pharmacokinetic modelling and reverse dosimetry, OEDs were extrapolated from these in vitro data. The extrapolated OEDs were confirmed to be within biologically relevant exposure ranges for the reference chemicals. Next, we tested 14 chemicals found in food, selected from thousands of putative chemicals on the basis of structure-based prediction for nuclear receptor activation. Amongst these, orotic acid had an extrapolated OED overlapping with realistic exposure ranges. By the strategy developed in this study, we were able to characterize known NAFLD-inducing chemicals and translate to data scarce food-related chemicals, amongst which we identified orotic acid to induce steatosis. This strategy addresses needs of next generation risk assessment, and can be used as a first chemical prioritization hazard screening step in a tiered approach to identify chemical risk factors for NAFLD.

pharmacology and toxicology↗

bioRxiv2018

Empirical Models for Anatomical and Physiological Changes in a Human Mother and Fetus During Pregnancy and Gestation

Many parameters treated as constants in traditional physiologically based pharmacokinetic models must be formulated as time-varying quantities when modeling pregnancy and gestation due to the dramatic physiological and anatomical changes that occur during this period. While several collections of empirical models for such parameters have been published, each has shortcomings. We sought to create a repository of empirical models for tissue volumes, blood flow rates, and other quantities that undergo substantial changes in a human mother and her fetus during the time between conception and birth, and to address deficiencies with similar, previously published repositories. We used maximum likelihood estimation to calibrate various models for the time-varying quantities of interest, and then used the Akaike information criterion to select an optimal model for each quantity. For quantities of interest for which time-course data were not available, we constructed composite models using percentages and/or models describing related quantities. In this way, we developed a comprehensive collection of formulae describing parameters essential for constructing a PBPK model of a human mother and her fetus throughout the approximately 40 weeks of pregnancy and gestation. We included models describing blood flow rates through various fetal blood routes that have no counterparts in adults. Our repository of mathematical models for anatomical and physiological quantities of interest provides a basis for PBPK models of human pregnancy and gestation, and as such, it can ultimately be used to support decision-making with respect to optimal pharmacological dosing and risk assessment for pregnant women and their developing fetuses. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.\n\nAUTHOR SUMMARYPhysiologically based pharmacokinetic modeling is a well-known technique for making predictions about internal time-course concentrations of a substance that has entered an organism. This tool is widely used in both pharmaceutical research and human health risk assessment because it harnesses one of the fundamental tenets of both pharmacology and toxicology: it is the concentrations of an active chemical that reach internal target tissues, rather than externally applied \"doses\", that govern the extent of the response (whether beneficial or adverse). Constructing physiologically based pharmacokinetic models for pregnancy and gestation presents a considerable challenge because many of the required parameters (such as blood flow rates or tissue volumes) that are typically assumed to be constant in adult models or short-duration simulations cannot be assumed to be constant when modeling pregnancy. Here we present models, stated as functions of gestational age, for anatomical and physiological changes that occur in a human mother and fetus during pregnancy and gestation. We evaluated and selected models by applying a consistent statistical technique, and where possible, we compared results produced by our models to those produced by previously-published models. The collection of pregnancy parameter models presented here represents the most comprehensive such collection to date.

developmental biology↗