Grantee Research Project Results
2024 Progress Report: Integrating tissue chips, rapid untargeted analytical methods and molecular modeling for toxicokinetic screening of chemicals, their metabolites and mixtures
EPA Grant Number: R840032Title: Integrating tissue chips, rapid untargeted analytical methods and molecular modeling for toxicokinetic screening of chemicals, their metabolites and mixtures
Investigators: Rusyn, Ivan , Baker, Erin D. , Chiu, Weihsueh A
Institution: Texas A & M University , North Carolina State University
EPA Project Officer: Spatz, Kyle
Project Period: August 1, 2020 through May 2, 2025
Project Period Covered by this Report: August 1, 2023 through July 31,2024
Project Amount: $799,993
RFA: Advancing Toxicokinetics for Efficient and Robust Chemical Evaluations (2019) RFA Text | Recipients Lists
Research Category: Chemical Safety for Sustainability
Objective:
The long-term objective of this project is to support risk-based decisions with new approach methodologies (NAMs) data by demonstrating integration of new biological (i.e., tissue chips), analytical (i.e., IMS-MS), and modeling methods for high fidelity, data-driven IVIVE. Specifically, this project aims to use tissue chips that are already commercially available to generate physiologically relevant toxicokinetic data, as well as to demonstrate how high-throughput detection, identification, and quantification of multiple chemicals, their metabolites, and mixtures can be achieved through the use of Ion mobility spectrometry-mass spectrometry and a computational pipeline and database of thousands of environmental chemicals. We are extending traditional IVIVE approaches by incorporating both tissue chip-based toxicokinetic data and IMS-MS analytical data into high throughput PBPK modeling of both parent chemicals and metabolites. This work will enable a more comprehensive characterization of toxicokinetics and metabolite formation, thereby reducing the uncertainty of traditional IVIVE approaches and improving the basis for decision-making with NAMs data.
The main outcome of this project will be a novel approach and a framework to support risk-based decisions on environmental chemicals and mixtures by demonstrating how an integrated set of novel biological assays (i.e., tissue chips), analytical techniques (i.e., IMS-MS) and computational methods can be used to enable high-fidelity, data-driven toxicokinetic modeling. Overall, the project is pursuing the following specific aims.
Aim 1: To generate physiologically relevant toxicokinetic data for IVIVE by using tissue chips.
Aim 2: To integrate untargeted analytical methods and metabolite predictions into IVIVE.
Aim 3: To integrate tissue chip assays and IMS-MS into high throughput PBPK models for more efficient and robust IVIVE.
Progress Summary:
During the reporting period, significant progress was made on several research fronts related to the use of microphysiological systems (MPS) for toxicokinetic studies and ion mobility spectrometry-mass spectrometry (IMS-MS) for novel molecule identification.
In Aim 1, we focused on the use of commercially available tissue chips to generate physiologically relevant data for regulatory science, especially in the context of in vitro to in vivo extrapolation (IVIVE). Work on liver and proximal tubule MPS models advanced considerably. For liver models, we evaluated the PhysioMimix LC12, a microfluidic system for drug metabolism studies. This model showed high metabolic function, particularly with primary human hepatocytes (PHHs) for up to 14 days. While induced pluripotent stem cell-derived hepatocytes and PHH co-cultured with non-parenchymal cells (NPCs) underperformed, the findings offered useful insights for future model development and adoption in drug development. In addition, power analyses based on replicate experiments and different contexts of use will inform future study designs due to the limited throughput and high cell demand. Overall, this study describes a workflow for independent testing of a complex microphysiological system for specific contexts of use, which may increase end-user adoption in drug development.
Also, two renal proximal tubule models were studied. The OrganoPlate 3-lane 40 showed limited utility for drug transport studies but provided useful information for studying cellular uptake and toxic effects. The PhysioMimix T12 was used to evaluate various human renal proximal tubule epithelial cell (RPTEC) types. Some commercially available RPTECs were unsuitable for transport studies due to poor barrier formation, while TERT1 cell lines performed better, although fluidic conditions had minimal impact on their function. These findings contribute to a more nuanced understanding of the role of fluidic conditions in kidney models.
The team also collaborated on a human placenta organ-on-chip model to study endocrine disruptors. The model successfully replicated the placental environment and demonstrated that tested chemicals caused only localized stress, with the placenta compensating for these exposures.
In Aim 2, our research focused on IMS-MS to identify novel molecules and optimize workflows for feature selection and phenotype classification. The team evaluated over 28,000 small molecules, including lipid standards, providing critical molecular size data for machine learning studies. These new IMS collision cross section (CCS) values expand public databases, aiding analytical studies. Further work was conducted to develop untargeted analysis methods for evaluating unknown bile acids and PFAS, leading to the discovery of 11 new PFAS in the Cape Fear River and new findings in fish fillet. Additionally, a novel screening approach for clinical plasma and water exposomics improved sample classification accuracy by 25%, further enhancing multidimensional data analysis.
In Aim 3, we worked to integrate tissue chip assays with IMS-MS into physiologicallybased pharmacokinetic (PBPK) models for IVIVE, particularly for renal clearance. The team developed an in vitro-in silico model that predicts renal clearance for compounds undergoing both passive and active transport. Using PFAS as a case study, this model showed high concordance with in vivo human data, suggesting that a combined workflow can prioritize PFAS with higher bioaccumulation potential. This model has the potential to be implemented in highthroughput screening, contributing to better predictions of human health risks associated with environmental chemicals.
Future Activities:
In Specific Aim 1, we will continue experiments with the tissue chip models for kidney, gut (Caco-2 cells and human enteroids), and liver (other commercial platforms). We will be testing a number of chemicals in each model and conduct both in vitro and analytical chemistry experiments to collect data for IVIVE analyses in Aim 3. We will be testing both individual chemicals, their metabolites, and mixtures.
In Specific Aim 2, we will complete publication of the screening paper. We will also continue optimization of computational workflows using cheminformatics and machine learning with emphasis on the improving the features and utilizing the molecular descriptors determined from the IMS-MS measurements. Both parent chemicals and their transformation products will continue to be evaluated from complex biological samples and tissue chip models. Errors between experimental and theoretical analyses will be assessed by evaluating molecules present in mixtures and those predicted from theoretical collision cross section values. These will allow an understanding of how well the computations are reproducing the experimental conditions.
In Specific Aim 3, we will work with Aims 1 and 2 to incorporate data from additional chemicals and platforms into our hepatic clearance, gut absorption, and renal clearance frameworks. This includes hepatic clearance calculations using data from various platforms, integration of both traditional Caco-2 and “gut chip” data for calculating gut absorption, and both 2D culture and transwell data for our in vitro-in silico pipeline to calculate renal clearnce. Furthermore, we will explore the integration of Aims 1 and 2 through use of IMS/MS relative quantification instead of traditional analytical techniques in assessing clearance and/or transport in different platforms. In all cases, we will continue to utilize the literature data we have collected on ADME for comparison and analyses of accuracy. Recognizing that potential for in vitro bioavailability to affect IVIVE, we will also examine potential to use in vitro mass balance modeling to improve the accuracy and precision of our IVIVE calculations.
Journal Articles on this Report : 11 Displayed | Download in RIS Format
| Other project views: | All 40 publications | 31 publications in selected types | All 31 journal articles |
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Chappel JR, King ME, Fleming J, Eberlin LS, Reif DM, Baker ES. Aggregated molecular phenotype scores:enhancing assessment and visualization of mass spectrometry imaging data for tissue-based diagnostics. Analytical Chemistry 2023;95(34):12913-12922. |
R840032 (2024) |
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Sakolish C, Moyer HL, Tsai HH, Ford LC, Dickey AN, Wright FA, Han G, Bajaj P, Baltazar MT, Carmichael PL, Stanko JP. Analysis of reproducibility and robustness of a renal proximal tubule microphysiological system OrganoPlate 3-lane 40 for in vitro studies of drug transport and toxicity. Toxicological Sciences 2023;196(1):52-70. |
R840032 (2024) |
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Lim AY, Kato Y, Sakolish C, Valdiviezo A, Han G, Bajaj P, Stanko J, Ferguson SS, Villenave R, Hewitt P, Hardwick RN. Reproducibility and robustness of a liver microphysiological system PhysioMimix LC12 under varying culture conditions and cell type combinations. Bioengineering 2023;10(10):1195. |
R840032 (2024) |
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Kirkwood-Donelson KI, Dodds JN, Schnetzer A, Hall N, Baker ES. Uncovering per-and polyfluoroalkyl substances (PFAS) with nontargeted ion mobility spectrometry–mass spectrometry analyses. Science Advances 2023;9(43):eadj7048. |
R840032 (2024) |
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Stewart AK, Foley MH, Dougherty MK, McGill SK, Gulati AS, Gentry EC, Hagey LR, Dorrestein PC, Theriot CM, Dodds JN, Baker ES. Using multidimensional separations to distinguish isomeric amino acid–bile acid conjugates and assess their presence and perturbations in model systems. Analytical Chemistry 2023;95(41):15357-15366. |
R840032 (2024) |
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Lin HC, Sakolish C, Moyer HL, Carmichael PL, Baltazar MT, Ferguson SS, Stanko JP, Hewitt P, Rusyn I, Chiu WA. An in vitro-in silico workflow for predicting renal clearance of PFAS. Toxicology and Applied Pharmacology 2024;489:117015. |
R840032 (2024) |
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Vidal MS, Richardson LS, Kammala AK, Kim S, Lam PY, Cherukuri R, Thomas TJ, Bettayeb M, Han A, Rusyn I, Menon R. Endocrine-disrupting compounds and their impact on human placental function:evidence from placenta organ-on-chip studies. Lab on a Chip 2024;24(6):1727-1749. |
R840032 (2024) |
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Chappel JR, Kirkwood-Donelson KI, Reif DM, Baker ES. From big data to big insights:statistical and bioinformatic approaches for exploring the lipidome. Analytical and Bioanalytical Chemistry 2024;416(9):2189-2202. |
R840032 (2024) |
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Kirkwood-Donelson KI, Chappel J, Tobin E, Dodds JN, Reif DM, DeWitt JC, Baker ES. Investigating mouse hepatic lipidome dysregulation following exposure to emerging per-and polyfluoroalkyl substances (PFAS). Chemosphere 2024;354:141654. |
R840032 (2024) |
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Sakolish C, Moyer HL, Tsai HH, Ford LC, Dickey AN, Bajaj P, Villenave R, Hewitt P, Ferguson SS, Stanko J, Rusyn I. Comparative analysis of the physiological and transport functions of various sources of renal proximal tubule cells under static and fluidic conditions in PhysioMimix T12 platform. Drug Metabolism and Disposition 2024:100001. |
R840032 (2024) |
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Solosky AM, Kirkwood-Donelson KI, Odenkirk MT, Baker ES. Recent additions and access to a multidimensional lipidomic database containing liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry information. Analytical and Bioanalytical Chemistry 2024:1-7. |
R840032 (2024) |
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Supplemental Keywords:
in vitro-to-in vivo, tissue chips, rapid analytical methods, IMS-MS, NAMsRelevant Websites:
NC State - Collision Cross-section Database Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.