Grantee Research Project Results

Final Report: A tiered hybrid experimental-computational strategy for rapid risk assessment of complex environmental mixtures using novel analytical and toxicological methods

EPA Grant Number: R840450
Title: A tiered hybrid experimental-computational strategy for rapid risk assessment of complex environmental mixtures using novel analytical and toxicological methods
Investigators:
Institution:
EPA Project Officer:
Project Period: September 1, 2022 through May 2, 2025
Project Amount: $750,000
RFA: Development of Innovative Approaches to Assess the Toxicity of Chemical Mixtures Request for Applications (RFA) (2022) RFA Text |  Recipients Lists
Research Category: Health Effects , Endocrine Disruptors , New Approach Methods (NAMs) , Human Health , Safer Chemicals , Mixtures , Chemical Safety for Sustainability , Predictive Toxicology , CSS

Objective:

Evaluation of composition and hazards of chemical mixtures, or complex products classified as UVCBs (unknown variable composition or biological substances), presents a multitude of challenges. These include the presence of unknown constituents, a limited basis for grouping additive and independent components, and the lack of toxicity data on most constituents, and whole mixtures or UVCBs. Recent disasters resulting in redistribution of complex chemical mixtures in the environment have provided our group an opportunity to develop new approaches to rapid composition and hazard characterization to inform rapid decision-making. Our long-term goal is to ensure timely risk-based assessment of mixtures and UVCBs that ensures human health protection from the toxicity of known/unknown components. We will accomplish this through integration of novel toxicological (i.e., human cell-based assays), analytical (i.e., ion mobility spectrometry-mass spectrometry), and modeling (i.e., interaction, mediation and dose reconstruction) methods. We plan to demonstrate the application of these methods in the context of rapid risk assessment/management of sites contaminated with uncharacterized chemical mixtures.

The main outcomes of this project will be a suite of analytical, in vitro, and computational methods and tools that can be applied in a tiered strategy for rapid quantitative characterization of the composition and hazards of complex environmental mixtures and UVCBs. Overall, the project is pursuing the following specific aims.

Aim 1: To determine grouping of chemical mixture components for assessment of hazard(s) through integration of multi-phenotype/multi-tissue bioactivity data from a compendium of human induced pluripotent stem cell (iPSC)-derived cells.

Aim 2: To develop approaches for prioritization of components in whole mixtures or UVCBs that are likely to contribute most to joint toxicity through mediation and interaction methods that integrate multi-dimensional analytical and in vitro bioactivity data.

Aim 3: To evaluate prediction of joint toxicity of whole or defined mixtures and UVCBs through novel probabilistic additivity models of grouped (Aim 1) and prioritized (Aim 2) components.

Aim 4: To demonstrate the integration of the proposed exposure, toxicological and modeling methods into a tiered hybrid experimental-computational strategy for rapid risk assessment of complex environmental mixtures and UVCBs.

Summary/Accomplishments (Outputs/Outcomes):

Specific Aim 1: Grouping of Chemical Mixture Components

In this Aim, the project tested the utility of human iPSC-derived cell models across multiple tissues to group and evaluate chemical mixture components. Studies on PFAS revealed that structural categories alone could not reliably predict bioactivity. Instead, PFAS demonstrated divergent, cell type–specific effects, especially cardiotoxicity, with significant inter-individual variability. Parallel studies on petroleum-derived UVCBs showed that while some composition-bioactivity patterns could be identified, existing manufacturing categories were often too heterogeneous. This body of work highlighted the importance of integrating multi-phenotype in vitro assays with compositional analysis for more accurate hazard grouping.

Key Takeaways and Impact

• Human iPSC-derived cell models (hepatocytes, cardiomyocytes, neurons, endothelial, etc.) were used to characterize bioactivity of PFAS and petroleum-derived UVCBs.
• PFAS studies showed cell type–specific effects (notably cardiotoxicity), limited predictive value of structure-based grouping, and high inter-individual variability in responses.
• UVCB studies integrating chemical composition and bioactivity revealed heterogeneity in manufacturing categories but demonstrated strong links between specific constituents and bioactivity.

Policy and Research Translation

• Findings underscore the limits of structure-based grouping in regulatory toxicology; instead, in vitro phenotypic and transcriptomic data may prove to be more informative for prioritization.
• Data support shifting regulatory evaluation toward human-relevant NAMs, emphasizing variability and risk prioritization beyond class-based hazard assumptions.

Specific Aim 2: Prioritization of Components in Whole Mixtures/UVCBs

Recognizing the complexity of whole mixtures and UVCBs, the project developed analytical and computational approaches to pinpoint components most responsible for joint toxicity. Ion mobility spectrometry-mass spectrometry (IMS-MS) emerged as a powerful tool for crude oil fingerprinting and source attribution, identifying biomarkers linked to toxicity. Advanced statistical methods—including regression modeling and mediation analysis—were applied to link chemical features and transcriptomic signals to bioactivity. These studies underscored the predictive power of polycyclic aromatic content while demonstrating that transcriptomic data provided additional, though incremental, insights.

Key Takeaways and Impact

• Ion mobility spectrometry-mass spectrometry (IMS-MS) proved effective for high-throughput crude oil fingerprinting, enabling source characterization and prospective biomarkers.
• Developed novel statistical tools (ridge regression, mediation analysis) to link chemical features and transcriptomic profiles to bioactivity.
• Identified polycyclic aromatic content (PAC) as a strong predictor of hazard potential, with transcriptomics adding incremental value

Policy and Research Translation

• Advances provide regulators with rapid and reliable methods to prioritize hazardous constituents within complex mixtures.
• Statistical mediation approaches pave the way for integrated frameworks that combine analytic and NAM datasets to guide chemical risk management and resource allocation.

Specific Aim 3: Prediction of Joint Toxicity Using Additivity Models

This aim sought to improve methods for predicting joint toxicity of mixtures by integrating grouping and prioritization data. Although planned experimental work was curtailed, important progress was made in evaluating mass balance models that account for in vitro bioavailability. Comparative studies found that the Armitage model most accurately predicted free media concentrations, while cell-level predictions remained more variable. These efforts provided a practical foundation for better aligning in vitro results with in vivo outcomes, offering guidance for more realistic mixture risk assessment.

Key Takeaways and Impact

• Planned experiments were curtailed due to termination of EPA funding, but progress included evaluation of in vitro mass balance models to improve quantitative in vitro-to-in vivo extrapolation (QIVIVE).
• The Armitage model showed slightly better performance in predicting free media concentrations; chemical property data were critical for predictive accuracy.
• Improvements in bioavailability modeling only modestly increased in vitro–in vivo concordance but established first-line guidance for risk translation.

Policy and Research Translation

• Highlights need for more precise incorporation of bioavailability into regulatory QIVIVE.
• Provides regulators with practical guidance: Armitage model + high-quality chemical property data as baseline approach to improve risk translation for mixtures.

Specific Aim 4: Integration into a Tiered Hybrid Risk Assessment Strategy

The final aim demonstrated how analytical, toxicological, and modeling tools could be integrated into a tiered strategy for rapid risk assessment. A framework was established using iPSC-derived hepatocytes and cardiomyocytes as sentinel models to prioritize petroleum UVCBs for further testing. Probabilistic and Bayesian approaches were developed to link in vitro PODs with biomonitoring data, enhancing confidence in in vitro–in vivo concordance. Beyond mixtures, the team applied NAM data to the evaluation of carcinogenic “Key Characteristics,” illustrating broader policy relevance. Together, these advances show that hybrid experimental-computational approaches can support cost-effective, human-relevant, and regulator-ready decision-making.

Key Takeaways and Impact

• Demonstrated a tiered testing strategy using iPSC-derived hepatocytes and cardiomyocytes to prioritize petroleum UVCBs for in vivo testing.
• Developed probabilistic and Bayesian modeling approaches integrating in vitro points of departure (PODs) with biomonitoring data, improving confidence in risk estimates.
• Applied NAMs to systematically analyze “Key Characteristics of Carcinogens,” showing how human-relevant mechanistic evidence can refine hazard classification.

Policy and Research Translation

• Validates a tiered, cost-effective NAM-driven testing framework for regulatory use in prioritizing complex mixtures.
• Supports broader adoption of probabilistic and Bayesian methods in regulatory decision-making to reduce uncertainty and strengthen confidence in in vitro data.
• Provides actionable frameworks for systematic use of NAMs in cancer hazard assessments and other policy-relevant contexts.

Conclusions:

This project advanced the science and application of New Approach Methodologies (NAMs) for risk assessment of complex environmental mixtures, including PFAS and petroleum-derived UVCBs. By combining state-of-the-art in vitro systems, novel analytical chemistry, and advanced computational/statistical modeling, the research demonstrated feasible pathways for integrating human-relevant data into regulatory decision-making. The outcomes of this work will reduce reliance on traditional animal testing, enhance the ability to account for variability and complexity, and provide regulators with transparent, data-driven tools for prioritization and hazard evaluation. Collectively, these findings position tiered hybrid strategies as practical and impactful solutions for rapid, science-based risk assessment of emerging contaminants and complex mixtures.

References:

Publications/Presentations:

1. Cordova, A.C., Klaren, W.D., Ford, L.C., Grimm, F.A., Baker, E.S., Zhou, Y.-H., Wright, F.A., and Rusyn, I. Integrative chemical-biological grouping of complex high production volume substances from lower olefin manufacturing streams. Toxics 11(7):586. 2023
2. Tsai, H.D., House, J.S., Wright, F.A., Chiu, W.A., and Rusyn, I. A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo. Toxicol Sci 193(2):219-223, 2023.
3. Roman-Hubers, A.T., Cordova, A.C., Barrow, M.P., and Rusyn, I. Analytical chemistry solutions to hazard evaluation of petroleum refining products. Regul Toxicol Pharmacol 137:105310, 2023.
4. Cordova, A.C., Dodds, J.N., Tsai, H.D., Lloyd, D.T., Roman-Hubers, A.T., Wright, F.A., Chiu, W.A., McDonald, T.J., Zhu, R., Newman, G., and Rusyn, I. Application of Ion Mobility Spectrometry-Mass Spectrometry for Compositional Characterization and Fingerprinting of a Library of Diverse Crude Oil Samples. Environ Toxicol Chem 42(11):2336-2349, 2023.
5. Lin, H.-C., Rusyn, I., and Chiu, W.A. Assessing Proarrhythmic Potential of Environmental Chemicals Using a High Throughput In Vitro-In Silico Model with Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. ALTEX 41(1):37-49, 2024.
6. Lu, E.H., Grimm, F.A., Rusyn, I., De Saeger, S., De Boevre, M., and Chiu, W.A. Advancing Probabilistic Risk Assessment by Integrating Human Biomonitoring, New Approach Methods, and Bayesian Modeling: A Case Study with the Mycotoxin Deoxynivalenol. Envir Int 182:108326, 2023.
7. Ford, L.C., Lin, H.C., Tsai, H.H.D., Zhou, Y.H., Wright, F.A., Sedykh, A., Shah, R.R., Chiu, W.A., and Rusyn, I. Hazard and Risk Characterization and Grouping of 56 Structurally Diverse PFAS Using a Targeted Battery of Broad Coverage Assays in Six Human Cell Types. Toxicology 503:153763, 2024.
8. Rusyn, I., and Wright, F. A. Ten years of using key characteristics of human carcinogens to organize and evaluate mechanistic evidence in IARC Monographs on the identification of carcinogenic hazards to humans: Patterns and associations. Toxicological Sciences, 198:141-154, 2024.
9. Lu, E.H, Ford, L.C., Chen, Z., Burnett, S.D., Rusyn, I., and Chiu, W.A. Evaluating Scientific Confidence in the Concordance of In Vitro and In Vivo Protective Points of Departure. Regul Toxicol Pharmacol 148:105596, 2024.
10. Tsai, H.H.D., Ford, L.C., Chen, Z., Dickey, A.N., Wright, F.A. and Rusyn, I. Risk-based prioritization of PFAS using phenotypic and transcriptomic data from human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes. ALTEX 41(3):363-381, 2024.
11. Ford, L.C., Lin, H.C., Zhou, Y.H., Wright, F.A., Gombar, V.K., Sedykh, A., Shah, R.R., Chiu, W.A., and Rusyn, I. Characterizing PFAS Hazards and Risks: A Human Population-Based In Vitro Cardiotoxicity Assessment Strategy. Hum Genomics 18(1):92, 2024.
12. Lu, E.H., Ford, L.C., Rusyn, I., and Chiu, W.A. Reducing uncertainty in dose-response assessments by incorporating Bayesian benchmark dose modeling and in vitro data on population variability. Risk Anal 45:457-472, 2025.
13. Lin, H.C., Ford, L.C., Rusyn, I., and Chiu, W.A. Comparative Analysis of Chemical Distribution Models for Quantitative In Vitro to In Vivo Extrapolation. Toxics 13:439, 2025.
14. Zhou, Y.H., Gallins, P.J., Rusyn, I., and Wright, F.A. An approach to uncover significant direct and mediated relationships in multi-dimensional new approach methods (NAMs) data: A case study of hazard evaluation of petroleum UVCBs. Sci Tot Envir 985:179724, 2025.

Journal Articles:

No journal articles submitted with this report: View all 3 publications for this project

Supplemental Keywords:

in vitro-to-in vivo, mixtures, NAMs.

Progress and Final Reports:

Original Abstract

2023 Progress Report

2024 Progress Report