ArticleToxicological sciences : an official journal of the Society of Toxicology2020
A Bayesian Method for Population-wide Cardiotoxicity Hazard and Risk Characterization Using an In Vitro Human Model.
Article in Toxicological sciences : an official journal of the Society of Toxicology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.
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Who cites it
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes as an in vitro model in toxicology: strengths and weaknesses for hazard identification and risk characterization.Expert opinion on drug metabolism & toxicology · 2021Pooled it
- Probabilistic Concentration-Response Modeling and Risk Prioritization of Defined Mixtures of PFAS Using HumanEnvironmental science & technology · 2026Article
- Quantitative estimates of inter-individual variability for new approach methodologies-based systemic safety toolbox using a population-based human in vitro model.Toxicological sciences : an official journal of the Society of Toxicology · 2026Article
- A Deep-Learning-Based Scoring Framework for Large-Scale Multi-donor Cardiotoxicity Screening.Computational and structural biotechnology journal · 2026Article
- Computationally informed point of departure evaluation for proarrhythmic cardiotoxicity assessment using 3D engineered cardiac microtissues from human iPSC-derived cardiomyocytes.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Reducing uncertainty in dose-response assessments by incorporating Bayesian benchmark dose modeling and in vitro data on population variability.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!Journal of toxicology and environmental health. Part B, Critical reviews · 2025Review
- Characterizing PFAS hazards and risks: a human population-based in vitro cardiotoxicity assessment strategy.Human genomics · 2024Article
- In vitro to in vivo extrapolation from 3D hiPSC-derived cardiac microtissues and physiologically based pharmacokinetic modeling to inform next-generation arrhythmia risk assessment.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes.Chemical research in toxicology · 2024Article
- Hazard and risk characterization of 56 structurally diverse PFAS using a targeted battery of broad coverage assays using six human cell types.Toxicology · 2024Article
- Mapping Interindividual Variability of Toxicodynamics Using High-Throughput Transcriptomics and Primary Human Hepatocytes from Fifty Donors.Environmental health perspectives · 2024Article
- Evaluating scientific confidence in the concordance of in vitro and in vivo protective points of departure.Regulatory toxicology and pharmacology : RTP · 2024Article
- Invited Perspective: Uneven Progress Addressing Population Variability in Human Health Risk Assessment.Environmental health perspectives · 2024Article
- Proof of concept for quantitative adverse outcome pathway modeling of chronic toxicity in repeated exposure.Scientific reports · 2024Article
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- Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling: A case study with the mycotoxin deoxynivalenol.Environment international · 2023Article
- Beyond pharmaceuticals: Fit-for-purpose new approach methodologies for environmental cardiotoxicity testing.ALTEX · 2023Review
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Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes are an established model for testing potential chemical hazards. Interindividual variability in toxicodynamic sensitivity has also been demonstrated in vitro; however, quantitative characterization of the population-wide variability has not been fully explored. We sought to develop a method to address this gap by combining a population-based iPSC-derived cardiomyocyte model with Bayesian concentration-response modeling. A total of 136 compounds, including 54 pharmaceuticals and 82 environmental chemicals, were tested in iPSC-derived cardiomyocytes from 43 nondiseased humans. Hierarchical Bayesian population concentration-response modeling was conducted for 5 phenotypes reflecting cardiomyocyte function or viability. Toxicodynamic variability was quantified through the derivation of chemical- and phenotype-specific variability factors. Toxicokinetic modeling was used for probabilistic in vitro-to-in vivo extrapolation to derive population-wide margins of safety for pharmaceuticals and margins of exposure for environmental chemicals. Pharmaceuticals were found to be active across all phenotypes. Over half of tested environmental chemicals showed activity in at least one phenotype, most commonly positive chronotropy. Toxicodynamic variability factor estimates for the functional phenotypes were greater than those for cell viability, usually exceeding the generally assumed default of approximately 3. Population variability-based margins of safety for pharmaceuticals were correctly predicted to be relatively narrow, including some below 10; however, margins of exposure for environmental chemicals, based on population exposure estimates, generally exceeded 1000, suggesting they pose little risk at current general population exposures even to sensitive subpopulations. Overall, this study demonstrates how a high-throughput, human population-based, in vitro-in silico model can be used to characterize toxicodynamic population variability in cardiotoxic risk.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.