ArticleALTEX2017
A tiered, Bayesian approach to estimating of population variability for regulatory decision-making.
Article in ALTEX, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 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
- 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
- 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
- Characterizing PFAS hazards and risks: a human population-based in vitro cardiotoxicity assessment strategy.Human genomics · 2024Article
- Technical evaluation and standardization of the human thyroid microtissue assay.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- Invited Perspective: Uneven Progress Addressing Population Variability in Human Health Risk Assessment.Environmental health perspectives · 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
- Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).Archives of toxicology · 2024Review
- Article
- Advancing probabilistic risk assessment by integrating human biomonitoring, new approach methods, and Bayesian modeling: A case study with the mycotoxin deoxynivalenol.Environment international · 2023Article
- A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo.Toxicological sciences : an official journal of the Society of Toxicology · 2023Article
- Article
- Are Non-animal Systemic Safety Assessments Protective? A Toolbox and Workflow.Toxicological sciences : an official journal of the Society of Toxicology · 2022Article
- Decision-Making with New Approach Methodologies: Time to Replace Default Uncertainty Factors with Data.Toxicological sciences : an official journal of the Society of Toxicology · 2022Article
- Article
- Model systems and organisms for addressing inter- and intra-species variability in risk assessment.Regulatory toxicology and pharmacology : RTP · 2022Review
- Article
- A new approach method for characterizing inter-species toxicodynamic variability.Journal of toxicology and environmental health. Part A · 2021Article
- Cardiotoxicity Hazard and Risk Characterization of ToxCast Chemicals Using Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes from Multiple Donors.Chemical research in toxicology · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Characterizing human variability in susceptibility to chemical toxicity is a critical issue in regulatory decision-making, but is usually addressed by a default 10-fold safety/uncertainty factor. Feasibility of population-based in vitro experimental approaches to more accurately estimate human variability was demonstrated recently using a large (~1000) panel of lymphoblastoid cell lines. However, routine use of such a large population-based model poses cost and logistical challenges. We hypothesize that a Bayesian approach embedded in a tiered workflow provides efficient estimation of variability and enables a tailored and sensible approach to selection of appropriate sample size. We used the previously collected lymphoblastoid cell line in vitro toxicity data to develop a data-derived prior distribution for the uncertainty in the degree of population variability. The resulting prior for the toxicodynamic variability factor (the ratio between the median and 1% most sensitive individuals) has a median (90% CI) of 2.5 (1.4-9.6). We then performed computational experiments using a hierarchical Bayesian population model with lognormal population variability with samples sizes of n = 5 to 100 to determine the change in precision and accuracy with increasing sample size. We propose a tiered Bayesian strategy for fit-for-purpose population variability estimates: (1) a default using the data-derived prior distribution; (2) a pilot experiment using samples sizes of ~20 individuals that reduces prior uncertainty by > 50% with > 80% balanced accuracy for classification; and (3) a high confidence experiment using sample sizes of ~50-100. This approach efficiently uses in vitro data on population variability to inform decision-making.
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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.