A Toxicokinetic Framework and Analysis Tool for Interpreting Organisation for Economic Co-operation and Development Guideline 305 Dietary Bioaccumulation Tests
Bibliographic record
Abstract
The Organisation for Economic Co-operation and Development guideline 305 for bioaccumulation testing in fish includes the option to conduct a dietary test for assessing a chemical's bioaccumulation behavior. However, the one-compartment toxicokinetic model that is used in the guidelines to analyze the results from dietary bioaccumulation tests is not consistent with the current state of the science, experimental practices, and information needs for bioaccumulation and risk assessment. The present study presents 1) a 2-compartment toxicokinetic modeling framework for describing the bioaccumulation of neutral hydrophobic organic chemicals in fish and 2) an associated toxicokinetic analysis tool (absorption, distribution, metabolism, and excretion [ADME] B calculator) for the analysis and interpretation of dietary bioaccumulation test data from OECD-305 dietary tests. The model framework and ADME-B calculator are illustrated by analysis of fish dietary bioaccumulation test data for 238 substances representing different structural classes and susceptibilities to biotransformation. The ADME of the chemicals is determined from dietary bioaccumulation tests and bioconcentration factors, biomagnification factors, and somatic and intestinal biotransformation rates. The 2-compartment fish toxicokinetic model can account for the effect of the exposure pathway on bioaccumulation, which the one-compartment model cannot. This insight is important for applying a weight-of-evidence approach to bioaccumulation assessment where information from aqueous and dietary test endpoints can be integrated to improve the evaluation of a chemical's bioaccumulation potential. Environ Toxicol Chem 2019;39:171-188. © 2019 SETAC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.026 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.018 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".