Identifying organic chemicals not subject to bioaccumulation in air-breathing organisms using predicted partitioning and biotransformation properties
Bibliographic record
Abstract
Abstract Because the respiration processes contributing to the elimination of organic chemicals deviate between air- and water-breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol–water partition ratio KOW need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted KOW, octanol–air partition ratio KOA, and biotransformation half-life HLB with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false-negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four-fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on KOW and KOA would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air-breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297–1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). KEY POINTS A procedure is described that identifies, based solely on predicted partitioning and biotransformation properties, those organic chemicals that do not require a higher tier assessment for bioaccumulation in air-breathing organisms. By explicitly considering quantitative estimates of the errors of the predicted properties, it is possible to select the number of false negative decisions one is willing to tolerate when applying the procedure. Testing it on a representative set of >1000 diverse organic chemicals, the procedure is shown to be far more effective in identifying chemicals not requiring further bioaccumulation assessment than a simple comparison with log KOA and log KOW thresholds. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air-breathing organisms and for the potential for renal reabsorption.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".