Assessing the relevance of ecotoxicological studies for regulatory decision making
Bibliographic record
Abstract
Abstract Regulatory policies in many parts of the world recognize either the utility of or the mandate that all available studies be considered in environmental or ecological hazard and risk assessment (ERA) of chemicals, including studies from the peer-reviewed literature. Consequently, a vast array of different studies and data types need to be considered. The first steps in the evaluation process involve determining whether the study is relevant to the ERA and sufficiently reliable. Relevance evaluation is typically performed using existing guidance but involves application of “expert judgment” by risk assessors. In the present paper, we review published guidance for relevance evaluation and, on the basis of the practical experience within the group of authors, we identify additional aspects and further develop already proposed aspects that should be considered when conducting a relevance assessment for ecotoxicological studies. From a regulatory point of view, the overarching key aspect of relevance concerns the ability to directly or indirectly use the study in ERA with the purpose of addressing specific protection goals and ultimately regulatory decision making. Because ERA schemes are based on the appropriate linking of exposure and effect estimates, important features of ecotoxicological studies relate to exposure relevance and biological relevance. Exposure relevance addresses the representativeness of the test substance, environmental exposure media, and exposure regime. Biological relevance deals with the environmental significance of the test organism and the endpoints selected, the ecological realism of the test conditions simulated in the study, as well as a mechanistic link of treatment-related effects for endpoints to the protection goal identified in the ERA. In addition, uncertainties associated with relevance should be considered in the assessment. A systematic and transparent assessment of relevance is needed for regulatory decision making. The relevance aspects also need to be considered by scientists when designing, performing, and reporting ecotoxicological studies to facilitate their use in ERA. Integr Environ Assess Manag 2017;13:652–663. © 2016 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC) Key Points Relevance assessment of ecotoxicological studies is required to ensure appropriate use in hazard and risk assessment of chemicals. Structured and systematic evaluation processes are preferred to promote reproducibility and transparency. Relevance assessment consists of overarching regulatory relevance and associated aspects concerning exposure and biological components. The examples provided may inform and improve guidance for relevance assessment of ecotoxicological studies for use in regulatory decision making.
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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 | 0.476 | 0.563 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.018 | 0.007 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.007 | 0.010 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".