Report on the European Partnership for Alternative Approaches to Animal Testing (EPAA) “New Approach Methodologies (NAMs) User Forum Kick-Off Workshop”
Bibliographic record
Abstract
The European Partnership for Alternative Approaches to Animal Testing (EPAA) held the “New Approach Methodologies (NAMs) User Forum Kick-Off Workshop”, at the European Chemicals Agency (ECHA), Helsinki, Finland on 7–8 December 2023. The aim of the User Forum was to gain insight into the regulatory use of NAMs, with a particular reference to Next Generation Risk Assessment (NGRA), for chemical safety assessment. To achieve this, presentations summarised the learnings and experiences of previous EPAA Skin Sensitisation User Forums as well as that of the European Commission's Scientific Committee on Consumer Safety (SCCS). The findings of five case studies were summarised that illustrated the use of NAMs. The presentations and subsequent discussions allowed for learnings and insights to be compiled from all stakeholders with regard to the use of NAMs. Recommendations for the regulatory use of NAMs in NGRA were made, namely for exposure assessment; hazard identification; using tiered and targeted testing strategies; performing risk assessment using NAM data; the practical implementation of NAMs; the use of -omics technologies; and the needs for capacity building and training. The EPAA User Forum provided an open platform for safety assessors to share learnings and experiences. Recommendations for the format and topics of future EPAA User Forums were also made. • Broad stakeholder support exists for the regulatory use of NAMs for chemical safety. • NAMs are applicable in assessment of internal exposure and hazard identification. • Tiered testing strategies allow NAMs to be used in risk assessment. • Applicability, confidence and practical implementation of NAMs are required. • Areas to improve regulatory uptake of NAMs are identified.
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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 | 0.033 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.114 | 0.032 |
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".