Modern science for better quality control of medicinal products “Towards global harmonization of 3Rs in biologicals”: The report of an EPAA workshop
Bibliographic record
Abstract
This article summarizes the outcome of an international workshop organized by the European Partnership for Alternative Approaches to Animal Testing (EPAA) on Modern science for better quality control of medicinal products: Towards global harmonization of 3Rs in biologicals. As regards the safety testing of biologicals, the workshop participants agreed to actively encourage the deletion of abnormal toxicity tests and target animal batch safety tests from all relevant legal requirements and guidance documents (country-specific guidelines, pharmacopoeia monographs, WHO recommendations). To facilitate the global regulatory acceptance of non-animal methods for the potency testing of, e.g., human diphtheria and tetanus vaccines and veterinary swine erysipelas vaccines, international convergence on the scientific principles of the use of appropriately validated in vitro assays for replacing in vivo methods was identified as an overarching goal. The establishment of scientific requirements for new assays was recognized as a further means to unify regulatory approaches in different jurisdictions. It was recommended to include key regulators and manufacturers early in the corresponding discussions. Manufacturers and responsible expert groups, e.g. at the European Directorate for the Quality of Medicines and Health Care of the Council of Europe or the European Medicines Agency, were invited to consider leadership for international collaboration.
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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 | 0.087 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".