Guidelines for the preclinical in vivo evaluation of pharmacological active drugs for ALS/MND: Report on the 142nd ENMC international workshop
Bibliographic record
Abstract
A transgenic animal model for anterior horn cell loss was established in 1994. This model is based on the insertion of a high copy number of disease-causing human Cu/Zn SOD mutations into the intact mouse genome. It serves to establish hypotheses for the pathogenesis of anterior horn cell death, but also to test potential pharmacological approaches to therapy in human ALS. Today, more than 100 -- published and unpublished -- compounds have been tested in this animal model, a large part of them being reported as successful. However, it proved to be difficult to translate these therapeutic successes in the animal model into human trials. Also, a number of disease-modifying strategies were difficult to reproduce, even by the same group. On the other hand, the step from mice to men means a huge investment for the sponsors of clinical trials and the scientific community. Therefore, establishment of standard methods for drug testing in ALS models is mandatory. In this workshop, clinical and preclinical researchers established in the field of ALS/MND met in Holland in March 2006 in order to establish guidelines for the community for drug testing in mouse models.
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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 | 0.034 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.009 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.008 |
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".