Ethics codes and use of new and innovative drugs
Bibliographic record
Abstract
Treatment with new and/or innovative drugs with uncertain safety and efficacy profile is associated with substantial ethical concerns. The main objective of this paper is to present guidance on the use of such drugs contained in: (i) major international codes and guidelines pertaining to medical ethics and biomedical research; (ii) national codes of medical ethics and professional conduct of the USA, Canada, Australia, New Zealand, the UK, Ireland, France and Germany. Out of the four international codes and guidelines analysed, only the Declaration of Helsinki addresses the question of the use of unproven drugs. Among national codes, only two (USA and New Zealand) explicitly allow for use of new or innovative drugs. Moreover, treatment with unproven drugs seems to be permissible under the French code, though this is not stated explicitly. The remaining codes do not contain any articles on the use of new and innovative drugs. An update of existing articles, as well as the addition of new guidelines to the codes, should be considered in view of the rapid pace of development and introduction to clinical practice of new drugs. This work is relevant to innovative off-label applications of approved drugs and expanded access to investigational drugs.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".