Off-trial access to experimental cancer agents for the terminally ill: balancing the needs of individuals and society
Bibliographic record
Abstract
The development of cancer therapies is a long and arduous process. Because it can take several years for a cancer agent to pass clinical testing and be approved for use, terminal cancer patients rarely have the time to see these experimental therapies become widely available. For most terminal cancer patients the only opportunity they have to access an experimental drug that could potentially improve their prognosis is by joining a clinical trial. Unfortunately, several aspects of clinical trial methodology that are set in place in order to optimise drug development for the benefit of future generations of cancer patients, pose significant limitations to current patient participation. Therefore, several terminal cancer patients believe that they should have the right to access experimental agents that have passed initial safety testing without having to participate in clinical trials. However, granting off-trial access to patients could be detrimental to the scientific process of drug development, and thus could pose significant risks to the health of future patients relying on sound research. Examining this matter through two divergent ethical lenses, rights-based ethics and communitarian ethics, may provide new insight into the issues surrounding the balance between the autonomous rights of current terminal cancer patients, and the needs of future patients and the values of society.
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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 | 0.074 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".