CLINICAL TRIALS AND SCID ROW: THE ETHICS OF PHASE 1 TRIALS IN THE DEVELOPING WORLD
Bibliographic record
Abstract
Relatively little has been written about the ethics of conducting early phase clinical trials involving subjects from the developing world. Below, I analyze ethical issues surrounding one of gene transfer's most widely praised studies conducted to date: in this study, Italian investigators recruited two subjects from the developing world who were ineligible for standard of care because of economic considerations. Though the study seems to have rendered a cure in these two subjects, it does not appear to have complied with various international guidelines that require that clinical trials conducted in the developing world be responsive to their populations' health needs. Nevertheless, policies devised to address large scale, late stage trials, such as the AZT short-course placebo trials, map somewhat awkwardly to early phase studies. I argue that interest in conducting translational research in the developing world, particularly in the context of hemophilia trials, should motivate more rigorous ethical thinking around clinical trials involving economically disadvantaged populations.
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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 | 0.517 | 0.519 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.051 |
| Scholarly communication | 0.020 | 0.010 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.031 | 0.041 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".