Can medical product development be better aligned with global needs?
Bibliographic record
Abstract
Go to any pharmacy and you'll see a dizzying array of shampoos and facial moisturizers with new kinds emerging all the time.There is no medical need for more ways to wash your hair or moisturize your skin, but the huge financial returns guarantee continual investment by companies into rebranding.By contrast, there are many disabling or fatal diseases for which we desperately need new medical products (such as medicines, vaccines, and diagnostics)-yet few, or none, are available and the product development pipeline is bare. 1 2 Even when these medical products do become available, often they reach high income-countries first, with a time lag of up to several decades before they become available in lower income settings.How has such inequity arisen and how can it be addressed?How drug companies determine whether to engage in product development OPINION
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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 | 0.027 | 0.126 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.039 | 0.036 |
| Insufficient payload (model declined to judge) | 0.022 | 0.012 |
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".