US Tropical Disease Priority Review Vouchers: Lessons In Promoting Drug Development And Access
Bibliographic record
Abstract
The COVID-19 global pandemic has devastated lives and economies. It has served as a reminder of how critical it is to invest in preventing and treating infectious diseases. Until the COVID-19 pandemic, the largest US government-sponsored reward for infectious disease drug and vaccine development was the Tropical Disease Priority Review Voucher program. Under this program, the Food and Drug Administration awards a priority review voucher to the sponsor of a new drug or vaccine for tropical infectious diseases. The voucher then can be exchanged for the faster review of one drug. We provide case studies for tropical disease voucher recipients between 2007 and 2018, examine the effects of the voucher program on product innovation and access, and recommend that policy makers protect the voucher program while creating complementary incentives.
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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 | 0.050 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.014 | 0.021 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.033 | 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".