WHO Model list of essential medicines: visions for the future
Bibliographic record
Abstract
contained 186 medicines in 1977 and has evolved to include 502 medicines in 2023. Over time, different articles criticized the methods and process for decisions; however, the list holds global relevance as a model list to over 150 national lists. Given the global use of the model list, reflecting on its future role is imperative to understand how the list should evolve and respond to the needs of Member States. In 2023, the model list Expert Committee recommended the World Health Organization (WHO) to initiate a process to revise the procedures for updating the model list and the criteria guiding decisions. Here, we offer an agenda outlining priority areas and a vision for an authoritative model list. The main areas include improving transparency and trustworthiness of the recommendations; strengthening connection to national lists; and continuing the debate on the principles that should guide the model list, in particular the role of cost and price of essential medicines. These reflections are intended to support efforts ensuring the continued impact of this policy tool.
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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 | 0.039 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".