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Record W3206808995 · doi:10.1016/j.lanepe.2021.100219

Impact of the European Union on access to medicines in low- and middle-income countries: A scoping review

2021· review· en· W3206808995 on OpenAlexaff
Katrina Perehudoff, Carlos E. Durán, Іван Демченко, Valentina Mazzanti, Pramiti Parwani, Fátima Suleman, Anniek de Ruijter

Bibliographic record

VenueThe Lancet Regional Health - Europe · 2021
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEuropean unionAuthorizationPolitical scienceAccessionWelfare economicsHumanitiesMember statesBusinessGeographyInternational tradeEconomics

Abstract

fetched live from OpenAlex

This Scoping Review synthesises evidence of the impacts of European Union (EU) law, regulation, and policy on access to medicines in in non-EU low- and middle-income countries (LMICs), and the mechanisms and nature of those impacts. We searched eight scholarly databases and grey literature published between 1995-2021 in four languages. The EU exerts global influence on pharmaceuticals in LMICs in three ways: explicit agreements between EU-LMICs (ex. accession, trade, and economic agreements); LMICs' reliance on EU internal regulation, standards, or methods (ex. market authorisation); ‘soft’ forms of EU influence (ex. research funding, capacity building). This study illustrates that EU policy makers adopt measures with the potential to influence medicines in LMICs despite limited evidence of their positive and/or negative impact(s). The EU's fragmented internal and external actions in fields related to pharmaceuticals reveal the need for principles for global equitable access to medicines to guide EU policy. Esta revisión exploratoria sintetiza la evidencia disponible sobre el impacto que ejercen las leyes, las políticas y las regulaciones de la Unión Europea (UE) sobre el acceso a los medicamentos en países de bajo y mediano ingreso (PBMI) que no pertenecen a la UE. La búsqueda se realizó en ocho bases de datos académicas, incluyendo literatura gris. Se incluyeron publicaciones en cuatro idiomas entre 1995 y 2021. Como resultado principal se encontró que la UE ejerce su influencia sobre los productos farmacéuticos en los PBMI a través de tres mecanismos principales: i) acuerdos explícitos entre la UE y los PBMI, por ejemplo, acuerdos de ascensión a la UE o tratados comerciales, ii) utilización de la normativa, estándares o métodos de la UE por parte de los PBMI (reliance) para, por ejemplo, autorizar el ingreso de nuevos medicamentos a partir de la autorización previa por parte de la UE) y, iii) formas blandas de influencia de la UE, por ejemplo, a través de financiación a la investigación o al desarrollo de capacidades locales. Esta revisión revela que los tomadores de decisión de la UE adoptan medidas que, a pesar de la escasa evidencia que sustenta su impacto, positivo o negativo, tienen el potencial de influir en el acceso a los medicamentos de los PBMI. El accionar fragmentado de la UE respecto a los productos farmacéuticos, tanto a nivel interno como externo, son una clara muestra de la necesidad de crear principios que guíen las políticas de la UE frente al acceso equitativo a los medicamentos a nivel global. Это обзорное исследование обобщает данные о глобальном регуляторном влиянии Европейского Союза (ЕС) на доступ к лекарственным средствам в странах с низким и средним уровнем доходом (СНСД), которые не входят в ЕС. Был осуществлен поиск словосочетаний «развивающиеся страны», «Европейский Союз», «лекарственные средства» в восьми базах данных (OvidMedline, Scopus, Web of Science, Epistemonikos, HeinOnline, LILACS, E-library, Научный архив) и серой литературе. Были рассмотрены документы на английском, испанском, португальском и русском, опубликованные между 1995-2021, которые касались права ЕС, регуляторной политики относительно доступа к лекарственным средствам в СНСД. Было отобрано 3954 публикаций, из которых 109 включены (13 научных статей). ЕС оказывает глобальное влияние на лекарственные средства в СНСД тремя способами: определенные соглашения между ЕС-СНСД; использование СНСД внутренних норм, стандартов и методов ЕС; «мягкие» формы влияния ЕС. Данное исследование демонстрирует, что разработчики политики ЕС принимают меры с потенциальным влиянием на лекарственные средства в СНСД, несмотря на ограниченные данные об их положительном и/или негативном влиянии (- ях).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.087
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0220.025
Science and technology studies0.0010.002
Scholarly communication0.0070.006
Open science0.0020.003
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.326
GPT teacher head0.466
Teacher spread0.141 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations20
Published2021
Admission routes1
Has abstractyes

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