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Record W3127870523 · doi:10.1007/s40264-020-01033-z

Risk Management for the 21st Century: Current Status and Future Needs

2021· article· en· W3127870523 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDrug Safety · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversité de MontréalHealth Canada
FundersU.S. Food and Drug Administration
KeywordsMedicineRisk managementRisk analysis (engineering)HarmonizationGuidelinePharmacovigilanceHealth careRisk assessmentManagement scienceEngineeringComputer scienceBusinessPharmacologyDrugPolitical science

Abstract

fetched live from OpenAlex

Global adoption of risk management principles outlined in the International Conference on Harmonisation (ICH) E2E guideline and the Council for International Organizations of Medical Sciences (CIOMS) Working Group VI guidance introduced greater proactivity and consistency into the practice of pharmacovigilance and benefit-risk management throughout the lifecycle of a drug. However, following the release of these guidelines there have been important advances in the science and practice of risk minimisation itself, especially in terms of how risk minimisation measures (RMMs) are designed, implemented, disseminated and evaluated for effectiveness in real-world healthcare settings. In this article, we describe how the field of design, implementation, dissemination and evaluation of RMMs has advanced in recent years while highlighting current areas of challenge and possible solutions. Where possible we cite global examples to demonstrate how evidence-based approaches have informed the development of RMMs. In this context, while taking into consideration local healthcare system policies and national legislations, we conclude with a call for a global effort to harmonise certain areas that focus on, but are not limited to, standardising certain terms and definitions, consistent application of robust methodologies, and outline of best practices for risk minimisation design, implementation, and dissemination.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.918
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.107
GPT teacher head0.367
Teacher spread0.259 · 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