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Record W4416276467 · doi:10.37897/rjphp.2025.3-4.4

Materiovigilance: current status, global perspectives and implication for pharmaceutical practice

2025· article· W4416276467 on OpenAlexaboutno aff
H Rathi, Priyanka Rathi, M. Biyani, Sampat G. Rathod, Ravi Saini

Bibliographic record

VenueRomanian Journal of Pharmaceutical Practice · 2025
Typearticle
Language
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacovigilance and Adverse Drug Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacovigilancePatient safetyEuropean unionRelevance (law)Health careRisk managementMedical deviceLegislation

Abstract

fetched live from OpenAlex

Background. Medical devices are essential components of modern healthcare, but their increasing use has heightened the need for structured safety monitoring. Materiovigilance refers to the systematic detection, reporting, and evaluation of adverse events associated with medical devices. While several countries maintain well-established regulatory systems, India formalized its framework through the Materiovigilance Programme of India (MvPI), coordinated by the Indian Pharmacopoeia Commission. Aim. This narrative overview summarizes the global development of materiovigilance systems, describes India’s regulatory framework, and outlines the relevance of medical device safety monitoring to pharmaceutical professionals. Methods. Literature from PubMed, Scopus, regulatory authority websites, and policy documents published between 2015 and 2025 was reviewed to identify national and international approaches to materiovigilance, common challenges, and opportunities for implementation. Results. Countries such as the United States, European Union members, Japan, Australia, and Canada have established post-marketing surveillance systems for medical devices, whereas India’s MvPI is still evolving since the implementation of the Medical Device Rules (MDR) 2017, which categorize devices into four risk-based classes (A–D). Challenges persist in under-reporting, lack of awareness, limited traceability, and uneven institutional integration. Pharmaceutical professionals can contribute to improved materiovigilance through adverse event reporting, device handling oversight, risk communication, and integration of device safety into existing pharmacovigilance workflows. Conclusion. Materiovigilance complements pharmacovigilance and forms an essential part of broader patient safety systems. Strengthening reporting mechanisms, enhancing awareness among healthcare workers, and involving pharmacists in device safety activities can improve the overall effectiveness of materiovigilance initiatives in India and globally.

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)0.036
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.036
Threshold uncertainty score0.192

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.078
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.011
Science and technology studies0.0010.007
Scholarly communication0.0090.009
Open science0.0030.005
Research integrity0.0050.006
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 head0.077
GPT teacher head0.536
Teacher spread0.459 · 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 designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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