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Record W4411238754 · doi:10.26452/ijrps.v16i2.4777

A comprehensive examination of regulatory affairs awareness in several pharmacy industries

2025· article· en· W4411238754 on OpenAlexfundno aff
P Pravallika, V Ramadoss, N Audinarayana

Bibliographic record

VenueInternational Journal of Research in Pharmaceutical Sciences · 2025
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Quality and Counterfeiting
Canadian institutionsnot available
FundersHealth CanadaUganda National Council for Science and TechnologyMinistry of Health, Labour and WelfareCollege ter Beoordeling van Geneesmiddelen
KeywordsPharmacyBusinessRegulatory affairsMedicineOperations managementFamily medicineEngineering

Abstract

fetched live from OpenAlex

The registration process for various pharmaceutical products and new drug applications is the primary responsibility of the pharmaceutical drug regulatory affairs department. In the pharmaceutical industry, regulatory affairs (RA) specialists are essential due to their involvement with medical devices. RA offers operational and strategic guidance to accelerate the development of pharmaceutical, biological, and medical devices while working within legal constraints. Its main concerns include ensuring safety, effectiveness, low risk/high reward, and quality evaluation of pharmaceutical products used globally. Different regulatory authorities regulate certification and good manufacturing practices in each country’s regulatory framework. RA also plays a specialized role in drug product development. This abstract highlights research on awareness and knowledge testing in regulatory affairs, conducted among pharmaceutical professionals. A certified online survey, based on key RA concepts, was shared with over 1,000 professionals (academics, students, and industry experts). The results show that industrial professionals possess greater knowledge of RA than scholars and students. The survey concludes that RA education should be incorporated into academic curricula to meet future demands.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.392
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.357
GPT teacher head0.580
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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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