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Record W3086015271 · doi:10.33974/ijrpst.v1i4.196

An overview on comparative study of registration requirements for generics in US, Canada and Europe

2020· article· en· W3086015271 on OpenAlexaboutno aff
Meghraj Suryawanshi, Jain minal

Bibliographic record

VenueInternational Journal of Research in Pharmaceutical Sciences and Technology · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
FundersU.S. Food and Drug AdministrationWorld Health Organization
KeywordsProduct (mathematics)Agency (philosophy)BusinessAuthorizationMarketing authorizationProcess (computing)European marketRegulatory agencyNew product developmentMarketingIndustrial organizationInternational tradeComputer scienceComputer securityPolitical sciencePublic administration

Abstract

fetched live from OpenAlex

Generic Drug Product approval is most stringent and crucial process for company with different rules and regulation in different country. For the registration of the product company has to follow regulatory rules and requirement of country specific agency. Company should apply product marketing authorization as per norms of country requirements and should manage life cycle of that product throughout market. Need to understand and describe the various regulatory requirements for the generic drug approval process and comparison of regulated country. To understand the technical requirements required to market medicines in regulated pharmaceutical market. To evaluate similarities and differences within regulated market of U.S, Canada, and Europe. To understand and evaluate differences of post approval Changes within regulated market.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.067
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0220.045
Science and technology studies0.0020.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.568
GPT teacher head0.540
Teacher spread0.028 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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