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Record W2959919038

Drug Product Registration in US, EUROPE, JAPAN and CANADA for New Drug and Generics

2014· article· en· W2959919038 on OpenAlexaboutno aff
Sharin Thomas, Mudit Dixit, R. Narayana Charyulu, P Bengre, Rao, Asode Ananthram Shetty

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDrugProduct (mathematics)BusinessDrug approvalApproved drugMarketingDrug developmentMedicinePharmacology
DOInot available

Abstract

fetched live from OpenAlex

Getting a marketing approval includes various junctures such as getting drug substances from approved vendors, finished product development, clinical studies, plant inspection, dossier writing and finally submission to authorities. US, Europe, Japan and Canada are the countries which are regulated for the approval of pharmaceutical products. These countries follow the ICH guidelines for the registration of drug of drug product. But each country has different type of application for the approval of new drug and generic drug. Europe follows different kinds of procedures for the approval of drugs. There is also difference in the duration required for the approval of drug to reach the market. Even though these countries follow harmonized procedures, it is impractical to get global marketing approval at same time and launch in all the regions at one go due to different type of applications and the different procedures. This article discusses the basic requirements for a drug product to reach the market. Keywords: NDA, ANDA, PMDA, TPD

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)0.002
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.682
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.009
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0420.015

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 head0.035
GPT teacher head0.238
Teacher spread0.204 · 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
Published2014
Admission routes1
Has abstractyes

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Same topicPharmaceutical Economics and PolicyFrench-language works237,207