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Quality changes to approved biotherapeutic product: Simulated case studies on reporting categories & supporting data requirements

2019· review· en· W2981766175 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

VenueBiologicals · 2019
Typereview
Languageen
FieldImmunology and Microbiology
TopicBiosimilars and Bioanalytical Methods
Canadian institutionsHealth Canada
FundersWorld Health Organization
KeywordsQuality (philosophy)Product (mathematics)BusinessProcess managementProcess (computing)Order (exchange)Operations managementRisk analysis (engineering)Computer scienceEngineeringFinance

Abstract

fetched live from OpenAlex

Changes are essential for the continual improvement of the manufacturing process and for maintaining state-of-the-art controls on biotherapeutic products and such changes often need to be implemented after the product has been approved. WHO guidelines on procedures and data requirement for changes to approved biotherapeutic products were issued in 2017 to provide guidance to national regulatory authorities and manufacturers on the regulation of changes to already licensed biotherapeutic products in order to assure their continued quality, safety and efficacy, as well as continuity of supply and access. The case studies in this article were prepared to be used for WHO implementation workshops. Using these case studies, an interactive discussion was carried out among the workshop participants, and this article reflects the outcomes of case study exercise and lessons learnt from the 1st implementation workshop on the guidelines held on 25-26 June 2019, Seoul, Korea.

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)0.009
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.742
GPT teacher head0.585
Teacher spread0.157 · 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