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Record W2082573663 · doi:10.5731/pdajpst.2014.01012

Need for New Technologies for Detection of Adventitious Agents in Vaccines and Other Biological Products

2014· review· en· W2082573663 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

VenuePDA Journal of Pharmaceutical Science and Technology · 2014
Typereview
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsSanofi (Canada)
FundersSanofi PasteurU.S. Food and Drug AdministrationSanofi
KeywordsRisk analysis (engineering)Computer scienceRotavirus vaccineBiochemical engineeringPreclinical testingBiotechnologyRotavirusBusinessVirologyMedicineVirusBiologyEngineeringMedical physics

Abstract

fetched live from OpenAlex

From an industrial perspective, the conventional in vitro and in vivo assays used for detection of viral contaminants have shown their limitations, as illustrated by the unfortunate detection of porcine circovirus contamination in a licensed rotavirus vaccine. This contamination event illustrates the gaps within the existing adventitious agent strategy and the potential use of new broader molecular detection methods. This paper serves to summarize current testing approaches and challenges, along with opportunities for the use of these new technologies. LAY ABSTRACT: Testing of biological products is required to ensure the safety of patients. Recently, a licensed vaccine was found to be contaminated with a virus. This contamination did not cause a safety concern to the patients; however, it highlights the need for using new testing methods to control our biological products. This paper introduces the benefits of these new tests and outlines the challenges with the current tests.

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)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.172
GPT teacher head0.475
Teacher spread0.303 · 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