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Record W2608656888 · doi:10.1016/j.jbiotec.2017.04.028

Therapeutic glycoprotein production in mammalian cells

2017· review· en· W2608656888 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Biotechnology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsNational Research Council CanadaUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsChinese hamster ovary cellBiopharmaceuticalMonoclonal antibodyGlycoproteinGlycosylationGlycanRecombinant DNAComputational biologyCell biologyBiologyAntibodyCell cultureBiotechnologyImmunologyBiochemistryGeneGenetics

Abstract

fetched live from OpenAlex

Over the last years, the biopharmaceutical industry has significantly turned its biologics production towards mammalian cell expression systems. The presence of glycosylation machineries within these systems, and the fact that monoclonal antibodies represent today the vast majority of new therapeutic candidates, has largely influenced this new direction. Recombinant glycoproteins, including monoclonal antibodies, have shown different biological properties based on their glycan profiles. Thus, the industry has developed cell engineering strategies not only to improve cell's specific productivity, but also to adapt their glycosylation profiles for increased therapeutic activity. Additionally, the advance of "omics" technologies has recently given rise to new possibilities in improving these expression platforms and will significantly help developing new strategies, in particular for CHO (Chinese Hamster Ovary) cells.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.971
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.346
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