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Record W1969167989 · doi:10.5339/qfarf.2012.aesnp9

Efficient manufacturing of viral vectors for cancer therapies

2012· article· en· W1969167989 on OpenAlexaff
Amine Kamen

Bibliographic record

VenueQatar Foundation Annual Research Forum Volume 2012 Issue 1 · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsHEK 293 cellsOncolytic virusGenetic enhancementViral vectorTransfectionCell cultureComputational biologyVirusVirologyComputer scienceMedicineBiologyGeneRecombinant DNA

Abstract

fetched live from OpenAlex

HEK-293 cell lines have been widely used for over 35 years by the scientific community. Currently HEK-293 cells are the most efficient system for the improved production of ribosomal proteins and viral vectors by large-scale transfection of suspension-growing cells in serum-free medium. Also, it is the most established cell line for the production of adeno- and adeno-associated viruses, retro- and lentiviruses for gene therapy applications. Additionally HEK-293 cells sustain replication of many viruses that are evaluated as vaccines or viro-therapeutic agents. Consequently numerous viral vectors produced in HEK-293 cells have been approved for phase II and phase III clinical trials. In this presentation, major achievements in process developments completed at NRC to support the large scale manufacturing of viral vectors and vaccines using HEK-293 technology platform will be reviewed. In particular, we will discuss the development of REOLYSIN®, an oncolytic reovirus type 3 Dearing based therapeutic that is currently evaluated in phase III. The REOLYSIN® manufacturing process was scaled-up to a 100 L operation volume to support multicenter clinical evaluation. Advanced online monitoring tools allowed a very precise characterisation of viral infection and production kinetics to demonstrate process robustness, define critical process parameters and establish the process operating space according to the Quality-by-Design guidelines. Through different examples, the presentation will also discuss practises and experiences at NRC in supporting translational research and technology transfer.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.389
Teacher spread0.351 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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