MétaCan
Menu
Back to cohort
Record W3183731058 · doi:10.1111/ijlh.13605

Gene therapy for hemophilia: Current status and laboratory consequences

2021· review· en· W3183731058 on OpenAlexafffund
Paul Batty, David Lillicrap

Bibliographic record

VenueInternational Journal of Laboratory Hematology · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsQueen's University
FundersCanadian Institutes of Health Research
KeywordsGenetic enhancementFactor IXMedicineClinical trialIntensive care medicineGene deliveryViral vectorBioinformaticsGeneInternal medicineBiologyGeneticsRecombinant DNA

Abstract

fetched live from OpenAlex

Since the cloning and characterization of the factor VIII (FVIII) and factor IX genes in the mid-1980s, gene therapy has been perceived as having significant potential for the treatment of severe hemophilia. Now, some 35 years later, these proposals are close to being realized through the licensing of the first clinical gene therapy product. Adeno-associated viral vector-mediated gene therapy for hemophilia A and B has been extensively investigated in preclinical models over the past 20 years, and since 2011, there has been increasing evidence in early phase clinical trials that this therapeutic strategy can provide safe and effective rescue of the hemostatic phenotype in severe hemophilia. As the uptake of hemophilia gene therapy progresses, it is clear that many aspects of the gene therapy process require crucial laboratory support to ensure safe and effective outcomes from his new therapeutic paradigm. These laboratory contributions extend from evaluations of the gene therapy vehicle, assessments of the patient immune status for the vector, and ultimately the performance of assays to determine the hemostatic benefit of the gene therapy and potentially of its long-term safety on the host genome. As with many aspects of past hemophilia care, the safe and effective delivery of gene therapy will require an informed and coordinated contribution from laboratory science.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-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 score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.046
GPT teacher head0.407
Teacher spread0.361 · 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 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

Citations23
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Laboratory HematologySame topicVirus-based gene therapy researchFrench-language works237,207