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Record W2965000423 · doi:10.1093/hmg/ddz157

Advances and challenges for hemophilia gene therapy

2019· review· en· W2965000423 on OpenAlexaff
Paul Batty, David Lillicrap

Bibliographic record

VenueHuman Molecular Genetics · 2019
Typereview
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsQueen's University
FundersBayer
KeywordsBiologyGenetic enhancementGeneticsGeneComputational biologyBioinformatics

Abstract

fetched live from OpenAlex

Hemophilia is an X-linked inherited bleeding disorder, resulting from defects in the F8 (hemophilia A) or F9 (hemophilia B) genes. Persons with hemophilia have bleeding episodes into the soft tissues and joints, which are treated with self-infusion of factor VIII or IX concentrates. Hemophilia provides an attractive target for gene therapy studies, due to the monogenic nature of these disorders and easily measurable endpoints (factor levels and bleed rates). All successful, pre-clinical and clinical studies to date have utilized recombinant adeno-associated viral (AAV) vectors for factor VIII or IX hepatocyte transduction. Recent clinical data have presented normalization of factor levels in some patients with improvements in bleed rate and quality of life. The main toxicity seen within these studies has been early transient elevation in liver enzymes, with variable effect on transgene expression. Although long-term data are awaited, durable expression has been seen within the hemophilia dog model with no late-toxicity or oncogenesis. There are a number of phase III studies currently recruiting; however, there may be some limitations in translating these data to clinical practice, due to inclusion/exclusion criteria. AAV-based gene therapy is one of a number of novel approaches for treatment of hemophilia with other gene therapy (in vivo and ex vivo) and non-replacement therapies progressing through clinical trials. Availability of these high-cost novel therapeutics will require evolution of both clinical and financial healthcare services to allow equitable personalization of care for persons with hemophilia.

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)0.000
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 score0.994
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.217
GPT teacher head0.429
Teacher spread0.212 · 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

Citations105
Published2019
Admission routes1
Has abstractyes

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