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Record W4405034657 · doi:10.1182/blood-2024-211420

A Therapeutic siRNA Targeting Plasminogen Acts As a Long-Lasting Antifibrinolytic in Nonhuman Primates

2024· article· en· W4405034657 on OpenAlexaff
Amy W. Strilchuk, Lih Jiin Juang, Andrew Winterborn, Lori Harpell, Abbey Pender, Aomei Mo, Fateme Babaha, Christian J. Kastrup, David Lillicrap

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsFibrinolysisAntifibrinolyticHemostasisMedicineFibrinCoagulationTranexamic acidThrombosisPharmacologyAnesthesiaImmunologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

To maintain hemostasis while preventing thrombosis, clot formation must be tightly regulated by the coagulation, anticoagulation, and fibrinolytic systems. Fibrinolysis, the proteolytic process that degrades and clears blood clots from the vasculature, becomes activated both during and after clot formation, opposing the growth of the fibrin clot and ultimately restoring blood flow through vessels. In conditions where coagulation is compromised, the balance between clot formation and degradation is disrupted. When coagulation is weaker, fibrinolysis is more active, and these combined pressures lead to impaired hemostasis. Antifibrinolytic drugs, such as tranexamic acid (TXA), are used on-demand to achieve hemostasis in diverse clinical scenarios, including heavy menstrual bleeding, prehospital trauma, surgical hemorrhage, and bleeding disorders. Suppressing fibrinolysis could also prevent or lessen the chronic recurring bleeding caused by bleeding disorders, but current small molecule antifibrinolytics are cleared too rapidly to maintain stable inhibition. We are investigating the use of small interfering RNA (siRNA) targeting the central fibrinolytic protein, plasminogen, as a long-lasting antifibrinolytic that can restore the balance between coagulation and fibrinolysis to achieve hemostasis in bleeding disorders. Previously, species-specific siRNA targeting plasminogen (siPLG) achieved fibrinolytic suppression in wild-type mice and dogs, performing as well as TXA, without causing any symptoms associated with plasminogen deficiency after months of knockdown. In hemophilia A mice, pre-treatment with siPLG reduced the severity of induced bleeds. In hemophilia A dogs, repeat dosing with siPLG over a 4-month period reduced the frequency of spontaneous bleeding episodes. In this work, we investigate the ability of a human compatible siPLG to knock down plasminogen and suppress fibrinolysis in nonhuman primates. Intravenous administration of siPLG contained in lipid nanoparticles achieved 70% knockdown of circulating plasminogen at doses as low as 0.1 mg siRNA / kg body weight. Knockdown lasted for weeks after administration, and thromboelastometry showed that clots had increased stability during this time. All doses tested (up to 0.3 mg/kg) were well tolerated, with no changes in complete blood count or markers of liver and kidney function. Animals were monitored for adverse effects or symptoms of plasminogen deficiency, and menses were tracked to evaluate the impact of siPLG on menstrual bleeding. TXA is often recommended for people experiencing heavy menstrual bleeding, and is effective irrespective of the underlying cause of bleeding because it restores the balance between coagulation and fibrinolysis. This siRNA strategy is predicted to be effective in the many indications where TXA is used, and has the potential to overcome many of the limitations of current prophylactics for bleeding disorders, such as frequent administration, thrombotic risk, and applicability to those with inhibitory antibodies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.017
GPT teacher head0.277
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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