In vitro assessment and phase I randomized clinical trial of anfibatide a snake venom derived anti-thrombotic agent targeting human platelet GPIbα
Bibliographic record
Abstract
The interaction of platelet GPIbα with von Willebrand factor (VWF) is essential to initiate platelet adhesion and thrombosis, particularly under high shear stress conditions. However, no drug targeting GPIbα has been developed for clinical practice. Here we characterized anfibatide, a GPIbα antagonist purified from snake (Deinagkistrodon acutus) venom, and evaluated its interaction with GPIbα by surface plasmon resonance and in silico modeling. We demonstrated that anfibatide interferds with both VWF and thrombin binding, inhibited ristocetin/botrocetin- and low-dose thrombin-induced human platelet aggregation, and decreased thrombus volume and stability in blood flowing over collagen. In a single-center, randomized, and open-label phase I clinical trial, anfibatide was administered intravenously to 94 healthy volunteers either as a single dose bolus, or a bolus followed by a constant rate infusion of anfibatide for 24 h. Anfibatide inhibited VWF-mediated platelet aggregation without significantly altering bleeding time or coagulation. The inhibitory effects disappeared within 8 h after drug withdrawal. No thrombocytopenia or anti-anfibatide antibodies were detected, and no serious adverse events or allergic reactions were observed during the studies. Therefore, anfibatide was well-tolerated among healthy subjects. Interestingly, anfibatide exhibited pharmacologic effects in vivo at concentrations thousand-fold lower than in vitro, a phenomenon which deserves further investigation.Trial registration: Clinicaltrials.gov NCT01588132.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".