Usability of mepolizumab single-use prefilled autoinjector for patient self-administration
Bibliographic record
Abstract
Objective: To evaluate usability of mepolizumab as a liquid drug product self-administered via a single-use prefilled autoinjector (AI) by patients with severe eosinophilic asthma (SEA), or their caregivers, in-clinic and at home.Methods: This open-label, single-arm, Phase IIIa study (NCT03099096; GSK ID: 204959) included patients aged ≥12 years with SEA who were either receiving mepolizumab (100 mg subcutaneously [SC]) every 4 weeks (Q4W) for ≥12 weeks before screening or not receiving mepolizumab but met criteria indicative of SEA. Patients/caregivers self-administered mepolizumab (100 mg SC) via an AI Q4W for 12 weeks. The first (Week 0) and third (Week 8) doses were observed in-clinic; the second dose (Week 4) was administered unobserved at home. Primary and secondary endpoints were the proportion of patients who successfully self-administered their third and second doses, respectively (determined by investigator/site staff). Patient experience, mepolizumab trough concentrations, blood eosinophil count (BEC), and safety were also assessed.Results: Of 159 patients/caregivers who self-administered ≥1 dose of mepolizumab, 157 completed the study. Nearly all patients successfully self-administered their third mepolizumab dose in-clinic and second dose at home (≥98% and ≥96%, respectively); this was further confirmed by mepolizumab trough concentrations/BEC. At study end, ≥88% of patients were “very” or “extremely” confident about using the AI correctly. Incidence of on-treatment drug-related adverse events (AEs) was low (3%); no fatal AEs occurred.Conclusions: Patients/caregivers successfully self-administered mepolizumab via the AI both in-clinic and at home; no new safety concerns were identified.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".