A novel injection device to administer repository corticotropin injection for inflammatory disease treatment: findings from a market research study
Bibliographic record
Abstract
Aim: The goal of this market research study was to determine the usability of a single-dose prefilled injector (SelfJect™) for administration of Acthar ® Gel (manufactured by Mallinckrodt Pharmaceuticals, UK) in patients with inflammatory diseases by obtaining feedback from patient and practitioner user groups in the US. Materials & methods: Patients and healthcare professionals (HCPs) representing relevant therapeutic areas were enrolled in the study between February and March 2021. SelfJect was mailed to patients and HCPs prior to 90-min virtual video-recorded focus group sessions and 60-min 1:1 virtual interviews, respectively. Patients completed an online assignment prior to the group session, which included instructions on how to use SelfJect and questions about their initial reaction while handling the device. HCPs were instructed to not open the package until the interview. Feedback from patients and HCPs were captured by open-ended questions and ranking scales. Results: Twelve patients and 42 HCPs participated in the study. Most patients (9/12 [75%]) and HCPs (38/42 [90%]) had experience with injectable medications, and 7/12 (58%) and 30/42 [71%] had experience with Acthar injections, respectively. Most patients and HCPs reported that key benefits of SelfJect were accurate dose delivery and ease of use, including the ergonomic handle and elimination of drawing Acthar from a vial into a syringe. Patients expressed some concerns about storage and disposal, but the need to store SelfJect would not deter them from using it. Most patients (9/12 [75%]) felt prepared to inject Acthar after reviewing the instructions. HCPs anticipated that 75% to 100% of patients would benefit switching from the vial to SelfJect. Conclusion: All participants expressed positive perceptions for SelfJect including easy use, few preparation steps and potential reduced anxiety due to needle phobia. These attributes may help treatment adherence for patients and caregivers.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".