Industry Perceptions and Experiences with the Access Consortium New Active Substance Work-Sharing Initiative (NASWSI): Survey Results and Recommendations
Bibliographic record
Abstract
The Access Consortium New Active Substance Work-Sharing Initiative, or "Access" for simplicity, allows regulatory authorities (RAs) of the Access Consortium countries to jointly review applications for the registration of new active substances or for new indications. Using a survey developed by the pharmaceutical industry trade associations of the five Access Consortium countries-Australia, Canada, Singapore, Switzerland, and the United Kingdom (UK)-this study gathered insights into the perceptions and experiences of the Access pathway held by affiliates of pharmaceutical companies. Understanding industry perceptions of Access is important for the success of the initiative, as participation is voluntary. Findings indicate that affiliates who participated in Access had mostly positive experiences with this pathway; most affiliates were satisfied with their interactions with the Access RAs and appeared willing to continue to participate in the initiative. Affiliates' reasons for not having yet participated in Access included a lack of opportunity to do so and perceived barriers, such as the Access pathway being too complicated to manage. Recommendations to improve Access cover six key areas: ensure predictability, increase guidance and transparency, streamline processes, maintain flexibility, increase harmonization, and advance RA-industry cooperation. This study should facilitate informed discussions among relevant stakeholders on how to improve Access to maximize efficiencies, accelerate approvals, and improve patient access to innovative medicines.
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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 | 0.013 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".