OP172 Do Expedited Regulatory Pathways Affect Time To Health Technology Assessment Decision?
Bibliographic record
Abstract
Introduction: In an effort to speed the assessment of new medicines while maintaining the quality of the regulatory review, facilitated regulatory pathways (FRPs) have been introduced in many countries. In this study, the effects of FRPs (expedited and conditional reviews) were investigated in terms of their influence on HTA outcomes and timing. Methods: HTA recommendations issued between 2014 and 2016 were collected from CADTH (Canada), HAS (France), IQWIG (Germany), SMC (Scotland) and TLV (Sweden) for 90 internationalized medicines (new active substances approved between 2012 and 2016 by all regulatory agencies in the five jurisdictions). The HTA decisions were then classified into the following categories: positive, positive with restrictions, negative and multiple. Results: Of this cohort of internationalized medicines that received an HTA recommendation, 31 percent in Canada and 28 percent in Europe were approved via a FRP. With the exception of Scotland, expedited medicines were more likely to be appraised within a year from regulatory approval and had a shorter median time between regulatory approval to HTA recommendation than standard medicines. The largest difference was seen in Sweden, where medicines were 66.5 days faster than standard pathways when it underwent the expedited pathways. Compared to standard pathways, there were generally a higher proportion of positive and positive with restrictions recommendations when expedited pathways were used. Germany reported the largest proportional difference (31 percent) between the two pathways. Conclusions: Medicines being designated for an expedited review pathway show a reduced time from regulatory approval to HTA decision. This finding suggests there is an alignment between regulators and HTA agencies on which medicines require expedited HTA pathways; however, from this data it cannot be assessed whether the reduced time from approval to HTA decision is attributed to the company strategy, HTA review time or both. Further investigation is required.
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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 | 0.045 | 0.286 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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.
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".