Use of priority and provisional approval pathways by the Australian Therapeutic Goods Administration in approving new medicines: a cross-sectional study
Bibliographic record
Abstract
Objective Examine the use of priority and provisional approval pathways by the Australian Therapeutic Goods Administration (TGA) for evaluating new medicines. Methods This observational study assessed all new medicines approved by the TGA between 1 January 2018 and 18 October 2021. It examined how frequently priority and provisional approval pathways are being used, the conditions which the medicines are being approved to treat, how long medicines are spending in the approval pathways, the additional therapeutic value of the medicines being approved through these pathways and how the use of the pathways compares with similar regulatory pathways used by Health Canada. Results The TGA approved 138 new medicines in the time period under study, of which 33 were approved through either the priority or provisional approval pathways. Sixteen were approved to treat cancer. It took the TGA a mean of 130 (95% CI 118, 143) and 144 (95% 101, 188) working days for priority and provisional pathways, respectively. Therapeutic evaluations were available for 16 of these medicines and 11 offered little to no therapeutic gain over existing medicines. There was moderate agreement between the TGA and Health Canada in their use of these pathways (Kappa = 0.5458, 95% CI 0.3900, 0.7016). Conclusions The priority and provisional approval pathways are now being used by the TGA for about one-third of all new medicine approvals. Although the medicines approved in these ways are moving through the review process more quickly than those approved through the standard approval pathway, the majority of these medicines, for which an evaluation of therapeutic value is available, do not offer any substantial additional therapeutic value over existing medicines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".