The Turkish Medicines and Medical Devices Agency: Comparison of Its Registration Process with Australia, Canada, Saudi Arabia, and Singapore
Bibliographic record
Abstract
Introduction: Regulatory agency comparisons can be of more value and facilitate improvements if conducted among countries with common challenges and similar health agency characteristics. A study was conducted to compare the registration review model used by the Turkish Medicines and Medical Devices Agency (Türkiye İlaç ve Tıbbi Cihaz Kurumu; TITCK) with those of four similar-sized regulatory agencies to identify areas of strength and those requiring further improvement within the TITCK in relation to the review process as well as to assess the level of adherence to good review practices (GRevP) in order to facilitate the TITCK progress toward agency goals. Methods: A questionnaire was completed and validated by the TITCK to collect data related to agency organizational structure, regulatory review process and decision-making practices. Similar questionnaires were completed and validated by Australia’s Therapeutic Goods Administration (TGA), Health Canada, Singapore’s Health Science Authority (HSA), and the Saudi Arabia Food and Drug Administration (SFDA). Results: The TITCK performs a full review for all new active substance (NAS) applications. Submission of a Certificate of Pharmaceutical product (CPP) with an application is not required; however, evidence of approval in another country is required for final authorization by the TITCK. Pricing data are not required by the TITCK at the time of submission; however, pricing must be completed to enable products to be commercially available. Mean approval times at the TITCK exceeded the agency’s overall target time suggesting room for improved performance, consistency, and process predictability. Measures of GRevP are in place, but the implementation by the TITCK is not currently formalized. Discussion: Comparisons made through this study enabled recommendations to the TITCK that include streamlining the good manufacturing practice (GMP) process by sharing GMP inspection outcomes and certificates issued by other authorities, thus avoiding the delays by the current process; removing the requirement for prior approval or CPP; introducing shared or joint reviews with other similar regulatory authorities; formally implementing and monitoring GRevP; defining target timing for each review milestone; redefining the pricing process; and improving transparency by developing publicly available summaries for the basis of approval.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".