Regulatory requirements for the registration of generic medicines and format of drug dossiers: procedures in Sri Lanka in comparison with selected regulatory authorities
Bibliographic record
Abstract
BACKGROUND: The regulatory requirements for approval of generic medicines and the format of compiling drug dossiers vary among regulatory authorities. The variation is particularly wide between High-income countries (HIC) and lower and middle-income countries (LMIC) with different regulatory frameworks. In this study, document requirements for approval of generic products, approval timelines, and consideration of bioequivalence and/or biowaiver data by Regulatory Authorities (RAs) of 10 selected jurisdictions was studied. METHODS: The guidelines and procedures from 5 purposively chosen RA of HIC and4 regional RAs relevant for Sri Lanka were compared with the Sri Lankan National Medicines Regulatory Authority (NMRA). Information available in the official websites of the selected RAs, published journal articles and via personal communication was collected in2016. Drug approval timelines achieved in Sri Lanka was obtained from data available from another study. RESULTS: Common technical dossier (CTD) format of the International Council on Harmonization (ICH) for registration of pharmaceuticals (ICH:CTD) or the Association of South East Asian Nations (ASEAN) CTD format (ACTD) was used by all RAs studied except Sri Lanka which use its own dossier format. Nine out of ten RAs studied request BE data or justification for not submitting BE data for generic medicines. Sri Lanka requested BE studies only for antimicrobials, antiepileptic drugs and narrow therapeutic index drugs. Biowaivers are allowed for Biopharmaceutics Classification System (BCS)-based Class 1drugs in Singapore and India. USA, EMA, Canada and South Korea allowed biowaiver for BCS Class1and Class 3drugs but Sri Lanka does not accept BW at present. Nine NMRAs out of the ten studied reported legislated timelines for approval of generic pharmaceuticals except Sri Lanka. CONCLUSIONS: Streamlining the drug regulatory systems in LMIC such as Sri Lanka with that of HIC would facilitate an effective drug regulatory system based on reliance on decisions made by stringent regulatory authorities. Findings of this study encourage Sri Lanka to adopt a CTD format for regulatory submission of drug dossiers. Expanding the BE requirement drug list and accepting BCS-based biowaivers for BSC class 1 and 3 drugs during registration of generic drugs when it is scientifically justified is also recommended for Sri Lanka.
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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 | 0.047 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".