Clinical trial registration in India: 12% of drug regulatory trials are not registered, as required by law
Bibliographic record
Abstract
BACKGROUND: Amongst other things, the drug regulator, Central Drugs Standard Control Organization (CDSCO), is responsible for regulating clinical trials that underlie drug approvals in India. Since 2009, CDSCO has mandated that all regulatory clinical trials be registered with the Clinical Trials Registry - India (CTRI). In this study, we aimed to determine whether regulatory trials, for which CDSCO had given permission, were registered with CTRI as required. We also aimed to quantify missing CTRI records, if any. METHODS: This study involved regulatory trials, for which CDSCO permission letters were available. The permission letters, available as portable document format (PDF) files, were analysed to extract trial titles and protocol numbers. These data were then used to search the CTRI database, which was initially downloaded on 19 January 2024 and updated in August 2024, for matching records. The matches were confirmed by cross-referencing titles and protocol numbers, ignoring protocol version variations. RESULTS: Of the 381 trials examined, 335 (88%) had corresponding CTRI records, whereas 46 (12%) did not. CONCLUSIONS: This study highlights that not all regulatory trials approved by CDSCO are registered with CTRI, despite legal requirements. The absence of a significant number of trials from CTRI raises concerns about transparency in the clinical trial enterprise in India. To improve trust and regulatory compliance, it is essential to establish explicit linkages between CDSCO and CTRI records to avoid the challenges of identifying matches. This study contributes to ongoing efforts to increase transparency and accountability in clinical trial registration in India.
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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 | 0.093 | 0.182 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.018 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".