P-102 The Regulatory and Legal Complexity of the Multicentre, Multinational Clinical Trial with TP05
Bibliographic record
Abstract
The evidence provided by multinational clinical trials is of outstanding importance for new drugs, new medical devices and new procedures. Large multinational randomised clinical trials are under a financial and organizational threat because of the burden of complex regulations imposed by governments and authorities. The burden is affecting administration, costs and timing. The “overbureaucracy” is justified by protection of data integrity and by protection of the safety of patients. In most of the cases, it is only possible for the industry to manage these trials with the help of CROs (contract research organization). Some authors speak of “mountains of red tape” or “stifled innovation” and “mountains of paperwork” when addressing clinical trial bureaucracy. A quantitative review the paperwork of a major multinational, multicenter clinical trial has to our knowledge not yet been performed. All agreements, contracts and permits necessary for the clinical trial “TP05 for the Treatment of Mild to Moderate Active UC (Precision-UC)” with the Clinicaltrials.gov Identifier: NCT01903252 were analyzed. The number of countries originally approached was 34, covering all continents, with 22 countries in Europe and North America finally participating. The planned number of patients is 800. There are around 180 investigators participating. We looked at investigators, CROs, free-lancers, hospitals, pharmacies, patients, governments, regulatory agencies, IRBs, transport and logistics companies, manufacturer and others. If identified as a legal or regulatory requirement, any legal document or permit became a counting unit. The statistics are descriptive only. Until end of March 2015 we identified 1789 contracts and agreements between the CRO and the sites (64 were in countries which in the end did not participate), 58 contracts between the CRO and subcontractors, 32 contracts of the sponsor (main one with the CRO), 104 permits issued by authorities and institutions, and 3 agreements with couriers and depots. A multinational, multicenter clinical trial of this size requires around 2000 contracts, agreements and permits with a ratio of 1:10 per investigator and 1:2.5 per patient. This amount can only be handled with dedicated legal and administrative support. This also explains why the industry cannot manage such trials without specialized CROs and it also explains why these kinds of trials almost never can be handled purely by the academic community. To minimize the bureaucratic burden, contracts should be rigorously standardized and IRBs as wells as competent authorities should reciprocally acknowledge votes. Absent such steps, there is not much opportunity for improvement to the status quo.
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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 | 0.129 | 0.356 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.006 |
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".