Initiative to streamline clinical trials (ISCT): Guidance for academic investigators/sponsors.
Bibliographic record
Abstract
219 Background: The 2011 Canadian Cancer Research Alliance (CCRA) report on the State of Cancer Clinical Trials in Canada outlined in detail the threats to the conduct of academic oncology clinical trials caused by increasing complexity and workload resulting from a perceived onerous regulatory environment. The report recommended engaging Health Canada and key stakeholders to foster agreement in appropriate interpretations of the Canadian Food and Drug Regulations Part C Division 5 and ICH Good Clinical Practice (GCP) guidelines. Methods: The ISCT Working Group (ISCT WG) was formed in 2012 to address the CCRA recommendations for academic clinical trials and include experts from multiple therapeutic areas. The primary objective of the ISCT is to develop specific, practical interpretations of current regulations, laws and guidelines to facilitate Canadian clinical trials. Feedback was obtained from interested parties and ISCT members by means of surveys, face-to-face meetings and conference calls. Results: The major areas of concern identified include Health Canada Clinical Trial Applications, Investigational Product supply, monitoring, oversight of equipment and facilities, delegation of duties, validation of electronic systems, source documents and records retention, trial costs, the consistency of interpretation by different divisions of Health Canada, and access to related resources. A subcommittee was established for each area identified above and a series of recommendations to streamline processes with a focus to reduce regulatory burden for academic clinical trials. The ISCT WG used other relevant documents including the OECD framework and FDA Guidance on Risk Based Monitoring to inform its work. Conclusions: The final recommendations of the ISCT have been provided to all stakeholders, presented at international conferences and published on the N2 website. Canadian academic sites have used guidelines during Health Canada inspections with success. Future goals include an ISCT Workshop for academic site leaders to facilitate implementation of the ISCT guidelines, continue to address areas of concern, and track the success of the recommendations in ameliorating the conduct of academic trials.
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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 | 0.347 | 0.361 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.006 | 0.011 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.021 | 0.014 |
| Open science | 0.013 | 0.014 |
| Research integrity | 0.028 | 0.023 |
| Insufficient payload (model declined to judge) | 0.036 | 0.049 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".