Recommendations for Regulating the Environmental Risk of Shedding for Gene Therapy and Oncolytic Viruses in Canada
Bibliographic record
Abstract
Canadian academic and industry stakeholders are concerned about the inclusion of “virus-like particles or sub-viral particles” in the definition of New Substances Notification Regulations for organisms (NSNR(O)) which impacts clinical cell and gene therapy and commercialization. The requirement of an independent 120-day Environment and Climate Change Canada (ECCC) review preceding a Health Canada review on quality and environmental concerns places an additional burden on Sponsors submitting clinical trial applications (CTA) and/or New Drug Submissions (NDS). A workshop initiated by CellCAN and BIOTECanada with participants from Environment and Climate Change Canada, Health Canada, the Public Health Agency of Canada and Innovation, Science and Economic Development (Ottawa, March 19, 2018) with invited stakeholders discussed approaches to streamline the environmental review process. The following main recommendations were the focus of the workshop: 1) A regulatory policy to clarify Canadian Environmental Protection Act (CEPA)’s definition of “living organism.”[1] This is currently defined as “a substance that is an animate product of biotechnology.” A regulatory policy could potentially exempt “human cells touched by biotechnology for use in human medicinal products” from this definition to clarify any unintended overreach of CEPA, particularly as it applies to non-genetically modified cell therapies. 2) A guidance document to better interpret NSNR(O) Schedule 1 requirements by CTA/NDS sponsors to satisfy the environmental review process. 3) An amendment at the level of regulations, to the NSNR (O) to create a deferment to postpone environmental assessment of micro-organisms used in the manufacturing during investigational clinical trials (pre-market stage). The regulations would apply at the time of market authorization evaluation and review, when sufficient clinical data on vector shedding has been collected, as part of the investigational clinical trials. 4) Amendment to Schedule 4 of the CEPA to include the Food and Drugs Act and Regulations (FDA/FDR) as an exclusion to the application of CEPA. This would remove the current dual regulation of cell and gene therapies by both CEPA and FDA/FDR. These recommendations and other options were discussed at the workshop. These recommendations if adopted will significantly streamline the current regulatory burden and harmonize environmental assessment requirements with other jurisdictions
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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 | 0.041 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.010 | 0.006 |
| Research integrity | 0.025 | 0.014 |
| Insufficient payload (model declined to judge) | 0.028 | 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".