Human gene editing: revisiting Canadian policy
Bibliographic record
Abstract
Driven by the rapid evolution of gene editing technologies, international policy is examining which regulatory models can address the ensuing scientific, socio-ethical and legal challenges for regenerative and personalised medicine. 1 Emerging gene editing technologies, including the CRISPR/Cas9 2015 scientific breakthrough, 2 are powerful, relatively inexpensive, accurate, and broadly accessible research tools. 3 Moreover, they are being utilised throughout the world in a wide range of research initiatives with a clear eye on potential clinical applications. Considering the implications of human gene editing for selection, modification and enhancement, it is time to re-examine policy in Canada relevant to these important advances in the history of medicine and science, and the legislative and regulatory frameworks that govern them. Given the potential human reproductive applications of these technologies, careful consideration of these possibilities, as well as ethical and regulatory scrutiny must be a priority. 4 With the advent of human embryonic stem cell research in 1978, the birth of Dolly (the cloned sheep) in 1996 and the Raelian cloning hoax in 2003, the environment surrounding the enactment of Canada’s 2004 Assisted Human Reproduction Act (AHRA) was the result of a decade of polarised debate, 5 fuelled by dystopian and utopian visions for future applications. Rightly or not, this led to the AHRA prohibition on a wide range of activities, including the creation of embryos (s. 5(1)(b)) or chimeras (s. 5(1)(i)) for research and in vitro and in vivo germ line alterations (s. 5(1)(f)). Sanctions range from a fine (up to $500,000) to imprisonment (up to 10 years) (s. 60 AHRA). In Canada, the criminal ban on gene editing appears clear, the Act states that “No person shall knowingly […] alter the genome of a cell of a human being or in vitro embryo such that the alteration is capable of being transmitted to descendants;” (s. 5(1)(f) AHRA). This approach is not shared worldwide as other countries such as the United Kingdom, take a more regulatory approach to gene editing research. 1 Indeed, as noted by the Law Reform Commission of Canada in 1982, criminal law should be ‘an instrument of last resort’ used solely for “conduct which is culpable, seriously harmful, and generally conceived of as deserving of punishment”. 6 A criminal ban is a suboptimal policy tool for science as it is inflexible, stifles public debate, and hinders responsiveness to the evolving nature of science and societal attitudes. 7 In contrast, a moratorium such as the self-imposed research moratorium on human germ line editing called for by scientists in December 2015 8 can at least allow for a time limited pause. But like bans, they may offer the illusion of finality and safety while halting research required to move forward and validate innovation. On October 1 st , 2016, Health Canada issued a Notice of Intent to develop regulations under the AHRA but this effort is limited to safety and payment issues (i.e. gamete donation). Today, there is a need for Canada to revisit the laws and policies that address the ethical, legal and social implications of human gene editing. The goal of such a critical move in Canada’s scientific and legal history would be a discussion of the right of Canadians to benefit from the advancement of science and its applications as promulgated in article 27 of the Universal Declaration of Human Rights 9 and article 15(b) of the International Covenant on Economic, Social and Cultural Rights, 10 which Canada has signed and ratified. Such an approach would further ensure the freedom of scientific endeavour both as a principle of a liberal democracy and as a social good, while allowing Canada to be engaged with the international scientific community.
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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 | 0.030 | 0.075 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.075 | 0.062 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".