The Law and Ethics of Switching from Biologic to Biosimilar in Canada
Bibliographic record
Abstract
Governments and financial institutions in several jurisdictions are planning or implementing nonmedical/'forced' switches by cutting drug coverage for reference biologics and funding only less expensive biosimilars. Switches raise numerous ethical and legal challenges, as the drugs are framed as not being identical and, despite strong evidence for noninferiority of some biosimilars, there is controversy over whether switching can sometimes lead to adverse events. Canadian law generally requires physicians to give precedence to their patients' best interests over social interests such as cost containment. The primacy of patients' interests is also clearly reflected in professional policies and codes of ethics. Moreover, physicians are obligated to disclose everything a reasonable person in the patient's position would want to know when obtaining informed consent for treatment, including addressing not only scientific information but also relevant social controversy about nonmedical switches. Under Canadian law, physicians may be obligated to tell patients about the ability to access unfunded biologics, even if patients lack the resources to obtain them. In sum, while there is no inherent right to funding for reference biologics in Canada, physicians in some circumstances may have a legal obligation as fiduciaries to advocate on behalf of patients to remain on a reference biologic. At a minimum, the controversy surrounding switching will necessitate, as part of the consent process, a robust and thorough disclosure of relevant risks, benefits and reasonable alternatives.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".