Canadian prescribers’ attitudes and perceptions about ophthalmic biosimilars
Bibliographic record
Abstract
Introduction: The first biosimilar entered the Canadian market in 2009 and the first ophthalmic biosimilar was approved in 2022. In 2022, the Alliance for Safe Biologic Medicines (ASBM) and the International Federation on Ageing (IFA) asked prescribing ophthalmology physicians in Canada for their views on product identification, prescribing biologicals and biosimilars, and switching. Methods: In October/November 2022, the ASBM conducted a web-based quantitative survey with 41 participants practicing ophthalmology in Canada. Prescribers were asked for their views on several aspects: how products are identified; the influence of the cost of biologicals and biosimilars on prescribing; prescribing biosimilars and switching to biosimilars; pharmacist-level switching to biosimilars, and automatic substitution of biosimilars. Results: The survey reveals information about biological product identification and shows that the ophthalmologists are confident in the Canadian pharmacovigilance system’s ability to accurately identify the specific product that might be responsible for an adverse drug reaction. Most physicians are not influenced by the cost when prescribing biologicals and they are confident prescribing biosimilars and switching patients to biosimilars where appropriate. Overall, 90% of practitioners think they should have the sole authority to decide what biological is dispensed to patients and over 80% are not comfortable with third-party switching for non-medical reasons. The majority of practitioners said that the system that would best serve the patients of their province would be one in which multiple products, including innovator and biosimilars, are reimbursed, biosimilars are encouraged for new patients, and there is no automatic substitution. Conclusion: The survey reveals information about how Canadian ophthalmologists feel about the use of ophthalmic biosimilars, specifically on biological/biosimilar product identification, and prescribing and switching to biosimilars for ocular use.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".