Formulary Management of Sodium-Glucose Cotransporter-2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists
Bibliographic record
Abstract
Health Canada has approved 4 sodium-glucose cotransporter-2 (SGLT2) inhibitors (ertugliflozin, dapagliflozin, canagliflozin, and empagliflozin) and 5 glucagon-like peptide-1 (GLP-1) receptor agonists (semaglutide, liraglutide, dulaglutide, lixisenatide, and exenatide), with 5 fixed-dose combination products (SGLT2 inhibitors: dapagliflozin-metformin, canagliflozin-metformin, and empagliflozin-metformin; GLP-1 receptor agonists: liraglutide–insulin degludec and lixisenatide–insulin glargine). Data protection has ended for all SGLT2 inhibitors in Canada as well as their fixed-dose combinations. Eleven dapagliflozin generics are currently available, and there are several canagliflozin and empagliflozin generics under review at Health Canada. Patent protection has not expired for GLP-1 receptor agonists. There is heterogeneity in public drug program reimbursement criteria for each SGLT2 inhibitor and GLP-1 receptor agonist ranging from restricted to unrestricted benefit. This Environmental Scan highlights that as SGLT2 inhibitors and GLP-1 receptor agonists have matured, additional indications (heart failure, chronic kidney disease, weight management) have been added to their initial Health Canada–approved indication (type 2 diabetes mellitus). SGLT2 inhibitors are beginning to lose their exclusivity status and are experiencing generic competition.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".