Expanding the eligibility criteria for drugs in Canada’s time-limited health technology assessment and temporary drug access processes will further accelerate access to new medicines
Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) and the pan-Canadian Pharmaceutical Alliance (pCPA) have introduced new processes to balance timely patient access with decision-making for drugs showing early promise with high evidence uncertainties. In September 2023, CDA-AMC launched a time-limited reimbursement recommendation (TLR) category aimed at providing earlier access to new treatments for severe, rare, or debilitating illnesses. Concurrently, pCPA developed principles for a Temporary Access Process (pTAP) to guide negotiations for drugs following the TLR pathway. Drug eligibility for TLR and pTAP includes having a Notice of Compliance with Conditions (NOC/c) from Health Canada and a phase III clinical trial completion within three years.As of mid-2024, one drug, epcoritamab for diffuse large B-cell lymphoma, has successfully navigated this new pathway, which significantly accelerated time to listing. Despite this progress, current eligibility criteria may limit the broader impact of TLR and pTAP, as few drugs qualify. Future refinements could include broader eligibility criteria, such as NOC/c expansion to allow for other drug files, incorporating greater flexibility into the Phase III clinical trial requirements, and accepting real-world evidence (RWE) as a supplement to clinical trial data.Overall, the TLR and pTAP pathway represents a significant advancement in Canada’s approach to health technology assessments and drug reimbursement, promising timelier access to innovative treatments. Continued evaluation and adaptation of these processes will be crucial in ensuring their use, and their impact on timely patient access, with the expansion of drug eligibility criteria a logical next iteration.
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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 | 0.051 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".