<p>Meeting Regulatory Requirements for Drugs with a Narrow Therapeutic Index: Bioequivalence Studies of Generic Once-Daily Tacrolimus</p>
Bibliographic record
Abstract
Despite growing clinical confidence in generics and their potential to reduce long-term healthcare costs, the transplant community have had real concerns about the use of generic immunosuppressants. One such immunosuppressant is tacrolimus, a cornerstone of lifelong treatment for patients who have undergone a solid organ transplant. Tacrolimus has a narrow therapeutic index (NTI), giving rise to questions about the potential for clinically relevant altered drug exposure. Its use in transplant patients also gives rise to questions about the most discriminative subject population for bioequivalence studies. The recognised need for stringent criteria to support approval of generic drugs with an NTI led the European Medicines Association and Health Canada to provide detailed information on requirements for bioequivalence studies and introduce tighter bioequivalence limits for these drugs, including tacrolimus. The aim of this article is to illustrate how regulatory guidance is implemented during the clinical development of generic immunosuppressants, using a generic, once-daily prolonged-release formulation of tacrolimus as an example.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.068 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".