Determination of Bioequivalence for Drugs with Narrow Therapeutic Index: Reduction of the Regulatory Burden
Bibliographic record
Abstract
The US Food and Drug Administration (FDA) has recently suggested that the bioequivalence (BE) for products of drugs with narrow therapeutic indices (NTI) be assessed by the approach of reference-scaled average BE (SABE). Subsequently, in December, 2012, the FDA issued draft guidances for the comparison of products of warfarin sodium and of tacrolimus. The guidances expect that 4-period studies be performed, that the results be evaluated by SABE, and that the analysis include also unscaled average BE as well as the comparison of the estimated within-subject variations (sW) of the test and reference drug products. This communication discusses the new guidances and suggests considerations to reduce the regulatory burden. It is demonstrated that SABE could be applied when the within-subject variation of the reference product is not higher than 21.42%. Beyond this variation, the BE limits would remain 80% to 125%, as usual. No further testing by unscaled average BE is needed. It is also suggested that a comparison of the within-subject variations of the two drug products although interesting for both NTI and other drugs, is not essential for the determination of BE. In addition, when the within-subject variabilities are low then their ratio depends mainly on the non-product dependent factors. Moreover, introduction of an additional test would affect the probabilities involved in the primary comparison of the two means. Therefore, the test of comparing variances is not needed and replicate measurements of the test formulation need not be performed. Alternative considerations and approaches, including the use of partial AUC's, are suggested for the determination of BE for NTI drugs.
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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 | 0.116 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".