Revisiting FDA’s 1995 Guidance on Bioequivalence Establishment of Topical Dermatologic Corticosteroids: New Research Based Recommendations
Bibliographic record
Abstract
PURPOSE: As per the US FDA guidance issued on June 2, 1995, the establishment of bioequivalence for topical dermatologic corticosteroids is based on comparing the pharmacodynamic (PD) effects of Test and Reference products at the dose duration corresponding to the population ED50, determined either by naïve pooled data or nonlinear mixed effect modeling (NLME). The guidance was introduced using a study case example where the expectation maximization (EM) NLME algorithm, as implemented in P-PHARM®, was used. Although EM methods are relatively common, other methods such as the First-Order Conditional Estimation (FOCE) as implemented in the NONMEM® software are even more common. The objective of this study was to investigate the impact of using different parametric population modeling/analysis methods and distribution assumptions on population analysis results. METHODS: The dose duration-response data from 11 distinct skin blanching blinded pilot studies were fitted using FOCE (NONMEM®) and an EM algorithm (ADAPT5® (MLEM)). Three different Emax models were tested for each method. Population PD estimates and associated CV%, and the agreement between model predicted values and observed data were compared between the two methods. The impact of assuming different distributions of PD parameters was also investigated. RESULTS: The simple Emax model, as proposed in the FDA guidance, appeared to best characterize the data compared to more complex alternatives. The MLEM method in general appeared to provide better results than FOCE; lower population PD estimates with less inter-individual variability, and no variance shrinkage issues. The results also favored ln-normal versus normal distribution assumptions. CONCLUSIONS: The population ED50 estimates were influenced by both the type of population modeling methods and the distribution assumptions. We recommend updating the FDA guidance with more specific instructions related to the population approach to be used (EM-like versus FOCE-like methods) and to the normality assumptions that need to be set (ln-normal versus normal distribution).
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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 | 0.113 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".