Influence of Different Populations on Pharmacokinetic Bioequivalence Results: Can We Extrapolate Bioequivalence Results from One Population to Another?
Bibliographic record
Abstract
Purpose: Over the last 15 years, an ever-increasing proportion of pharmacokinetic bioequivalence studies for European/North American generic submissions appeared to have been conducted in geographical/ethnic populations other than those for which the drug is marketed for. The results of pharmacokinetic bioequivalence studies have traditionally been considered to be insensitive to the population studied. However, several recent studies have suggested that this may not necessarily be true. The objective of this study was to investigate whether there were any concerns regarding the current practice of extrapolating bioequivalence study results from one geographic/ethnic population to another. METHODS: In order for a regulatory agency to use bioequivalence results from one population to another, two formulations assessed as bioequivalent under fasted and fed conditions in one population must be bioequivalent in a geographically/ethnically different population under both conditions. Unfortunately, bioequivalence studies between a generic and its reference product for one submission are conducted using only one geographical/ethnic population. As bioequivalence study results between two populations for the same generic and reference products are not available, the food effect for the same reference product between two populations was compared. This is based on the rationale that if two products are bioequivalent under both fasted and fed conditions in two populations, even if there are PK differences in the product exposures between these two populations, the test to reference ratio, as well as the food effect, will remain constant within each population. Food effect (fed/fasted ratio) was calculated using pharmacokinetic data from publicly available regulatory resources and compared between two geographical/ethnic populations using the same reference for each studied drug product. Meta-analyses were conducted. RESULTS: Statistically significant differences (P<0.05) were found in the food effect between two populations for nine out of the ten (90%) available studied products. Among these, an observed clinical difference was suggested in three out of nine (33%) products. CONCLUSION: These results suggest that bioequivalence results from one population may not always be representative of what may be found in another population.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".