The bioequivalence study design recommendations for immediate-release solid oral dosage forms in the international pharmaceutical regulators programme participating regulators and organisations: differences and commonalities
Bibliographic record
Abstract
Bioequivalence (BE) studies are considered the standard for demonstrating that the performance of a generic drug product in the human body is sufficiently similar to that of its comparator product. The objective of this article is to describe the recommendations from participating Bioequivalence Working Group for Generics (BEWGG) members of the International Pharmaceutical Regulators Programme (IPRP) regarding the conduct and acceptance criteria for BE studies of immediate release solid oral dosage forms. A survey was conducted among BEWGG members regarding their BE recommendations and requirements related to study subjects, study design, sample size, single or multiple dose administration, study conditions (fasting or fed), analyte to be measured, selection of product strength, drug content, handling of endogenous substances, BE acceptance criteria, and additional design aspects. All members prefer conducting single dose cross-over designed studies in healthy subjects with a minimum of 12 subjects and utilizing the parent drug data to assess BE. However, differences emerged among the members when the drug’s pharmacokinetics and pharmacodynamics become more complex, such that the study design (e.g., fasting versus fed conditions) and BE acceptance criteria (e.g., highly variable drugs, narrow therapeutic index drugs) may be affected. The survey results and discussions were shared with the ICH M13 Expert Working Group (EWG) and played an important role in identifying and analyzing gaps during the harmonization process. The draft ICH M13A guideline developed by the M13 EWG was endorsed by ICH on 20 December 2022, under Step 2.
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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 | 0.249 | 0.198 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".