Method of Estimating the Equivalence of Dissolution Profiles: a Modern View (Review)
Bibliographic record
Abstract
Introduction. One of the purposes of dissolution profile comparison is to establish the equivalence of dissolution profiles of the studied drug and the comparison drug. Text. According to the current regulatory documents, the main tool for quantitative confirmation of equivalence of drug release profiles is the calculation of the similarity factor (f 2). However, it does not consider the form of dissolution profiles, incomplete release of the drug substance, time correlation, and is not susceptible to the «outliers», which leads to false positive results. Special attention should be paid to the dissolution of drugs with high variability, which is not eliminated by either increasing the sample or changing the sampling scheme. If f 2 is not used, it is necessary to use model-dependent and model-independent methods that are statistically correct, and their use is sufficiently justified (difference factor f 1 , Weibull distribution function, comparison of release degrees at different time points (according to the student's t-criterion). However, these models have an empirical nature that calls into question the application of such methods. Multivariate analysis is widely discussed in the literature and can be used to compare the similarity of dissolution with the assumption that the data has a normal distribution. The most common methods for checking similarity of dissolution profiles for highly variable drugs are the Mahalanobis distance test and the bootstrap for f 2. There is a document of EMA about suitability of the Mahalanobis distance as a tool to assess the comparability of drug dissolution profiles and to a larger extent to emphasise the importance of confidence intervals to quantify the uncertainty around the point estimate of the chosen metric. The bootstrap methodology for f 2 does not provide a clear understanding of the application to dissolution profile comparison for incomplete-release drugs, particularly in biorelevant environments. The «T2EQ» function, based on the Mahalanobis distance for highly variable drugs (Hoffelder), gives undefined results in practice. Conclusion. The topic of equivalence of dissolution profiles requires discussion, since it is shown that the convergence factor is outdated and cannot be adequately applied. The use of modern methods does not have a clear regulatory confirmation by the regulatory authority. In the published scientific literature, several statistical methods have been explored and compared for their design and performance. It is necessary to develop a clear plan (decision treeы) for conducting the procedure for equivalence of dissolution profiles, employing a range of statistical methods.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".