Non-Parametric Dissolution Profile Analysis
Plot of the bootstrap f2 simulation
Dissimilarity factor f1 for dissolution data
Similarity factor f2 for dissolution data
Get points on confidence region bounds by Newton-Raphson search
Hotelling's statistics (for two independent (small) samples)
Similarity limit
Hotelling's statistics (for one (small) sample)
Hotelling's statistics (for two independent (small) samples)
Model-independent multivariate confidence region (MIMCR) procedure
Martinez & Zhao Tolerance Interval Approach
Bootstrap f2
Check point location
Plot of the mztia simulation
Graphical representation of the of MZTIA estimation
Print a summary of the bootstrap f2 simulation
Print a summary of MIMCR estimation
Print a summary of MZTIA estimation
Print a plot of MZTIA estimation
Summary of the bootstrap f2 simulation
Summary of MIMCR estimation
Summary of MZTIA estimation
Similarity of dissolution profiles is assessed using the similarity factor f2 according to the EMA guideline (European Medicines Agency 2010) "On the investigation of bioequivalence". Dissolution profiles are regarded as similar if the f2 value is between 50 and 100. For the applicability of the similarity factor f2, the variability between profiles needs to be within certain limits. Often, this constraint is violated. One possibility in this situation is to resample the measured profiles in order to obtain a bootstrap estimate of f2 (Shah et al. (1998) <doi:10.1023/A:1011976615750>). Other alternatives are the model-independent non-parametric multivariate confidence region (MCR) procedure (Tsong et al. (1996) <doi:10.1177/009286159603000427>) or the T2-test for equivalence procedure (Hoffelder (2016) <https://www.ecv.de/suse_item.php?suseId=Z|pi|8430>). Functions for estimation of f1, f2, bootstrap f2, MCR / T2-test for equivalence procedure are implemented.
Useful links