Multivariate Testing of the Similarity of Dissolution Curves (EU2018 104)Level: Beginner
Piet Hoogkamer, Principal Analytical Scientist, Abbott Healthcare Products
Dissolution testing of pharmaceutical products is important, as it is a surrogate measure of in-vivo dissolution. In-vivo dissolution may affect the bio-availability, which may affect pharmacokinetics (blood levels) and, as a result, safety and efficacy. In case a change is proposed with respect to the formulation, manufacturing process or manufacturing site, “equivalence” needs to be demonstrated to obtain a bio-waiver. Similarity of curves may be tested using the mathematical f2 metric, where a value between 50 and 100 suggests similarity. The f2 metric will be explained in detail. However, in case the variability is too high (between tested units, within a time point), a multivariate distance-based statistic needs to be used instead. Some options will be shown for model-dependent and model-independent approaches. Use of JMP, both with standard functionality and with a dedicated script, will be illustrated for the Mahalanobis distance.
[video]
JSL Application DevelopmentQuality and ReliabilityVideoRe: Multivariate Testing of the Similarity of Dissolution Curves (EU2018 104)Dear Piet,
I tried running the script for mahalanobis analysis on each of the data sets you uploaded and i get an error after choosing the test and reference at the "select group window. the error says "name unresolved: ycol in access or evaluation of 'ycol', ycol/*###*/".
Am i doing anything wrong or is it a problem with the script?
Thanks,
Eitan
Re: Multivariate Testing of the Similarity of Dissolution Curves (EU2018 104)Hi @Piet_Hoogkamer Thanks!,for knowledge sharing on Dissolution similarity.
