Dissolution profile comparision-Pharmaceutical industry

[ParsaKarthik]

Hi Please include the options for the calculation of the following for dissolution profile comparison(requirement of  regulatory agencies)

a. F2

b. boot strap F2

c.Multivariate model dependent

d. Multivariate model independent 

This should help the people in pharma domain to use JMP more effectively.

[Byron_JMP]

Yes! this would be great.

Would you mind posting some links to this thread.

-a link to the Guidance for Industry

-a link to one of the FDA talk slide decks where the basic concepts are explained

[RicardoCosta]

Hi,

Please consider the formulas reported on page 8 of the following oficial guidance document.

https://www.fda.gov/media/70936/download

and scientific paper: https://link.springer.com/article/10.1023/A:1011976615750

There is a lot of scientific paper on this subject.

[Sridevi]

This is a very good feature and will be very useful to the pharma community if it is implemented in a user friendly format in JMP

[Audrey_Shull]

Hi everyone - for those who are interested, we're pleased to let you know that this feature will be available in the next major release of JMP (JMP 17) which will be available in October. 

[Byron_JMP]

That's awesome!! Thank you for the good news.

[RicardoCosta]

Great news. This is a significant upgrade for all involved in Pharma product research and development.

Looking forward to JMP 17.

[k_sateesh]

Hello @Sarah-Sylvestre, I am trying to boot strap F2 for my data using JMP17. I could not find much help on JMP on how to use this functionality. Do you have any detailed video or white paper on how to use this functionality? Thankyou, Sateesh

[SamGardner]

In JMP 17.2, when you run the Model Free F2 comparison, by default the boostrap results are displayed at the bottom of the analysis report

The mean bootstrapped F2 is displayed also. If you want to use the bootstrap results directly, you can right click the Table in the Bootstrap Results and save that to a data table.  One way to use the bootstrapped results is the look at the percentile of those results to determine bootstrap confidence limits for the estimated F2.  

In JMP 18.0, which is planned to be released soon, there is a red triangle command to save the bootstrap results for all the comparisons that is better designed to all for creation of the bootstrap confidence intervals

JMP 18.0 example bootstrap F2 results analysis