topic Re: How can I identify an optimal stabilizer combination from a complex formulation stability study in Discussions

How can I identify an optimal stabilizer combination from a complex formulation stability study

BHjmp0603 — Tue, 08 Sep 2026 06:26:51 GMT

Dear All,

I am looking for advice on the appropriate statistical approach in JMP to evaluate a formulation screening/stability study.

I have developed several formulations of an API solution containing different combinations of stabilizing components (A, B, C, D, E). The formulations have been filled into two different container types, so I would like to evaluate both the effect of the stabilizing components and the potential interaction with the container.

I currently have 2 months of stability data (t0, t1 m, t 2 m).

The main objective is to determine, statistically, which stabilizing component or combination of components provides the best API stability, and whether the performance depends on the container.

I would appreciate advice on how to structure and analyze the data in JMP, particularly regarding:

How to define the stabilizing components as factors (including the presence/absence of each component and combinations).
How to include container type as an additional factor.
Whether the appropriate approach would be a factorial/DOE model, linear mixed model, ANOVA/GLM, or another approach.
How to assess main effects and interactions, especially stabilizer × stabilizer and stabilizer × container interactions.
How best to incorporate the 2-month stability measurements (e.g., initial vs. 1- and 2-month data) into the model.
Which JMP platform/procedure would be most appropriate.
How to determine statistically whether one formulation is superior to the others rather than simply comparing individual means.
How to use the model to identify the best stabilizer or stabilizer combination, considering the stability responses simultaneously if several analytical attributes are being measured.

The stability responses include assay/API content and degradation products.

My primary goal is not simply to demonstrate statistical differences, but to use the available data to identify the most promising stabilizer combination for further formulation development.

Re: How can I identify an optimal stabilizer combination from a complex formulation stability study

MRB3855 — Tue, 08 Sep 2026 12:54:29 GMT

Hi @BHjmp0603 and welcome to the conversation. You've asked a lot of detailed questions...that there may be little hope of adequately answering via a forum such as this. I assume you are familiar with ICH Q1E and how the ANCOVA model is applied therein? If so, this reference may be worth a read to get a general idea of how to extend that approach when there are multiple factors.

https://www.researchgate.net/publication/10611962_Ancova_Approach_For_Shelf_Life_Analysis_Of_Stability_Study_Of_Multiple_Factor_Designs

Update: Within JMP, the Fit Model platform will be your go-to for this:

https://www.jmp.com/support/help/en/19.1/index.shtml#page/jmp/launch-the-fit-model-platform.shtml

Re: How can I identify an optimal stabilizer combination from a complex formulation stability study

DonMcCormack — Tue, 08 Sep 2026 13:24:11 GMT

Hi @BHjmp0603,

There are many ways to approach this problem. I'd start by taking a look at these two references and deciding on what works best for you. If you have questions about how to set up a particular analysis in JMP, feel free to ask.

Chow, Shein-Chung. Chapter 9, Stability Analysis with Multiple Components. From Statistical Design and Analysis of Stability Studies. Chapman & Hall, 2007-05-30.
Tsong, Y., Chen, W.J., & Chen, C.W. (2003). ANCOVA Approach for Shelf Life Analysis of Stability
Study of Multiple Factor Designs. Journal of Biopharmaceutical Statistics, 13, 3, pp. 375-393