Hello everyone,
I would appreciate your advice on the most appropriate statistical approach for an HPLC equivalence study.
Background
We need to demonstrate equivalence between our current and future HPLC systems. However, two factors are changing simultaneously:
- the HPLC instrument;
- the chromatographic column.
In routine use, these changes will not necessarily be implemented simultaneously, but the study is intended to support the transition to the new configuration.
Configurations Evaluated
- A: Old instrument + old column (current routine configuration)
- B: New instrument + new column (target configuration)
- C: Old instrument + new column (intermediate configuration)
The same samples will be analyzed under all three conditions, so the data will be paired.
Question
Which statistical approach would you recommend to demonstrate equivalence between the systems and, if possible, distinguish the effect of the instrument from the effect of the column?
I am considering several options.
Option 1: Equivalence Testing (TOST)
Option 2: Mixed Model Followed by TOST
For JMP users, have you implemented this approach using the Repeated Structure option, particularly with an Unequal Variances covariance structure? If so, what were the benefits and limitations?
Option 3: Alternative Approach
- Design of Experiments (DOE);
- Any other methodology you have successfully applied in a similar context.
Sample Size Determination
I would also be interested in recommendations regarding sample size calculations for this type of equivalence study
Study Limitation
We do not have the additional configuration:
- D: New instrument + old column
Thank you in advance for your insights, experience, and recommendations.
