Gwenola NINON, Staff Scientist, Statistics and Data Analytics, Fujifilm Diosynth Biotechnologies
Manufacturers in the biopharmaceutical industry must often demonstrate that they obtain similar results on different sites when transferring a manufacturing process and, importantly, when scaling processes up or down.
Comparison techniques such as t-tests and ANOVAs are widespread but equivalence testing has also become a standard way to show that two processes behave similarly. When there are just a few parameters, those techniques are easy to apply, but it becomes difficult to see the bigger picture when there is a large number of variables.
The challenge with equivalence testing is that it requires the scientists to provide a value for what they deem an acceptable difference between the groups of data. In addition, many processes change over time so it becomes important to capture whether they behave similarly across the duration of the process.
JMP scripting is a great way to automate the data prep, visualisations, and production of all the plots and comparison tests for those data sets. The JMP multivariate platform is used to get a holistic picture of the process for each time point. We can now use equivalence testing and relate it to the individual variable contributions.
