Gwenola NINON, Staff Scientist, Statistics and Data Analytics, Fujifilm Diosynth Biotechnologies
Working as a manufacturer in the biopharmaceutical industry means we often need to show that we obtain similar results on different sites when transferring a manufacturing process and, notably, when scaling processes up or down. Comparison techniques such as t-tests and ANOVAs are widespread, but equivalence testing has become a standard way to show two processes behave similarly. When we look at a few parameters, those techniques are easy to apply, but when we have large numbers of variables, it becomes difficult to see the bigger picture. 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, and we are interested in capturing 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 multivariate platform in JMP helps create a holistic picture of the process for each time point. We can now use equivalence testing and relate it to the individual variable contributions.
