Heath Rushing, Principal, Adsurgo
Andrew Karl, Senior Consultant, Adsurgo LLC
Jeff Hofer, Principal, JDH CMC Stats, LLC
Rick Burdick, Principal, Burdick Statistical Consulting, LLC
The most novel, innovative, and promising therapeutics in biopharmaceuticals are cell therapies. Cell therapies transfer human cells into a patient to treat disease. These cells either come directly from the patient or from a healthy (cell) donor. Multiple regulatory guidance documents recognize the importance of providing cell therapy manufacturers the flexibility to improve their processes. Therefore, it is imperative to show that the pre- and post-change processes are comparable and process changes pose no threat to the safety or efficacy of the drug product.
One method used to ensure comparability is an equivalence test of means. There is a regulatory expectation that the study is done as a paired design, often referred to as a split-apheresis study, unless there is minimal donor-to-donor variability. In split-apheresis studies, the same donor material is split and processed in the pre- and post-change process for comparison. The design of this study presents unique challenges in cell therapies as they require adequate sample sizes to ensure properly powered designs, yet the number of healthy donors available is usually quite low (three to six donors). Additionally, the power depends on lot-to-lot and assay variability, assay replication strategy, and the effect size used for the equivalence acceptance criterion (EAC).
This talk presents a series of JMP scripts that extend the existing capabilities of the Sample Size Explorer platform to address each of these relevant study nuances, as well as the capability to overlay power curves to address trade-offs with different sample sizes and approaches.
