Prior to utilizing assays for release and stability of clinical material, it is required per regulatory expectation and necessary for good scientific practice to establish quality control parameters and the corresponding acceptance criteria. Early in assay development, we often lack a large dataset to establish these criteria by. This is especially true for lower throughput, high variability assays such as bioassays. A bootstrap (random sampling with replacement) based method may be used to establish appropriate acceptance criteria with limited data. In this talk we will evaluate the performance and implementation of such a method. Examples based on real assay data will be presented.