Chair: Yi Tsong, PhD (FDA, CDER)
Co-Chair: Victoria Chang, PhD (JBS | BeiGene)
Speaker: Meiyu Shen, PhD (FDA, CDER)
Title: Statistical Methods of Cut Point Determination in Immunogenicity Studies
Abstract: Currently, screening cut point (CP) calculated from an assay validation with replicates are applied to an immunogenicity study with non-replicates, for which the ADA rate is determined. IID treats the replicate of a sample as coming from another independent sample. AVE uses average results from each sample across runs but inter-assay variability is reduced. Therefore, we propose a random effect model (REM) for calculating CP. Method: We investigate impact of non-compatibility design between validation and immunogenicity studies on CP and compare these methods. Conclusion: IID may not fit for use when replicates’ variability dominates all sources of uncertainty. REM considers covariance structure of repeated measurements. CP by REM is smaller than that by IID but larger than that by AVE.
Speaker: Elena Rantou, PhD (FDA, CDER)
Title: A Model-Based Approach for BE Assessment with In Vitro Permeation Test (IVPT) Data
Abstract: Bioequivalence (BE) has been the key field of research for approval of generic drugs by the US Food and Drug Administration (FDA) It is defined as the absence of a significant difference in the rate and extent to which the active ingredient or active moiety in pharmaceutical equivalents or pharmaceutical alternatives becomes available at the site of drug action when administered at the same molar dose under similar conditions in an appropriately designed study. For topical, dermatological products, the In Vitro Permeation Test (IVPT) provides an accurate and cost-effective path. To assess BE for such products, we need to compare the average bioavailability between the generic formulation and the reference listed drug (RLD).
Since the introduction, by the FDA (2016), of the new statistical methodology for BE assessment in IVPT data, various advances have been made. Such advances allow for an unbalanced data set and the characterization/identification of outliers and their impact on BE assessment. Furthermore, an adaptive design that combines the group sequential design with sample size re-estimation is shown to be advantageous in helping decide earlier with fewer subjects while controlling the impact of the familywise error rate. Lastly, a model-based approach expands the IVPT BE assessment method with the adaptation of a mixed effects model that accounts for both the skin donors and their corresponding replicate skin sections. Different versions of such a model are explored based on different data structure scenarios. One such scenario is whether there is donor-by-treatment interaction. The performance of such models is compared to that of the guidance-introduced approach for assessing BE.
Speaker: Yi Tsong, PhD (FDA, CDER)
Title: Papallelism Testing for Bioassay Curves
Abstract: FDA CDER and CBER CMC statistical reviewers jointly reviewed the methods proposed for parallelism testing methods for bioassay data. Parallelism is a prerequisite assumption that the test product behaves like a dilution or concentration of the reference product. It is the basis for defining the relative potency of a test product to the reference standard. Once the parallelism between test and reference curves is established, the relative potency will be constant at any effective response levels. A review is carried out on most of the proposals of parallelism testing via equivalence and similarity testing approaches. The pro and con of each reviewed proposal with equivalence limit determination will be discussed. The group is also proposing an alternative approach for testing parallelism.
(Based on collaborated work of CDER and CBER CMC Statistical Reviewer Working Group of bioassay data analysis.)
