We are pleased to announce a new course on equivalence/comparability. The course will be restricted to the first 15 paying customers.
Please contact email@example.com if you would like to register for the course.
Course Title: Demonstration of Comparability for Chemistry, Manufacturing, and Controls (CMC) in the Pharmaceutical Industry
Date: Wednesday August 25, 2021
Time: 12:00 – 4:00 (Eastern)/9:00 – 1:00 (Pacific)
Instructor: Rick Burdick (biography included below)
Software: JMP® software
The FDA comparability guidance (1996) recognizes the need for manufacturers to improve manufacturing processes and analytical procedures without performing additional clinical studies to demonstrate product safety and efficacy. This guidance was extended in ICH Q5E (2004) to provide additional direction for comparing pre- and post-change manufacturing processes.
Across the regulatory documents, there are only high-level recommendations for the design of an equivalence/comparability study and for setting acceptance criteria to assess the impact of the change. These documents do not generally contain prescriptive rules for setting acceptance criteria, study design, or statistical procedures for analysis. One notable exception is the draft guidance published by FDA (2019) concerning demonstration of analytical similarity. EMA also produced a report based on comments offered on a reflection paper concerning analytical comparability and similarity (2018). This course presents statistical approaches for demonstrating comparability consistent with these regulatory guidelines. In addition, this course provides JMP scripts for power and sample size determinations as well as appropriate constants for intervals used to calculate quality ranges.
The course includes:
- Explanation of differences between statistical methods used for demonstrating comparability and when each is appropriate.
- A list of considerations for selecting an appropriate method.
- An approach for setting comparability criteria.
- A method to determine reasonable sample sizes.
Examples discussed in the course include: qualification of reference standards, comparison of manufacturing sites, partitioning of variation in gene and cell therapies, analytical bridging studies, tech and analytical transfer, scale-down model (SDM) qualification, and analytical similarity of biosimilars.
Methods discussed in the course include: side-by-side plots, statistical equivalence tests for means (TOST), non-inferiority of standard deviations, and quality ranges (min-max intervals, tolerance intervals, 3-sigma intervals, and risk-based side-by-side intervals).
Instructor: Richard (Rick) K. Burdick is an Emeritus Professor of Statistics, Arizona State University (ASU) and former Quality Engineering Director for Amgen, Inc. for 10 years. He taught at ASU for 29 years at all levels including undergraduate business students, MBAs, Master of Statistics students, and doctoral candidates in both business and engineering. He received numerous teaching awards and taught a variety of courses for adult learners. His research and consulting interests consider several CMC statistical applications including comparability studies, stability data analysis, analytical method validation, quality by design process characterization, and analytical similarity for biosimilar products. He has written over 60 journal articles and three books, including Confidence Intervals for Random and Mixed ANOVA Models with Applications to Gauge R&R Studies, (with C. M. Borror and D. C. Montgomery) and Confidence Intervals on Variance Components, (with F. A. Graybill). Burdick is a Fellow of the American Statistical Association and a member of the American Society for Quality. He has served on the USP Statistics Expert Committee since 2010. He received his Bachelor’s Degree in Statistics from the University of Wyoming. He received his Masters and Doctorate degrees in Statistics from Texas A&M University.