Demonstration of Comparability for Chemistry, Manufacturing, and Controls (CMC) in the Pharmaceutical Industry (0.5 days)

Demonstration of Comparability for Chemistry, Manufacturing, and Controls (CMC) in the Pharmaceutical Industry (0.5 days): 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 One notable exception is the draft guidance published by FDA (2019) concerning demonstration of analytical similarity.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:

Demonstration of Comparability for CMC in the Pharmaceutical Industry:

• 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).

Outline:

1. Comparability Studies
   • Comparability Basics and Definitions
   • Comparability Tools and Statistical Designs
   • CMC Applications
2. Comparability Tools
   • Considerations in Selecting an Approach
   • Statistical Tests
   • Quality Ranges
   • Comparison of Methods
3. Defining Acceptance Criteria and Power Calculations
   • Power and Statistical Power Calculations
   • Final Recommendations