Statistical Elements of Implementing ICH Quality Guidelines

This 2-day seminar explores the unique challenges facing quality functions of pharmaceutical and biotechnology companies. Attendees will learn practical implementation solutions as well as best practice descriptions that will allow management to effectively assess, manage and mitigate risk of poorly designed studies. Participants will learn statistical methods related to ICH guidelines and will discover how regulatory agencies, such as the FDA expect organizations to meet these guidelines.

This seminar will provide attendees with an understanding of the fourteen ICH Quality guidelines as relates to statistical guidance and analysis. The course will provide tools, techniques and insight that will allow participants to immediately begin implementation of the information learned within their organization/firm

Learning objectives:

Upon completion of the course, you will be able to:

• Compare FDA requirements to ICH guidelines.
• Perform comparative analyses and regression analysis.
• Know the difference between confidence and tolerance intervals.
• Calculate the appropriate sample size.
• Calculate the probability of risk.
• Design and perform statistical tests for comparisons, stability, validation, impurities

Areas covered:

Day 1: ICH review and Statistics Fundamentals

1. Review ICH Quality Guidelines (Q Series)
• Q1 Stability Testing
• Q2 Analytical Validation
• Q3A-3E Impurities
• Q4 Pharmacopoeias
• Q5A-5E Quality of Biotechnological Products
• Q6A-6B Specifications
• Q7 Good Manufacturing Practice
• Q8 Pharmaceutical Development
• Q9 Quality Risk Management
• Q10 Pharmaceutical Quality System
• Q11 Development and Manufacture of Drug Substances
• Q12 Lifecycle Management
• Q13 Continuous Manufacturing of Drug Substances and Drub Products
• Q14 Analytical Procedure Development
• Developing a Quality Risk Management Plan
2. Fundamentals of Statistics
• Normal Distribution
• Descriptive and Summary Statistics
• Graphical Techniques
• Null Hypothesis Statistical Testing
• Confidence and Tolerance Intervals
• Statistical vs. Meaningful Significance

Day 2: Statistical Tests and Applications to Industry

1. Statistical Analyses
• Comparative Statistics
• Regression Analysis
• Sample Size (Power Analysis)
• Discussion/Questions
2. Application to Industry
• Design of Experiments (DOE)
• Setting Specifications/Thresholds/Acceptance Criteria
• Stability/Shelf-Life Testing
• Assay Validation
• Impurities
• Discussion/Questions

Who will Benefit:

• Quality Managers
• Analytical Validation scientists and personnel
• Assay Development Scientists
• Quality Control Personnel
• Quality Analysts
• Research Scientists
• Risk Managers