The FDA Group's Nick Capman sits down with pharmaceutical scientist and consultant Gary Ritchie to discuss the intricacies of statistical sampling in biopharmaceuticals.

They explore the limitations of the square root of n plus one sampling method, particularly for small lot sizes, and the advantages of more rigorous statistical approaches.

Discussion points include:

Limitations of Square Root of n + 1: Gary explains why this commonly used method is inadequate for small biopharmaceutical lot sizes, leading to potential risks in sample representativity and patient safety.

Importance of Proper Sampling: Gary highlights the need for statistically valid sampling plans considering lot size, inspection levels, and acceptance quality levels (AQLs) to ensure representative sampling and compliance with regulatory requirements.

Cost and Risk Management: The discussion emphasizes how improper sampling can increase business costs and risk to patients, while proper sampling can offer significant cost savings and better risk management.

Adoption of ANSI Standards: Gary encourages the industry to adopt ANSI standards for sampling, demystifying the complexity of statistical methods and emphasizing their importance for compliance and efficiency.

Practical Implementation: Gary shares insights from his experience, recommending resources and literature for better understanding and applying statistical sampling in the pharmaceutical industry, including Dan O'Leary's paper "Attributes Acceptance Sampling: Understanding How It Works" and Ron Snee's "Solving Statistical Mysteries: What Does the FDA Want?"

Gary Ritchie is a veteran pharmaceutical scientist with nearly 30 years of experience in the life sciences industry. He specializes in statistical sampling, analytical chemistry, and pharmaceutical waters. Gary's expertise spans various areas, including process analytics, quality control, and regulatory affairs. Gary’s held key positions at the United States Pharmacopeia, where he served for five years on expert committees for waters, statistics, and general chapters. His experience as a liaison allowed him to work closely with the FDA, industry leaders, and academia.

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Small Lots, Big Risks: Rethinking Statistical Sampling in Biopharma

The Life Science Rundown