Sampling Plans for Verification and Validation, Production Process Validation and Production Control

Overview:

When design flaws go unnoticed until late in production—or when a batch fails inspection with no clear justification—sampling is often at the root of the problem. In highly regulated industries like medical devices and life sciences, the way companies approach sampling can make or break the success of a verification, validation, or production control effort. Yet many professionals still rely on outdated shortcuts or “what we’ve always done,” rather than starting with a solid statistical foundation.

The FDA and other regulatory bodies have significantly stepped up scrutiny in this area. From warning letters to audit findings, there’s been a clear shift: manufacturers must now defend their sampling choices with documented, statistical reasoning. It's no longer enough to say “we tested five units” or “we’ve always used this plan”—inspectors increasingly ask why, and expect a response that ties back to risk, data, and sound methodology.

The pressure isn't just regulatory. Internally, organizations are struggling with conflicting demands—minimize waste, prove compliance, and still meet aggressive production timelines. That tension often leads to under-sampling critical processes or over-sampling low-risk ones, wasting resources and creating gaps in quality assurance. Without a clear, scalable sampling strategy, teams can’t move confidently through design verification or maintain control of day-to-day operations.

This webinar steps in where that uncertainty begins. It focuses on the practical challenges professionals face when creating or applying sampling plans for verification, validation, and production processes. From engineers drafting protocols to quality teams preparing for audits, many struggle to determine when a sampling plan is needed, how much is “enough,” and how to explain that decision to regulators or stakeholders.

Whether you're dealing with complex components, tight tolerances, or increasing FDA oversight, the risks of poor sampling are real—and so is the need to get it right the first time. This session helps attendees step back from the guesswork and focus on clarity, consistency, and confidence in how sampling is handled across the product lifecycle.

Areas covered in the session:

• Basic statistics
• The main parameters that should be considered
• Formulas related to sampling
• Sampling standards

Why Should You Attend?

If you’ve ever found yourself guessing the right sample size, pulling numbers from past protocols, or struggling to explain a sampling decision during an audit, you’re not alone. Many professionals face pressure to move fast while still meeting regulatory expectations—but without a clear, statistically grounded approach, sampling decisions can quickly become a weak point in otherwise strong protocols.

This webinar offers clarity. It’s designed to help you understand the core principles behind sampling plans—why they matter, how regulators view them, and what your documentation should reflect. You’ll walk away better prepared to defend your choices, improve consistency across your protocols, and avoid common pitfalls that trigger compliance concerns.

Most importantly, it will help you reduce uncertainty. Whether you’re drafting a design verification plan or supporting production quality, this session will provide you with a structured way to approach sampling—so you’re not relying on guesswork, assumptions, or outdated templates.

Who Will Benefit?

This webinar is ideal for professionals involved in verification, validation, and production quality processes who need to ensure their sampling plans are statistically sound and audit-ready. Those include:

• Quality Assurance Professionals
• Quality Control Analysts
• Validation Engineers
• Process Engineers
• Manufacturing Engineers
• Regulatory Affairs Specialists
• Design Assurance Engineers
• Compliance Officers
• Production Supervisors
• Documentation Specialists
• R&D Engineers
• Risk Management Personnel
• Technical Project Leads
• Internal Auditors
• Quality System Managers
• Supplier Quality Engineers