Cleaning Validation Based on PDEs

Cleaning Validation Based on PDEs

Avoid Critical Risks and Ensure Compliance at Your Pharmaceutical Plant

Are you sure your cleaning processes comply with regulations and protect patient safety?

Cleaning validation is a critical pillar in pharmaceutical manufacturing, ensuring patient safety and regulatory compliance. PDEs (Permitted Daily Exposure) have become the scientific reference for defining safe residual contamination limits, but their correct application requires technical, regulatory, and toxicological understanding.

In this webinar, you will discover how to integrate PDE-based criteria into your cleaning validation strategies, with a practical approach that combines regulation, data analysis, and advanced digital tools.

Why you should attend

• You will learn to use the PDE as a decision-making tool that allows you to avoid critical observations in audits
• To understand the regulatory and scientific framework behind cleaning validation and PDEs and how to apply it in the plant.
• To learn about practical tools and knowledge that impact the efficiency, safety, and compliance of your processes.

Get ready for a practical and participatory webinar, full of tools, formulas, and strategies you can apply immediately in your cleaning validations. We will share cases and examples that will allow you to understand how to correctly calculate and apply PDEs, meet regulatory expectations, and optimize your processes without adding unnecessary complexity.

This session will provide you with clarity, strategies, and resources to integrate scientific, statistical, and digital criteria into your cleaning validations safely and efficiently.

What you will learn

• How to use PDE as an essential part of cleaning validation through the correct selection of worst case and the establishment of adequate acceptance criteria, allowing you to guarantee the safety of manufactured medicines.
• Key regulatory requirements (EMA, ICH Q3, ICH Q9, PIC/S PI 006-3) and how to comply with them effectively.
• How to calculate PDEs from preclinical and clinical data, including formulas, correction factors, and clarification of frequently asked questions.
• Practical stages of cleaning validation, from design to approval.
• Applications of AI and digitalization for prediction, optimization, and intelligent management of the validation process.