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Training Section - PAT

Dive into the essentials of Process Analytical Technology, mastering Design of Experiments, optimal design strategies, and basic process monitoring. Uncover the world of process simulation, including Kalman Filtering and Digital Twins, to elevate your approach to process development and optimization. Join us in unlocking the potential of PAT for innovation and precision in your endeavors. Let's explore efficiency together!

Objectives

The Process Analytical Technology (PAT) course, focused on Module 4: PAT Overview, aims to provide participants with a comprehensive understanding of key concepts in process analysis and optimization. By the end of this module, participants will be able to:

  • Understand Design of Experiments (DoE):

    • Grasp the fundamentals of Design of Experiments.

    • Recognize the importance of DoE in the process development lifecycle.

  • Optimize Experimental Design:

    • Implement strategies for efficient experimentation.

    • Learn techniques for maximizing the value of collected data.

  • Master Basic Process Monitoring:

    • Identify Critical Process Parameters (CPP) and Critical Quality Attributes (CQA).

    • Understand the relevance of PAT in ensuring regulatory compliance and product quality.

  • Explore Process Simulation:

    • Gain an introduction to process simulation techniques.

    • Understand the principles of Kalman Filtering in the context of process analysis.

    • Explore the concept of Digital Twins and their application in process optimization.

These objectives are designed to guide participants through a structured learning experience, covering fundamental concepts in PAT. 

Course 
Overview

Design of  Experiments

  • Fundamentals of DoE.

  • Importance in process development.

2

Optimal Design

  • Strategies for efficient experimentation.

  • Maximizing data value.

3

Basic Process Monitoring

  • Critical Process Parameters (CPP).

  • Critical Quality Attributes (CQA).

  • Quality by Design (QBD)

4

Process Simulation

  • Introduction to process simulation

  • Kalman Filtering

  • Digital Twins

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