Validation of Chemical Methods for Residue Analysis

Registration is not open for this programme. You can already show your interest.

The practical information on this webpage refers to the 2024 edition.

Target audience

Professionals with a technical background in industry, in governmental, commercial or academic laboratories in the area of food and feed safety residue analysis. At least a BSc or comparable is required in a relevant field. In addition, work experience of at least two years in the field of chemical analysis of residues is required.

Learning outcomes

After successful completion of this programme, you will be able to:

• Explain the meaning of trueness, precision, CCα and CCß
• Determine measurement uncertainty
• Apply all this knowledge in your own validation plan
• Explain the phases to go through for a fit for purpose validation
• Construct and execute a validation plan
• Determine the relevant validation parameters
• Prepare a validation report
• Draw on hands-on experience with the evaluation of the analytical data

Programme

Multiple validation approaches exist (e.g. Commission Implementing Regulation EU 2021/808, SANTE/11312/2021, CODEX CAC/GL 71-2009) and it is often unclear how to implement these and how to come to a practical set-up of experiments. In this course, you will learn the theoretical background on the validation of quantitative confirmatory methods and how to select and execute a cost-effective validation approach based on a practical validation plan. The training will briefly discuss all three approaches and then zoom in on EU2021/808.

All participants in this course are invited to bring their own validation case study to apply all newly gained knowledge to their own laboratory practice. Preconstructed case studies are available in case you can’t bring your own.

In 40 to 60 hours, spread over eight weeks, this course will guide you through the field of validation of chemical methods for residue analysis. The kick-off will take place in week one and will be live online – so virtual, with real-time interaction. Onwards, you will have access to the online learning environment BrightSpace, with learning materials to study in your own time and place. Keep in mind 75% of your time will be self-paced online learning on BrightSpace.

Structured in seven modules, the following topics will be discussed:
1. Introduction to the course
2. Fundamentals - qualitative versus quantitative methods, performance characteristics and measurement uncertainty
3. Design - selecting performance characteristics, minimum requirements, design of experiments
4. Data evaluation – calculations and application
5. Reporting – outcome assessment, validation report
6. Other validation procedures – ongoing method validation, screening method, verification and extension
7. Closure of the course

What to expect learning online?
You will:

• watch knowledge clips and read information
• further extend your comprehension and self-assess by taking small quizzes
• share experiences and questions in a forum with your peers
• define and reflect on your learning goals
• have questions answered during the virtual classrooms
• meet and discuss group assignments during live sessions with your peers
• apply new content on your validation case and daily work
• prepare your own validation report