Responsibles: Ph. Hubert, Professeur, ULg - B. Boulanger, Chargé de cours adjoint, ULg

Objectives:

In general, the validation is the last step of the development phase of an analytical method before its use in routine analysis.
Based on scientific and regulatory requirements (European Directives, FDA, ICH, ISO,…), the validation should allow to evaluate the performances of the method regarding some parameters called “validation criteria” with the use of appropriate statistical tools.
In introduction, the regulatory documents will be presented, defining the various parts of chemical and pharmaceutical documentation you have to follow. Each criterion of validation will be treated by presenting the methodology and different statistical approaches which can be used for their determination.
In particular, we will examine the new approach based on Accuracy Profile and the total error of measurements. A critical analysis will show why the statistics reject a method which, a priori, seems acceptable or accept a method which does not seem to be acceptable. A brief reminder on the statistics will be carried out with the aim of better evaluating the advantages and the disadvantages of the various methodologies presented. Several practical examples will be studied in order to illustrate this methodology.

 

 

Target audience:

This training is aimed at people involved in the validation of analytical methods, working in physico-chemical analysis laboratories in R&D or Quality Control, and in any pharmaceutical and chemicals industries.

 

 

Program:

1. Basis of the analytical methods validation

• Objectives of an analytical method and its validation
• Regulatory documents (ICH, ISO, FDA, …)
• The validation criteria
• Acceptance criteria of a validation

 

2. Harmonised approach for the validation of analytical methods

• Harmonisation of the criteria
• Total Error concept
• Validation Protocols
• Accuracy Profile: β-expectation tolerance interval and acceptance limits
• Risk Profile

 

3. Discussion on practical cases

• Examples of validation of analytical methods;
• Possibility to discuss and compute examples from laboratories (if data are sent before the training)

 

 

These trainings can be dispatched internally or in your company.

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