Responsibles: Ph. Hubert, Professeur, ULg - B. Boulanger, Chargé de cours adjoint, ULg
Objectives:
The robustness is a main quality of any analytical method. Required by regulatory (ICH, FDA, …), scientific and economic necessities, must not only be seen as a criterion to fulfill but must be developed as soon as the development of the analytical method. It is highly critical for any method which has to be validated or transferred.
This training will:
• review the regulatory contexts (ICH, FDA, and European Union),
• identify the analytical method operating parameters to modify,
• use the design of experiments and walk through the appropriate analysis of the results: an experimental investment quickly beneficial by the development of robust analytical methods,
• The verification of the robustness, or of the limitations of a robust method also with the Design of Experiments to combine economy and efficiency.
It is essential to understand the place of the robustness in the whole life cycle of an analytical method.
Target audience :
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This training is dedicated to employees, responsible or technicians of quality control and analytical/bio-analytical laboratories in R&D for pharmaceutical industries or similar industries.
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Individual concerned by the development and the validation of analytical methods.
Program :
1. Introduction
- Why robustness?
- Validation of analytical methods: reminder.
2. Regulatory environment
- Recommendations: ICH, European Union, FDA, ...
3. Robustness: definition
- What is robustness?
- Difference between Robustness and Reproducibility
4. Optimisation of the robustness of methods
- The different type of analytical methods,
- Life cycle of a method,
- General principles of the optimization of robustness,
- Modelization of the main characteristics of a method,
- Identification of the adequate factors for robustness,
- Sources of variations,
- Variability and sensibility to variations of an analytical method during its operating conditions,
- Design of experiments in optimization:
- General principles: responses, levels, factors, selection of the type of design,
- Applications.
5. Verification of robustnessERIFICATION OF ROBUSTNESS
- General principles,
- Choice of experimental limits,
- Choice of important criteria for the robustness,
- Experimental Design for the verification: general principles and applications,
- Determination of the limits of a method.
6. Study of real cases
These trainings can be dispatched internally or in your company.
For more information, please contact us info@arlenda.com or use this form |
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