Responsibles: E. Rozet, Maître en Sciences Pharmaceutiques, ULg - W. Dewé, Collaborateur scientifique, ULg

Objectives:

Analytical method transfer between two laboratories is a complex process requiring critical steps. At the end of this process, demonstration must be made that the transferred analytical method is mastered by the receiving laboratory in comparison to pre-established acceptance criteria. The aim of this training is to elucidate the steps required for an analytical method transfer:

• The methodology to follow in order to make the adequate decision with all guarantees
• A reminder of the basic statistical tools
• The statistical approaches applicable and their pros and cons;

Another crucial step in any analytical method life cycle is the comparison of a candidate analytical method to a so called reference one. The different methodologies to compare analytical methods are reviewed, their conditions of applicability and their inconvenient. Examples will illustrate those different aspects.

 

 

Target audience :

This training is dedicated to employees, responsible or technicians of quality control and analytical laboratories in R&D or production. Any individual implicated in analytical method transfer as well as quality assurance responsible can benefit from this training. The usual physico-chemical methods used in R&D and in production as well as the validation criteria are supposed known by the attendees.

 

Program :

1. Why analytical method transfer?

• Regulatory and scientific requirements,
• Transfer or on site revalidation?
• Objectives of transfer.

2. Basic statistical tools

• Descriptive Statistics: mean, variance, standard-deviation, relative standard deviation,...
• Distribution, confidence interval,
• Hypothesis testing.

3. Statistical approaches for method transfer

• Trueness: The descriptive approach, The difference approach, The equivalence approach,
• Precision: The descriptive approach, The equivalence approach,
• Accuracy of results: approach based on measurement total error,
• Experimental planning (number of series and replicates),
• Critic of the different approaches,
• Examples and simulations.

4. Methods comparison

• The diverse methodologies (Correlation, Bland-Altmann, …)
• Advantages and dis-advantages

5. Study of real cases

• Real cases describing the different statistical approaches reviewed,
• Discussion on the presentation of different scenarios.

 

 

These trainings can be dispatched internally or in your company.

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