Wednesday, 11 November 2009

Quality by Design for analytical methods

ANALYTICAL TOPICS

Quality by Design (QbD) is the name given to the principle of fully understanding a process and the effect of the various characteristics which influence the process, rather than just testing the resulting product at the end to check if the process has performed as expected. This concept was adopted by the FDA in 2004 as detailed in ‘Pharmaceutical CGMPs for the 21st century – A Risk Based Approach’ [1] and is included in ICH Q8 'Pharmaceutical Development’ [2] and ICH Q9 ‘Quality Risk Management’ [3].

QbD has been applied to manufacturing processes but can it be applied to analytical methods? When we develop analytical methods we typically select suitable method parameters based on experience and knowledge and then check to ensure that we can achieve the desired results by applying analytical method validation characteristics. Thus we can ensure that the method can quantify at the levels required, that the results are always the same and that they give the true value, etc. This approach does not result in a full understanding of how the parameters of the method can affect the results.

Validation guidelines such as ICH Q2 [4] list the validation characteristics which should be investigated when validating your analytical method. These characteristics include intermediate precision, reproducibility and robustness. These three can provide understanding of the effects of method parameters.

Intermediate precision tests how the method performs when carried out by different analysts, on different analytical systems, on different days, etc. Reproducibility is required when the method needs to transferred to another laboratory and adds to the previous variables investigated for intermediate precision that of carrying out the method in a different laboratory. Robustness testing investigates the effect of slight changes to the method parameters. For example, in a HPLC method the effect of the flow rate, buffer strength and composition of the mobile phase might be investigated.

If performed thoroughly and correctly, the combination of these three validation characteristics can provide a good understanding of how a method performs and yet often this is not the case. Why?

One of the problems is that these characteristics are usually investigated at the end of a validation study due to the effort involved; they are time consuming, require different analysts, systems etc and thus are expensive to perform. For this reason they may only ever be investigated for projects which are in a late stage of development and even then often only the bare minimum of testing is performed. Also, there is a tendency to treat validation studies as a ‘tick-list’ exercise. It is regarded as a separate task which may even be performed by a different set of operators to those routinely using the method, thus valuable knowledge and experience is not gathered together. Another issue is the statistical knowledge required to interpret the results, particularly relating to robustness studies which are best performed using multivariate analysis techniques, such as design of experiments (DoE).

Applying QbD would involve moving these studies which provide an understanding of the method to the beginning of the method development process instead of performing them at the end of method validation. This would mean that the method parameters would be chosen on the basis of these experiments and would be within a design space of the method. The use of automation in these experiments would be desirable to reduce the effort involved and analytical chemists would benefit from a good understanding of the necessary statistics.


References:
1
. US Food and Drug Administration, Pharmaceutical CGMPs for the 21st Century – A Risk Based Approach, 2004.
2. The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, Quality Guideline Q8 Pharmaceutical development, 2006.
3. The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, Quality Guideline Q9 Quality Risk Management, 2006.
4. The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use, Quality Guideline Q2(R1) Validation of Analytical procedures: Text and Methodology, 2005.

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