Method Validation

To have quality attributes built into the analytical method will require that fundamental quality attributes be applied by the bench-level scientist. This is a paradigm shift that requires the bench-level scientist to have the scientific and technical understanding, product knowledge, process knowledge, and/or risk assessment abilities to appropriately execute the quality functions of analytical method validation.
It will require three things:
[COLOR=“seagreen”][b]-the appropriate training of the bench-level scientist to understand the principles involved with method validation and to be able to validate an analytical method and understand the principles involved with the method validation;

-proper documentation and understanding and interpreting data; and
-cross-functional understanding of the effect of their activities on the product and the customer (the patient).
-It is the responsibility of management to verify that skills gained from the training are implemented in day-to-day performance. [/b][/color]
Cycle of Analytical Methods
The analytical method validation activity is not a one-time study. This is illustrated and summarized in the life cycle of an analytical procedure in Life cycle Diagram JPG. An analytical method will be developed and validated for use to analyze samples during the early development of an active pharmaceutical ingredient or drug product. As drug development progresses from Phase 1 to commercialization, the analytical method will follow a similar progression.

The final method will be validated for its intended use for the market-image drug product and transferred to the quality control laboratory for the launch of the drug product. However, if there are any changes in the manufacturing process that have the potential to change the analytical profile of the drug substance and drug product, this validated method may need to be revalidated to ensure that it is still suitable to analyze the API or drug product for its intended purpose. (For more information, see the related article, “Perspectives on Method Validation,” in this issue.)
The typical process that is followed in an analytical method validation is as follows:

[COLOR=“blue”]1.Planning and deciding on the method validation experiments.
2.Writing and approval of method validation protocol.
3.Execution of the method validation protocol.
4.Analysis of the method validation data.
5.Reporting the analytical method validation.
6.Finalizing the analytical method procedure. [/color]

The method validation experiments should be well planned and laid out to ensure efficient use of time and resources during execution of the method validation. The best way to ensure a well-planned validation study is to write a method validation protocol that will be reviewed and signed by the appropriate person (e.g., laboratory management and quality assurance).

Validation Parameters

The validation parameters that will be evaluated will depend on the type of method to be validated. Analytical methods that are commonly validated can be classified into three main categories: identification, testing for impurities, and assay. Table 1 lists the ICH recommendations for each of these methods.

Execution of the method validation protocol should be carefully planned to optimize the resources and time required to complete the full validation study. For example, in the validation of an assay method, linearity and accuracy may be validated at the same time as both experiments can use the same standard solutions. A normal validation protocol should contain the following minimum contents:

[COLOR=“darkred”]objective of the protocol;
validation parameters that will be evaluated;
acceptance criteria for all the validation parameters evaluated;
details of the experiments to be performed; and
draft analytical procedure. [/color]

The data from the method validation data should be analyzed as the data are obtained and processed to ensure a smooth information flow. If an experimental error is detected, it should be resolved as soon as possible to reduce any impact it may have on later experiments. Analysis of the data includes visual examination of the numerical values of the data and chromatograms followed by statistical treatment of the data if required.

Upon completion of all the experiments, all the data will be compiled into a detailed validation report that will conclude the success or failure of the validation exercise. Depending on the company’s strategy, a summary of the validation data may also be generated. Successful execution of the validation will lead to a final analytical procedure that can be used by the laboratory to support future analytical work for the drug substance or drug product.

The minimal information that should be included in a final analytical procedure is:
Rationale of the analytical procedure and description of the capability of the method. Revision of analytical procedure should include the advantages offered by the new revision.

Proposed analytical procedure. This section should contain a complete description of the analytical procedure in sufficient detail to enable another analytical scientist to replicate it. The write-up should include all important operational parameters and specific instructions, such as preparation of reagents, system suitability tests, precautions, and explicit formulas for calculation of the test results.

[COLOR=“purple”]List of permitted impurities and their levels in an impurity assay.
Validation data. Either a detailed set or summary set of validation data is included.
Revision history.
Signature of author, reviewer, management, and quality assurance.

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