Analytical Validation Strategy: Response (Calibration Model)

Overview:

Validation of analytical procedures, i.e. the demonstration of suitability for the intended purpose is an essential GMP and regulatory requirement. The new revision of the ICH guideline Q2(R2) “Analytical procedure validation” published end of 2023 provides recommendations to address the relevant performance characteristics. Some of the gaps and deficiencies of the old guideline have been addressed, for example the exclusive focus on chromatographic methods, new lifecycle aspects were considered (in combination with the new guideline Q14 “Analytical Procedure Development”), and some new requirements were adopted. However, its degree of detail is rather low, and the examples provided in Annex 2 often lack orientation beyond the guideline text, so that interpretation and orientation for a practically relevant validation design remains important.

Response is required for all (relative) quantitative analytical procedures (assay and impurities).

Why you should Attend:

A rational, efficient, and science-based validation is important to ensure an appropriate performance of analytical procedures as well as to obtain a marketing authorization of a pharmaceutical product. Therefore, a comprehensive understanding of the performance parameters is key. Participants will learn what aspects have changed and what is new in the revised Q2 guideline. A rational and efficient validation approach is ultimately based on the respective routine application, which should be reflected in the validation design as far as possible. 

The webinar will help participants to better understand the challenges, and thus to avoid pitfalls and be prepared for future regulatory expectations, leading to a targeted and efficient demonstration of suitability of the analytical procedure.

Areas Covered in the Session:

• ICH Q2(R2): Range
• Requirements to calibration models
• ICH Q2(R2): Linear response 
• Unweighted linear regression
• Suitable regression parameters
• Appropriate evaluation of the calibration model - residual plot
• Weighted regression for large concentration ranges
• Evaluation of the intercept
• ICH Q2(R2): Non-linear response 

Who Will Benefit:

• Analysts
• lab supervisors and managers in Analytical Development and Quality Control responsible for method development, optimization, and validation
• Quality Assurance and regulatory affairs representatives responsible to approve or evaluate analytical procedure validation