From method validation to the life-cycle

As mentioned above, the historical approach was rather one-dimensional. Factors such as measurement uncertainty, suitable acceptance criteria, requirements for stability-indicating or non-linear calibration models received little attention. Furthermore, modern techniques such as NIR and ICP-MS were not adequately addressed. The terms specificity and linearity were often misapplied or inconsistently defined. Overall, these guidelines reflected a static, rather than dynamic, understanding of validation.

A turning point came with the 2011 FDA Process Validation Guidance, which for the first time introduced the life-cycle concept, aligning closely with Annex 15 of the EU GMP Guidelines. This led to new global concepts for analytical procedures. In the USA, USP <1220> (“The Analytical Procedure Life Cycle”, effective since May 2022) was established, while in Europe, the revised guidelines ICH Q2(R2) and ICH Q14 were finalised and published in January 2024.

The life-cycle approach aims to understand and control analytical variability, thereby increasing the reliability of results. It provides a framework for defining performance characteristics, developing suitable procedures, and maintaining control throughout the method life-cycle. Both classical (univariate) and multivariate techniques such as FTIR, NIR and Raman spectroscopy are included.
The new ICH Q14 guideline defines scientifically sound, risk-based strategies for method development and control. Building on ICH Q8 (Pharmaceutical Development) and ICH Q9 (Quality Risk Management), it allows a choice between a traditional or enhanced approach. The enhanced model integrates modern tools, real time release testing (RTRT), and enables efficient change management in accordance with ICH Q12. Submitting data in CTD format supports transparent regulatory communication and post-approval flexibility.

According to Schmidt and Stanic (GMP Journal, June 2025), the practical implementation of ICH Q14 relies heavily on digital and statistical methodologies. Key tools include:

• Design of Experiments (DoE): evaluation of influencing factors and model development.
• Multivariate statistics: defining design space and assessing robustness.
• Control strategy and knowledge management: data-driven control and documentation.
• As a result, Quality by Design (QbD) again moves to the forefront of analytical procedures, marking the shift from traditional, rigid approaches towards flexible, science-based systems.

Their growing significance is reflected at the PharmaLab Congress in Düsseldorf (24–26 November 2025), introducing the new track “Bioanalytical Control of Biological Drug Substances and Products”. This track specifically addresses  bioanalytical methods and regulatory expectations, underlining the increasing importance of analytical control for bio-logically active substances as a central theme within the European GMP quality landscape. Further information: www.pharmalab-congress.com/bioanalytical

This article from Axel H. Schroeder, Operations Director, CONCEPT HEIDELBERG GmbH, was originally published in the Special CDMOs & CROs as part of European Biotechnology Magazine Autumn 2025.