Evolution of Analytical Procedure Validation Concepts: Part II– Incorporation of Science and Risk-based Principles in ICH Q14 and Q2(R2) Guidelines

In parallel to the evolution of compendial and regulatory approaches addressing new quality paradigms for analytical procedure validation (discussed in Part I of this article), fundamentals of the quality by design (QbD) concept have been incorporated into the new International Council for Harmonisation (ICH) Q14 and ICH Q2(R2), which were recently released for public consultation. This article focuses on drawing parallels between ICH Q14/Q2(R2), United States Pharmacopeia (USP) <1220>, and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 17025:2017.

ICH Q14 Draft Guideline: Analytical Procedure Development

In March 2022, the ICH Q14 draft guideline was published for public consultation aiming to describe science- and risk-based approaches for developing and maintaining analytical procedure suitable for assessing the quality of chemical and biological/biotechnological drug substances and drug products (1). ICH Q14 considers the application of QbD principles to the development and analytical procedure life cycle (APLC) management based on the systematic approach suggested in ICH Q8, together with principles described in ICH Q9.

One of the most significant sections for industry is chapter 7, “Lifecycle Management and Post-Approval Changes of Analytical Procedures”, which mentions several elements for APLC management, in line with Q12. Examples are established conditions (EC), post-approval change management protocols (PACMPs), product life cycle change management (PLCM), and pharmaceutical quality system (PQS).

In addition, Q14 introduces the elements method operable design region (MODR) and analytical target profile (ATP), which support the industry in applying the enhanced approach and may facilitate regulatory communication of post-approval changes and allow for regulatory flexibility, possibly reducing the burden on industry. Q14 mentions that ATP could also form the basis of a PACMP, which would allow changes between technologies to be reported at a lower reporting category, provided that the previously established performance requirements for a change are met (1). Although Q14 does not clearly emphasize the role of the MODR in the PACMPs, this element could build the basis for allowing suitable risk management, enabling comprehensive analytical changes management within the qualified operating ranges while identifying which conditions meet ATP requirements without running additional experimentation or validation. From a compendial perspective, the inclusion of validated MODR in compendial monographs can provide a certain degree of flexibility for risk management to ensure fitness for use (“operating range procedure” instead of “traditional fixed-point procedure”). Other analytical QbD (AQbD) elements may be potentially incorporated into monographs, such as the ATP, replication strategy (e.g., number of injections; sample and standard preparation) and analytical control strategy (ACS [e.g., system suitability and any relevant attribute/requirement]). The ATP and AQbD principles were introduced by joint working groups of the European Federation of the Pharmaceutical Industries and Associations (EFPIA) and the Pharmaceutical Research and Manufacturers of America (PhRMA) in 2010 (2,3), and later in a few USP stimuli articles (4–9) and USP <1220> (10). The MODR was introduced by several authors in 2010 (11,12), in USP <1220> (10) and in ICH Q14(1). The first official mention of MODR by health authorities was in the European Medicines Agency (EMA)–FDA pilot program report (13).

Key aspects in Q14 include the following:

• Minimal (traditional) or enhanced approaches to analytical procedure development can be applied.

• The enhanced approach offers a systematic way of developing analytical procedure and managing knowledge. This approach is similar to stage 1 described in USP <1220>.
• Knowledge and quality risk management (QRM) are presented as key enablers of the enhanced approach as well as the definition of ATP.
• Other elements included in the enhanced approach are the use of multivariate experiments, establishment of an analytical procedure control strategy, and definition of reporting categories of ECs, proven acceptable ranges (PARs), or MODR. All this information can be used to build the lifecycle change management plan and can be shared in the regulatory dossiers.
• Q14 highlights the important role of robustness assessment during procedure development.
• Q14 emphasizes the importance of establishing analytical procedure control strategy and recommends ongoing monitoring of selected analytical procedure outputs to look for any trends considering the analytical procedure control strategy as major enabler. However, little guidance is given on how to conduct ongoing monitoring.
• Q14 brings a section dedicated to development of multivariate analytical procedure and real-time release testing (RTRT), building off existing guidance (e.g., Q2(R2) and Q13). It presents the multivariate model lifecycle and provides support for the use of multivariate prediction models for risk assessment.
• A section on submission of analytical procedure–related information has also been included to facilitate harmonization of the level of details submitted by applicants.

As discussed in Part I of this article, the ICH Expert Working Group (EWG) decided to split the APLC stages into Q14 and Q2(R2) guidelines, attempting to not significantly change the structure of Q2(R2) from its previous version (14). Although both guidelines present some level of interconnectivity, stronger connectivity could have been built to facilitate the knowledge management. QRM should be emphasized, because this is what connects all stages. Tables I and II show a comparison of terminology and elements between Q14 and USP <1220>.

Q2(R2) Draft Guideline: Validation of Analytical Procedures

ICH Q2(R2) applies to new or revised AP used for release and stability testing of commercial drug substances and products (chemical and biological/biotechnological). However, it can be applied to support clinical studies development, as well as other types of products, with appropriate regulatory authority consultation as needed (15). Q2(R2) can also be applied to other analytical procedure used as part of the control strategy (Q8–Q10) following a risk-based approach (15), enlarging its scope to validate procedures to be used for manufacturing process monitoring and other stages involved in the pharmaceutical product life cycle. Q2(R2) can be seen (in part) as similar to stage 2 described in USP <1220>; however, the two documents have the following significant differences:

• Q2(R2) does not include guidance for procedure transfer and verification, which are part of stage 2 in USP <1220>.
• The concept of “analytical procedure validation” differs between Q2(R2) and USP <1220>.
  1. As per USP <1220>, “Analytical procedure performance qualification” (APPQ) refers to all activities performed in APLC stage 2, conducted to confirm that the procedure is fit for its intended purpose, and may include “traditional” procedure validation, transfer, and verification (10,16). APPQ is inspired by the term “process performance qualification” included in FDA’s guidance on process validation (17), referring to activities that confirm that the commercial manufacturing process design and performance are as expected.
  2. As per USP <1220>, “AP validation” refers to a broader concept that encompasses all activities that confirm that a procedure is suitable for use and that take place over the entire APLC, not just activities restricted to stage 2 and “traditional validation”. Q2(R2) still describes the “traditional” procedure validation concept only. The more holistic concept of validation introduced in USP <1220> expands the well-known activities to integrate them into the procedure life cycle and include them in a process that incorporates the ATP. Q2(R2) does not mention ATP and does not emphasize: the link between the ATP performance characteristics and the intended purpose of the reportable value; and the probability assessment of making a wrong decision.

A high-level summary of new principles included in Q2(R2) is provided in the following sections.

Knowledge management versus checkbox exercise: incorporation of risk-based approach principles. ICH Q2(R2) emphasizes the importance of using prior knowledge to design the validation protocol and illustrates the interdependencies of APLC stages covered in Q14. The ATP is an element considered as a guide to ensure fitness for use along the entire APLC in USP <1220>. However, the ATP was not mentioned in Q2(R2), which still leaves some gaps in ensuring fitness for use and representing the APLC holistically. A new section entitled “Validation during the lifecycle of an AP” was included to emphasize the importance of APLC management. Q2(R2) mentions that changes may be required during the product life cycle and that science- and risk-based principles can be used to justify whether or not a given performance characteristic needs revalidation. This provides connectivity to Q14 (section 7), which is in line with Q12, and provides a certain flexibility for submission of post-approval changes by the industry.

Amplify spectrum of analytical techniques and support validation of RTRT. While ICH Q2(R1) places a greater focus on chromatographic procedures and is not sufficient to establish the suitability of multivariate procedures, Q2(R2) amplifies the spectrum of analytical procedure that it can be applied to, such as UV (entire spectrum), infrared spectroscopy (IR), near-infrared spectroscopy (NIR), nuclear magnetic resonance (NMR), mass spectrometry (MS), liquid chromatography-mass spectrometry (LC-MS), etc. The new section, 3.4, in Q2(R2) provides considerations for validation of multivariate analytical procedure. This supports development of process analytical technologies (PATs), which usually apply multivariate data and require the use of machine learning methodologies for large data set processing and analysis. Q2(R2) builds off existing principles described in Q13 (continuous manufacturing) (18) and supports the development and validation of not just offline procedures but also in-line/online/at-line procedures that can be used for process monitoring/control and RTRT. USP <1039> Chemometrics provides general guidance on the application of machine learning algorithms in the development of multivariate procedures; however, it does not provide connectivity to the APLC described in USP <1220> and may be revised in the near future to provide best practices for development of PATs and to cover a wider spectrum of analytical techniques. USP <1039> may also be used as a risk-based approach for development of different compendial standards, along with USP <1220>.

Performance characteristics at a glance. In ICH Q2(R2), the language around a few performance characteristics was changed to accommodate suitable considerations for the validation of uni- and multi-variate procedures. Table III provides a summary of these changes.

Drawing parallels between ISO standards, ICH Q14/Q2(R2), and USP <1220>

The evolution of validation concept principles to a APLC risk-based approach is also occurring in other industries, standard-setting bodies, and regulations. Consequently, they are incorporating similar tools and approaches, often taking these from metrology. In this section, the approaches of the ISO standards, especially ISO/IEC 17025:2017; the ICH Q14/Q2(R2); and USP <1220> are presented and compared (Tables IV and V). They may use different terms or emphasize various related concepts differently, but they all have this same focus: “ensure that a procedure is fit for use”.

Another similarity between these guidelines is the importance of assessing risk. Risk is based on fit for purpose, because risk is assessed by its impact on the analytical procedure’s fitness for purpose. In addition, probability is part of risk, where the probability of being wrong (or the probability of a reportable value not being fit for its purpose) is used to assess the risk of making the wrong decision about product compliance/quality. The acceptable probability of being wrong; the clear, concise definition of what is being measured; and the acceptable range of results can be determined using the decision rule, measurand, and target measurement uncertainty and then can be included in the ATP. These items then guide the ongoing analytical procedure performance verification during routine use and also when changes are made. These relationships are shown in Figure 1.

References

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12. Hanna-Brown, M. Borman, Bale S, Jones J., Development of Chromatographic Methods Using QbD Principles, Separation Science. 2010, 2, 12–20.
13. EMA and FDA. EMA-FDA pilot program for parallel assessment of Quality by Design applications, 2011. (accessed June 30, 2022).
14. Teasdale A., Borman P.J., Mullen A.K.. Regulatory Highlights. Org. Process Res. Dev. (2022). https://doi.org/10.1021/acs.oprd.2c00054.
15. ICH. ICH Draft Guideline Q2(R2) Validation of Analytical Procedures (ICH, 2022).
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About the authors

Amanda Guiraldelli is Scientific Affairs Manager, United States Pharmacopeia, Rockville, MD. Jane Weitzel is an Independent Consultant, (Winnipeg, Canada) and Chair of the US Pharmacopeia Expert Committee on Measurement and Data Quality