Jane Weitzel

The principles of quality by design (QbD) and life cycle management, as outlined in International Council for Harmonisation (ICH) Q8–Q12, can equally be applied to the development, validation, and ongoing verification of analytical procedures. The first publicly available drafts of ICH Q14 (1) and Q2(R2) (2) issued in March 2022 cover the lifecycle management of analytical procedures and provide guidance on the development and validation stages of the lifecycle. There is little mention, however, of the ongoing procedure performance verification stage. 

’s) general chapter <1220>, entitled “Analytical Procedure Life Cycle” (3), which became official in May 2022, holistically pulls together the design, qualification, and ongoing performance verification of analytical procedures in a single document via a three-stage approach similar to FDA’s lifecycle-based process validation guidance (4).

 <1220> is to ensure that the analytical procedure is fit for purpose across the entirety of the analytical procedure’s life cycle. The requirements that the analytical procedure have to meet can be defined using the analytical target profile (ATP) (a concept explained in both 

 <1220> and ICH Q14 as well as in the literature [5–8]). The ATP is a prospective description of the desired purpose and performance of an analytical procedure that is used to measure a quality attribute and defines the required quality of the reportable value produced by the procedure (3). In Stage 3 of 

 <1220>, the ATP can also be used to determine the acceptance criteria needed to verify the performance of the analytical procedure during routine use (e.g., through a system suitability test [SST] or verification criteria applicable to procedure changes and transfers) and to ensure that the procedure continues to be fit for purpose. Performance verification can still take place even if an ATP hasn’t previously been defined. The verification acceptance criteria in these situations can be derived from validation or system suitability criteria. The principles in Stage 3 of 

 <1220> can therefore equally be applied to procedures that have been formally designed/developed (where an ATP exists) via an enhanced approach as well as procedures where a minimal approach was taken. For high-risk analytical procedures (see later section for how risk is determined), control-chart monitoring of selected performance data, generated during routine use of the procedure, can provide early warning of changes in performance. These data could be direct measures of accuracy and precision (e.g., through the analysis of a quality control sample) or indirect measures (e.g., chromatographic resolution between peaks, signal to noise response, peak tailing factor, etc.). Where the risk is low, performance verification may simply involve monitoring of atypical results and/or system suitability failures.

In addition to ensuring that the analytical procedure is fit for purpose during routine use, ongoing verification can also be used to evaluate the impact of any changes (9) to the procedure across the lifecycle and ensures that the performance of the procedure is maintained at an acceptable level over the procedure lifetime. Ongoing verification can also act as a preventive measure by providing an early indication of potential performance issues or adverse trends and aids in identifying required changes for the analytical procedure.

Determining performance monitoring via risk assessment

The performance of all analytical procedures used in the product control strategy should be assessed across the lifecycle of the product to ensure they remain fit for their intended purpose. This assessment should include routine monitoring (for prioritized procedures) as well as the evaluation of changes made to procedures. The extent of the routine monitoring required can be defined using a risk-based approach (10). It is important to consider which measures of analytical procedure performance or risk are readily available as inputs to a risk assessment. Two risk assessment approaches are described below.

 This approach may focus only on the type and complexity of the analytical procedure and its intended use. This approach would enable the establishment of a platform risk assessment per analytical procedure (technique) type. A complexity factor can be used to ensure that any unusually complex procedures are not underestimated. Analytical procedures that do not form a critical part of the control strategy can be treated as low risk by default.

 This approach may include an assessment of the current performance of the manufacturing process (which includes variability from the product and the analytical procedure) through an assessment of process performance (Ppk [11]) if enough representative batches of the manufacturing process (and analytical procedure) are available. A more involved risk assessment approach may include an assessment of the capability (precision) of the specific analytical procedure relative to the product specification or ATP. Precision to tolerance ratio (P/TOL [12]) and Z-score (13) are metrics that can be calculated to aid such an assessment. Conformity and validity rates and/or procedure robustness and reproducibility can also be used. Where procedures have been shown to be sensitive to changes (e.g., analyst, equipment, environment, reagent lots, or small changes in procedure parameters), this sensitivity presents a higher risk. 

 depicts sources of variability associated with Ppk and procedure capability metrics (such as P/TOL and Z-score). 

ALL FIGURES ARE COURTESY OF THE AUTHORS. 

 Product and analytical procedure sources of variability. P/TOL is precision to tolerance ratio.

Manufacturing process performance assessment through Ppk.

 Ppk (11) is a process performance index and can be used as a worst-case surrogate measure for analytical procedure precision. It represents a combination of manufacturing process and analytical procedure variability over the long term. If a drug product has a good overall process capability (Ppk) for a particular quality attribute (i.e., if the test results show little variation versus the specification), then it can be assumed that the analytical procedure precision is good (see 

where USL is the upper specification limit, LSL is the lower specification limit, 

overall is the combined process and analytical procedure standard deviation.

Analytical procedure performance assessment through P/TOL or Z-Score.

 P/TOLis described by Chatfield and Borman (12), and it is defined as shown in 

a is the analytical procedure standard deviation. Low P/TOL values are desirable.

The Z-score (13) is similar to P/TOL as it is defined as the number of analytical procedure standard deviations between the process mean and the nearest specification limit (see 

where SL is the nearest specification limit to the process mean (

A data-driven risk assessment that considers both process and analytical procedure capability is shown in 

 Data-driven risk assessment for identification of high-risk analytical procedures. P/TOL is precision to tolerance ratio.

When performing a risk assessment, it is possible that a low-risk procedure could become a high-risk procedure during a subsequent periodic risk assessment due to changes in the manufacturing process that impact the process mean, or changes to specification limits, despite the analytical procedure precision (

a) remaining constant. In such cases it may not be possible/practical to improve the procedure performance to reduce the risk of out-of-specification data, but it may be appropriate to consider manufacturing process improvements or review of the specification limit(s).

Development of risk-based performance-monitoring plans

Three types of procedure performance indicators categorized by Ermer 

Conformity: the number of out-of-specification results with analytical procedure root cause in a given time period. The number and types of analytical procedure errors will provide information on the reliability of the analytical procedure.

Validity: the number of invalid test results due to failures of system suitability criteria (established during Stage 1 of the lifecycle approach) in a given time period

Measurements collected during each analytical procedure test occasion monitored using control charts: these measurements could be critical analytical procedure attributes or parameters specified in the analytical procedure with well-defined acceptance criteria or ranges, respectively, or attributes or parameters selected due to a potential link with procedure performance.

“Conformity” monitoring is usually sufficient for low-risk analytical procedures, whereas for high-risk procedures “validity” monitoring and monitoring of informative analytical procedure attributes and/or parameters can provide early warning of potential changes in procedure performance.

A useful mechanism to identify the most value-adding performance attributes or parameters to monitor for high-risk procedures is to perform a procedure performance cause-and-effect review (PPC&ER). This review provides the analytical team with an understanding of likely root causes of any high risks identified from the risk assessment. Potential improvement ideas and tailored procedure performance indicators can then be documented for further consideration (and potentially taken forward for inclusion in the monitoring plan).

 <1220> and ICH Q14 describe the use of Ishikawa or fishbone diagrams (11) for risk identification. These are highly useful tools for collectively brainstorming potential sources of variability associated with a procedure. Gembas (11) (or “procedure walk-throughs” used in the implementation of lean principles) are also very important for this activity, and the analysts that are most familiar with the procedures should be included. It can also be useful to include independent experienced analytical scientists who are not familiar with the particular procedure under assessment and/or technique subject matter experts. Augmented reality technology can be a useful way to orientate all meeting participants with the procedure under assessment and to demonstrate any particularly problematic steps. Once sufficient analytical procedure platform knowledge has been acquired, creation of generic Ishikawa diagrams and process maps can prove useful starting points and serve to significantly accelerate this step. As it is not practical to monitor all potential sources of variability, it is important to prioritize the most value-adding procedure performance indicators for the monitoring plan.

A PPC&ER can be performed for new high-risk procedures that have been developed following the guidance in Stage 1 of 

 <1220> or ICH Q14 (as part of procedure development) and a monitoring plan developed at the same time as design of the analytical procedure control strategy. For established analytical procedures where 

’s Stage 1 was not followed/documented, then a new PPC&ER can be a good first step towards the design of a monitoring plan. Once the procedure performance indicators for routine monitoring have been selected, a decision on the most appropriate method of monitoring can be taken. The use of control charting in a similar fashion to statistical process control (SPC) should be considered to facilitate the identification of any drifts in performance of high-risk analytical procedures over time. The authors recommend the adaptation of SPC (14) tools and have termed this “Statistical Analytical Procedure Performance Control (SAPPC).” Well established SPC control chart types such as Shewhart (14), cumulative sum (Cusum) (14), and exponentially weighted moving average (EWMA [14]) can be applied to analytical procedures. Performance data compiled over time allows for the calculation of average parameters, for example repeatability from replicate sample preparations or intermediate precision from control sample analysis. Such average parameters are very reliable estimates of the long-term performance (10) and facilitate the identification of atypical results.

Analytical procedure performance monitoring will enable opportunities for proactive improvement of procedure performance to be identified over time. Improvements could be relatively small, such as updating training plans or changing wording in method documentation to improve clarity and consistency of procedure operation. Improvements could relate to instrument or reference standard management, or sometimes more fundamental procedure changes that require regulatory pre-approval action (e.g., changes to critical analytical procedure parameters or analytical technology).

Opportunities for improvement can be considered as a part of periodic review (e.g., reviews may occur during scheduled revisits of the analytical procedure risk assessment and PPC&ER or in response to a procedure performance trend alert during routine performance monitoring).

Case study 1: quantification of API polymorphic purity

 (15) describe how ongoing verification of a solid-state nuclear magnetic resonance (ssNMR) procedure used to quantify polymorphic purity of an API enabled an unusual effect relating to a standard used in the procedure to be identified and remediated promptly through a detailed PPC&ER. The level of an unwanted Form (Form 3) in the standard was observed to gradually increase over time. Following a thorough PPC&ER, corrective actions were implemented that resulted in the variability of the procedure due to the standard being significantly reduced with an acceptable range of ±1%. Following implementation of remedial actions, it was agreed to routinely monitor the amount of Form 3 as part of the routine procedure performance monitoring plan to ensure the integrity of the standard was maintained.

Case study 2: ion chromatography procedure performance monitoring

Ion chromatography instrument failures were observed for the same analytical procedure at two independent quality control laboratories after years of normal operation. These failures resulted in lengthy investigations, system downtime, and wasted resources. A PPC&ER determined the root cause to be an aging component within the ion chromatography system. As the aging of the instrument component led to a slow decline in procedure precision over time, calibration standard injection % RSD and % sample duplicate difference have now been added to the routine procedure performance monitoring plan for this procedure to provide an early detection mechanism. 

 provides examples of how these procedure performance indicators are trended. Drift in performance can be identified and the aging component replaced before batch results are impacted, and before system failure occurs. 

 Drift in precision detected over time for an ion chromatography procedure. RSD is relative standard deviation.

Ongoing analytical procedure performance verification can be used to ensure that procedures continue to be fit for their intended purpose across the lifecycle of their use. It can be equally applied to analytical procedures that have been developed via an enhanced approach (where an ATP has been created) as well as established procedures where 

 <1220> Stage 1 was not followed/documented. The extent of monitoring should be risk-based, and the assessment of both the manufacturing and analytical capability is recommended to determine which analytical procedures carry the greatest risk. A detailed procedure PPC&ER employing tools such as fishbone diagrams and gembas can be used to identify the most value-adding performance attributes or parameters to monitor (control charting is recommended for high-risk procedures). Performance verification can provide an early indication of potential performance issues and highlight opportunities to improve procedures. It can also be used to assess any changes made to analytical procedures over the lifecycle.

 <1220>, Analytical Procedure Lifecycle. 

Guidance for Industry, Process Validation: General Principles and Practices

 (CDER, CBER, 2011).
5. Barnett, K.L.; McGregor, P.L.; Martin, G.P.; et al. Analytical Target Profile: Structure and Application Throughout the Analytical Lifecycle. 

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6. Jackson, P.; Borman, P.; Campa, C.; et al. Using the Analytical Target Profile to Drive the Analytical Method Lifecycle. 

, 91 (4), 2577–2585.
7. Rignall, A.; Borman, P.; Hanna-Brown, M.; et al. Analytical Procedure Lifecycle Management: Current Status and Opportunities. 

, 42 (12), 18–23.
8. Borman, P.; Campa, C.; Delpierre, G.; et al. Selection of Analytical Technology and Development of Analytical Procedures Using the Analytical Target Profile. 

, 94 (2), 559–570.
9. Chatfield, M.J.; Borman, P.J.; Damjanov, I. Evaluating Change During Pharmaceutical Product Development and Manufacture-Comparability and Equivalence. 

, 27 (5), 629–640.
10. Ermer, J.; Aguiar, D.; Boden, A.; et al. Lifecycle Management in Pharmaceutical Analysis: How to Establish an Efficient and Relevant Continued Performance Monitoring Program. 

, 181, 113051. DOI: 10.1016/j.jpba.2019.113051.
11. Ishikawa, K. 

What is Total Quality Control? The Japanese Way

; Prentice-Hall, Englewood Cliffs, NJ, 1985.
12. Chatfield, M.J.; Borman, P.J. Acceptance Criteria for Method Equivalency Assessments. 

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13. Vukovinsky, K.; Watson, T.; Ide, N.; et al. Statistical Tools to Aid in the Assessment of Critical Process Parameters. 

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14. Suman, G.; Prajapati, D. Control Chart Applications in Healthcare: a Literature Review. 

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15. Barry, S.J.; Pham, T.N.; Borman, P.J.; Edwards, A.J.; Watson, S.A. A Risk-Based Statistical Investigation of the Quantification of Polymorphic Purity of a Pharmaceutical Candidate by Solid-State 19F NMR. 

Phil Borman is vice-chair of the USP Measurement and Data Quality Expert Committee (USP M&DQ EC); Amanda Guiraldelli Mahr is scientific affairs manager, US Pharmacopeia; Jane Weitzel is chair of the USP M&DQ EC; Sarah Thompson is principal scientist—Analytical Project Expert, AstraZeneca; Joachim Ermer, Stephanie Sproule, and Jean-Marc Roussel are members of the USP M&DQ EC; Jaime Marach is member of USP Analytical Procedure Life Cycle Joint Subcommittee; and Horacio Pappa is senior director, US Pharmacopeia.

When referring to this article, please cite it as Borman, P.; Mahr, A.G.; Weitzel, J.; et al. Ongoing Analytical Procedure Performance Verification—Stage 3 of 

Articles

Analytical procedure performance can be continually verified by risk-based monitoring of performance related data.

Ongoing Analytical Procedure Performance Verification—Stage 3 of USP<1220>

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), 

) <1220>, and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 17025:2017.

No additional expectations or mandated requirements are expected in Q14, Q2(R2) and USP <1220>. The minimal approach can still be used.

Q14 and Q2(R2) are consistent with the principles described in USP <1220>, but not in full agreement.

Although Q14/Q2(R2) represent great progress towards implementation of sound science and QRM, their publication as separate documents still leaves some gaps since a comprehensive and continuous APLC is not presented.

Presents strategies that allow for a more comprehensive AP change management and risk assessment (e.g., MODR, ATP, and ACS can be the basis for PACMPs and can be included in the regulatory dossiers).

Provides flexibility for post-approval changes and potential reduction of burden in the industry.

Presents the enhanced approach with a focus on fitness for use

More connectivity with other stages of the APLC.

Use of prior knowledge to design a more suitable validation protocol and implementation of risk-based approaches.

Provides support for validation of multivariate procedures such as PATs using other techniques rather than just chromatographic procedures or offline procedures.

No changes are required in terms of assessing specificity/selectivity, working range, accuracy and precision.

An alternative approach for combined accuracy and precision may be used and may help to ensure fitness for use.

<1225>, <1226>, and <1224> may be revised since they lack the connectivity to other APLC stages.

<1039> may be revised to provide guidance on the development of multivariate procedures and complement the principles described in USP <1225> providing support for development of RTRT and PATs.

<1220> and <1225> may be revised to be harmonized with Q14/Q2(R2).

AQbD elements may be incorporated into compendial monographs. The enhanced approach may change how compendial monographs are written in the future, providing a certain degree of flexibility.

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 

 <1220> (10). The MODR was introduced by several authors in 2010 (11,12), in 

 <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 

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. 

show a comparison of terminology and elements between Q14 and 

 Comparison of terminology and elements between International Council for Harmonisation (ICH) Q14 and United States Pharmacopeia (USP) General Chapter <1220>–ATP and Stage 1. [Click to enlarge]

 Comparison of terminology and elements between International Council for Harmonisation (ICH) Q14 and United States Pharmacopeia (USP) General Chapter <1220> – Stages 2 and 3. APLC is analytical procedure life cycle. [Click to enlarge]

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 

 <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 

The concept of “analytical procedure validation” differs between Q2(R2) and 

 <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.

 <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 

 <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 

 <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. 

 <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 

 <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. 

 <1039> may also be used as a risk-based approach for development of different compendial standards, along with 

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. 

 Comparison of performance characteristics described in International Council for Harmonisation (ICH) Q2(R1) and Q2(R2) and how they relate to United States Pharmacopeia (USP) chapters and ICH Q14. [Click to enlarge]

Drawing parallels between ISO standards, ICH Q14/Q2(R2), and 

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 

). 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”.

 Comparison of terminology and elements between International Council for Harmonisation (ICH) Q14, Q2(R2), United States Pharmacopeia (USP) <1220>, and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 17025–Part I. GUM is Guide to the Expression of Uncertainty in Measurement. [Click to enlarge]

 Comparison of terminology and elements between International Council for Harmonisation (ICH) Q14, Q2(R2), United States Pharmacopeia (USP) <1220>, and International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 17025 – Part II. [Click to enlarge]

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 

 Relationship among the various tools and approaches, where the purpose of the analytical procedure informs all the following steps. [Figure courtesy of the authors. Click to enlarge]

ICH Draft Guideline Q14 Analytical Procedure Development

Schweitzer M., Pohl M., Hanna-Brown M., Nethercote P., et al., 

Implications and Opportunities of Applying QbD Principles to Analytical Measurements.

Borman P., Chatfield M., Nethercote P., Thompson D., Truman K., The Application of Quality by Design to Analytical Methods, 

Kovacs E., Ermer J., McGregor P.L., et al., Analytical Control Strategy, USP Stimuli Article, 

Weitzel J., Meija J., LeBlond D., Walfish S., Measurement Uncertainty for the Pharmaceutical Industry, USP Stimuli Article, 

Martin G.P., Barnett K.L., Burgess C., et al., Proposed New USP General Chapter: The Analytical Procedure Lifecycle <1220>, USP Stimuli Article, 

Burgess C., Curry P., LeBlond D.J., et al., Fitness for Use: Decision Rules and Target Measurement Uncertainty, USP Stimuli Article, 

Barnett, K.L., Mcgregor P.L., Martin G.P., et al., Analytical Target Profile: Structure and Application Throughout the Analytical Lifecycle, USP Stimuli Article, 

Martin G.P., Barnett K.L., Burgess C., et al., Lifecycle Management of Analytical Procedures: Method Development, Procedure Performance Qualification, and Procedure Performance Verification, USP Stimuli Article, 

USP. General Chapter <1220> Analytical Procedure Lifecycle, 

Borman P., Roberts J., Jones C., Hanna-Brown M., Szucs R., Bale S., The Development Phase of an LC Method Using QbD Principles. 

Hanna-Brown, M. Borman, Bale S, Jones J., Development of Chromatographic Methods Using QbD Principles, 

EMA-FDA pilot program for parallel assessment of Quality by Design applications, 2011. 

Teasdale A., Borman P.J., Mullen A.K.. Regulatory Highlights. 

 (2022). https://doi.org/10.1021/acs.oprd.2c00054.

ICH Draft Guideline Q2(R2) Validation of Analytical Procedures

Nethercote P., Borman P., Bennett T., Martin G., McGregor P., QbD for Better Method Validation and Transfer, 

Guidance for Industry. Process Validation: General Principles and Practices.

ICH Draft Guideline Q13 Continuous Manufacturing of Drug Substance and Drug Products

International Vocabulary of Metrology-Basic and General Concepts and Associated Terms (VIM

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

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. 

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

In recent years, regulatory agencies have placed an increased emphasis on pharmaceutical process understanding through adoption of Quality by Design (QbD) principles by launching a series of initiatives to encourage the pharmaceutical industry to adopt QbD in the manufacturing process. A key component of this transformation is the evolution of validation concepts 

life cycle risk-based approach driven by 

Analytical Quality by Design (AQbD) principles

Different pharmacopoeias have been developing compendial approaches to support the implementation of analytical procedure 

International Conference on Harmonisation (

ICH) released in March 2022 two draft guidelines for public consultation which outline QbD principles: ICH Q14 (procedure development) 

, and the ICH Q2(R2) (procedure validation) 

. In a series of two articles, the authors will provide an overview of the validation concept principles evolution 

with a focus on compendial perspectives (Part I) and draw a parallel between ICH Q14 and Q2(R2) and 

 General Chapter <1220> and the ISO/IEC 17025:2017 (Part II). 

Evolution of process validation concept: quality paradigm shifts in the pharmaceutical environment

The new industrial revolution, “Industry 4.0,” has been leading to changes in the pharmaceutical industry (“Pharma 4.0”), where significant paradigm shifts have been occurring in the pharmaceutical quality environment to enable manufacturing modernization and innovation. These changes have significant implications for how we think about pharmaceutical quality. Regulators, industry, and standards-setting organizations are increasingly recognizing the need to rely more on risk-based and QbD approaches rather than ensuring quality solely by compliance-driven and quality-by-testing approaches (3). In this context, traditional validation practices are undergoing a paradigm shift that requires an in-depth understanding of products and processes.

The principles of process validation were initially established in the US Food and Drug Administration (FDA) guidance on general principles of process validation in 1987 (4) and have been considered in guidelines worldwide, including the current good manufacturing practices (CGMP) regulations promulgated by European regulatory agencies and the ICH. At that time, a common validation practice was to conduct process validation activities during the late stages of the product life cycle, primarily during phase III clinical studies, in preparation for filing biologics license application (BLA)/new drug application (NDA) and commercialization of the product. Validation activities conducted at early stages were minimal (5). Since 1987, the concepts of validation have evolved from a traditional “fixed-point” manufacturing process to a “life cycle” risk-based approach (5). Gradually, a new quality paradigm based on QbD principles started to take shape with the goal of building the quality into the product.

QbD is a concept first developed by the quality pioneer Dr. Joseph M. Juran (6). As defined by Dr. Janet Woodcock, currently FDA’s principal deputy commissioner, “QbD means that product and process performance characteristics are scientifically designed to meet specific objectives, not merely empirically derived from performance of test batches” (7). Over the past 20 years, regulatory agencies have been encouraging the adoption of QbD principles in pharmaceutical development through several initiatives including the FDA 2004 report, “Pharmaceutical cGMPs for the 21st Century – A Risk Based Approach” (8). The need to modernize the quality management process was also recognized by ICH and resulted in the development of a new series of guidelines outlining QbD principles and emphasizing the importance of knowledge and quality risk management (QRM)(9). In the ICH Q guideline series, the QbD concept was first introduced in 2004 in the ICH Q8 pharmaceutical development(10). The notion of QRM’s importance as an enabler of the QbD approach was reinforced with the approval of ICH Q9 in 2005 (11). Later, QbD principles were outlined in the process validation guidance published in 2011 by FDA (12) and in 2012 by the European Medicines Agency (EMA) (13), which are now in line with ICH Q8-Q11; both also require adherence to CGMP regulation.

“Quality by Design is a systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management” (10).

FDA has played a pivotal role in the transformation of quality culture, launching a series of pilot programs since 2005 to incorporate elements of QRM and QbD throughout the product life cycle (e.g., FDA ONDQA CMC pilot program 2005 (14); FDA OBP pilot program 2008). In March 2011, EMA and FDA launched a pilot to assess QbD applications in order to ensure consistent implementation of ICH Q8-11 guidelines between the European Union and the United States and facilitate sharing of regulatory decisions on new regulatory concepts (14,15). A final report was issued to communicate the lessons learned from the program (16).

ICH continued to develop guidelines outlining QbD principles. Examples are ICH Q12 (holistic framework for product life cycle management including analytical procedures)(17) and ICH Q13 draft guideline (continuous manufacturing) (18). ICH also established an Expert Working Group (EWG) in 2018 to revise Q2(R1) and develop the new guideline Q14 covering approaches for analytical procedure development. Q14 and Q2(R2) were released for public consultation in March 2022, outlining the life cycle risk-based approach applied to APLC management. These guidelines also build off both Q12 and Q13 guidelines, providing support to allow for implementation of principles and concepts described in both guides (

 Connectivity between the principles described in the most recent International Council for Harmonisation (ICH) Q guidelines which outline quality-by-design (QbD) principles. (Figure courtesy of the authors)

To advance the quality culture transformation necessary for continuous quality improvement, FDA continues to work on strategies to support implementation of product life cycle principles and facilitate regulatory flexibility when evidence of a mature and effective quality system is available (19). Investigations of supply disruptions show that manufacturing or quality issues are common root causes of drug shortages (e.g., substandard manufacturing sites or processes, or quality defects in the finished product), highlighting the need to implement strategies that can help advance quality. The New Inspection Protocol Project (NIPP) and Quality Management Maturity (QMM) (20) programs are examples of initiatives led by the FDA to build a framework to enable continuous quality improvement and mitigation of quality risks. In the 2021 report on the state of pharmaceutical quality, FDA recognizes that enhanced knowledge management and emphasis on risk-based approaches will enable FDA to target its regulatory resources more effectively, better protect the public from noncompliant products, and advance the quality of medicines (19). The NIPP and QMM initiatives demonstrate FDA’s commitment to innovative quality programs (19).

Evolution of validation concept in the analytical procedure context: analytical procedure life cycle

The concept of analytical procedure validation has also been evolving to a life cycle risk-based approach. Current validation practices often focus on satisfying regulatory requirements rather than understanding and controlling sources of variability (8). Furthermore, existing guidance is often applied in a checkbox manner, and default performance criteria are often established to satisfy compliance objectives, although the rationale for establishing the criteria is not always transparent. In other words, often no proper performance requirements are established to ensure fitness for use.

 Verification and Validation Expert Panel (EP) to envision the future of analytical validation concepts. Later, this Panel became the 

 Measurement & Data Quality Expert Committee. Several 

 stimuli articles were published from 2013 to 2019, covering key aspects of the APLC. These include:

 39(5) Lifecycle Management of Analytical Procedures (21)

 44(1) Measurement Uncertainty for the Pharmaceutical Industry (25)

 45(6) Distinguishing the Analytical Method from the Analytical Procedure to Support the USP Analytical Procedure Life Cycle Paradigm (26).

These articles incorporate QbD principles previously outlined in ICH Q8-Q12 and in publications by different associations such as the joint working groups of the European Federation of the Pharmaceutical Industries and Associations (EFPIA) and the Pharmaceutical Research and Manufacturers of America (PhRMA) (7,27). These articles built the basis for developing 

General Chapter <1220> Analytical Procedure Lifecycle, published in PF46(5) Dec. 1, 2020 (official as of May 1, 2022, in 

 <1220> presents a holistic approach for APLC management and highlights the importance of sound scientific approaches and QRM for the development, control, establishment, and use of procedures to ensure fitness for use (28). The APLC approach is considered an enhanced approach driven by AQbD principles that provides connectivity between all stages of the APLC, allowing for proper knowledge management.

“Analytical Quality by Design (AQbD) is asystematic approach to development that begins with predefined objectives and performance requirements (analytical target profile) and emphasizes procedure performance understanding and control, based on sound science and quality risk management. AQbD is derived from QbD principles and refers to the application of QbD in the APLC management allowing for the quality to be built into the procedure design.”

The major driver for adopting the life cycle approach is to ensure that the reportable value is fit for use, because the reportable value provides the basis for key decisions regarding compliance of a product with regulatory, compendial, and manufacturing limits (28).

Key questions that the industry usually needs to answer are:

“Can the lot of finished product meet specification so it can be released?”

“Does the manufacturing in-process sample contain the right amount of excipient?”

“Is the concentration of a residual solvent low enough to meet regulatory requirement?”

“What is the concentration of drug in the blood from a clinical study so that the dosage can be established?”

By ensuring analytical procedure (AP) fitness for use, the industry is allowed to answer these questions with confidence and minimize the risk of making the wrong decision about the product’s conformance and quality. In 

 <1220>, fitness for use is described as a concept used to show that a procedure meets established performance requirements and is considered fit for its intended purpose, where the establishment of the acceptable probability of making a wrong decision is part of ensuring that the AP is fit for use (28).

Different approaches can be used to ensure procedure fitness for use. Along the evolution of AP validation concepts, the acquisition of understanding about total procedure variability and its association with risk of false conformity/nonconformity decisions about pharmaceutical products has been reinforced (26). Thus, a central piece of the APLC approach involves the consideration of measurement uncertainty (MU)/total analytical error (TAE) as a critical procedure attribute to guide AP design, establish acceptance criteria for procedure qualification, and guide the ongoing procedure monitoring phase. Concepts such as analytical target profile (ATP) and maximum allowable MU (i.e., target measurement uncertainty -[TMU]) have been introduced to draw attention to fitness for use as a goal throughout the analytical life cycle (26). The APLC framework is depicted in 

Analytical procedure life cycle framework described in 

<1220>. Reproduced from Reference (28). (Figure courtesy of the authors)

Analytical Target Profile (ATP) is the predefined intended purpose of the procedure that stipulates what procedure performance requirements are that are linked to the intended analytical application and the quality attribute to be measured (28). This includes the definition of the required quality of the reportable value, aligned with the quality target product profile (QTPP). For quantitative or semi-quantitative procedures, the ATP should include upper limits on the precision and accuracy (bias) of the reportable value (28). The ATP can be reviewed whenever necessary, based on knowledge acquired and risks identified during other stages of the APLC.

Stage 1 Procedure Design aims to acquire understanding of how analytical parameters impact critical procedure attributes. The QRM process is what drives the design of optimum conditions, allowing the identification of conditions that optimize performance and minimize/avoid bias (reducing variability) to establish an operating range called “method operable design region” (MODR). The MODR is a multidimensional region where all study factors in combination provide suitable mean performance and robustness, ensuring procedure fitness for use. The MODR is equivalent to the term “Design Space” cited in the ICH Q8.

This article provides an overview of validation concept principles evolution to a life cycle risk-based approach with focus on compendial perspectives. 