Regulatory Highlights Cite This: Org. Process Res. Dev. XXXX, XXX, XXX−XXX
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Regulatory Highlights
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INTRODUCTION This article, one of a series published twice yearly, seeks to examine areas of regulatory guidance and practice that can be considered to be of highest current interest and to have the greatest impact on the activities of chemists and engineers in process research and development of pharmaceuticals. This is because of either ongoing evolution of new guidance or, in the case of the existing guidelines, clarification through supplementary publications aligned to a specific guideline. In this review, we examine the potential scope and impact of new ICH topics, specifically ICH Q2(R2)/Q14 Analytical Procedure Development and Validation and ICH Q13 Continuous Manufacture. In addition, we also examine the topic of change control pertaining to active pharmaceutical ingredient (API) manufacture, focusing in particular on the relationship between change and maintenance of the quality target product profile, specifically bioequivalence.
procedures. ICH Q2(R2)/Q14 will also have the potential to facilitate the selection or identification of development approaches that will reduce the risk (associated with data quality) incurred by post-approval changes to analytical procedures discussed in the Step 2 version of ICH Q12,9 thus enabling more efficient and science-based change management. ICH Q2(R2)/Q14 will also provide the opportunity to define the terminology and approach required to identify what ICH Q12 terms “established conditions” mean for analytical procedures (legally binding information considered necessary to ensure product quality). ICH Q12 describes parametric and performance-based approaches that can also be applied to analytical procedures. According to the draft concept paper, the planned revision to ICH Q2(R1) will aim to define typical validation elements for diverse analytical procedures beyond just HPLC, which is the main focus of ICH Q2(R1). Additional analytical methodologies such as those based on near-infrared (NIR) spectroscopy and those reliant on multivariate models need to be considered, especially given that they are becoming more commonly used for process control and real-time testing of pharmaceutical products. The intent of ICH Q14 will be in line with ICH Q81 and Q11,4 showing “traditional” and “enhanced” approaches for developing analytical procedures while utilizing quality risk management tools (ICH Q92) within pharmaceutical quality management systems (ICH Q103). ICH Q14 will aim to define performance criteria (linked to the control strategy) for analytical procedures and define requirements for analytical validation. It will also facilitate a greater understanding of analytical procedures being shared in the regulatory submission and create a basis for more flexible regulatory approaches. The analytical target profile (ATP) concept is a cornerstone of the enhanced approach for analytical procedures and parallels the concept of the quality target product profile (QTPP) detailed in ICHQ8.1 The ATP can be defined as the combination of all performance criteria required to ensure that the measurement of a quality attribute is f it for the intended purpose and produces data that can be used with the required conf idence to support specification pass/fail decisions.10 The ICH Q2(R2)/ Q14 topic is a golden opportunity to provide a global definition for this key concept along with other analogous terms that have been developed for the drug substance and drug product (e.g., analytical procedure terms equivalent to critical process parameters, critical quality attributes (CQAs), design space, control strategy, etc.). The ATP can be used to state the requirements for the output of the test procedure, i.e., the reportable result (usually associated with a CQA). The selection and development of an analytical procedure should be driven by the ATP requirements. Once the analytical procedure is selected, quality risk management (Q9) in conjunction with first-principles experimental studies and prior knowledge can be used to identify variables that may
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ICH Q2(R2)/Q14: ANALYTICAL PROCEDURE DEVELOPMENT (ICH Q14) AND REVISION OF ICH Q2(R1) VALIDATION OF ANALYTICAL PROCEDURES It has long been recognized that the principles of Quality by Design (QbD), as outlined in ICH Q8−Q111−4 can equally be applied to the development and use of analytical procedures.5,6 In particular, the life-cycle concept described in ICH Q81 (defined as “all phases in the life of a product from the initial development through marketing until the product’s discontinuation”) can be applied to an analytical procedure (method) if it is considered to be analogous to a manufacturing process, with the output of that process being a reportable result.7 Even though the original intent of ICH Q2(R1) was to provide scientific guidance on how best to demonstrate that an analytical procedure is suitable for its intended purpose, Q2 has evolved to be interpreted as a set of mandatory expectations for an analytical procedure. Since the adoption of Q2, its validation expectations (typically conducted via a “one-off exercise”) have helped to ensure that suitable analytical procedures are developed, but it does not provide any guidance on appropriate scientific justification for building more regulatory flexibility into analytical procedures. Postapproval changes to analytical procedures are burdensome for industry and consequently inhibit continuous improvement activities and innovation. In June 2018, the long-anticipated plan to revise ICH Q2(R1) was approved by the ICH Assembly,8 who in addition approved the creation of a new guideline (ICH Q14) on Analytical Procedure Development (analogous to ICH Q8 and Q11). An expert working group has formed that will finalize the concept paper for this combined topic (abbreviated as Q2(R2)/Q14) and a business plan by the end of November 2018. The combined topic ICH Q2(R2)/Q14 represents an opportunity to provide guidance on how to apply enhanced development approaches to analytical procedures and how to use the knowledge obtained to support routine use of © XXXX American Chemical Society
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DOI: 10.1021/acs.oprd.8b00366 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Regulatory Highlights
In June 2018, the ICH Management Committee approved the development of an ICH guideline for continuous manufacturing after the topic had been on the ICH “to do” list since 2014. Its final adoption was preceded by a debate involving industry and regulators from across the globe as to whether a new guideline was required or whether a Points to Consider or Q&A addendum to ICH Q8,1 Q9,2 Q10,3 or Q114 would be more appropriate. The current regulatory environment, as supported by ICH Q7,12 Q8,1 Q9,2 Q10,3 and Q114 and their supporting Q&As13,14 and Points to Consider, supports the introduction of new technologies through the use of QbD concepts, emphasizing science- and risk-based approaches to ensure product quality. Of note, specialized expert teams have been formed by the U.S. Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA) to foster adoption of innovative technologies including those needed to realize successful implementation of continuous manufacturing. In recent years, several white papers have been developed by industry and regulatory subject matter experts that seek to provide proposals for the quality and regulatory framework for continuous manufacturing.15−19 These papers highlight the broad applicability of many of the existing ICH concepts and QbD principles. However, to date there has been no systematic gap analysis of the existing ICH framework to clarify what additional elements might be required to support continuous manufacturing. In addition, some of the white papers fail to adequately address scenarios where processes may be a hybrid of batch and continuous steps and unit operations (semicontinuous processing). Because many concepts in existing ICH guidelines are already applicable to continuous manufacturing, it is hoped that the new ICH Q13 guideline will focus on only those areas where there is ambiguity or identified gaps. In the opinion of the authors, this could include guidance on topics such as batch definition and traceability, sampling and real-time release testing, process validation/verification, clarification of the role of models and GMP in the control strategy, and insights into control strategy presentation in the regulatory dossier. Guidance for the last of these may be of invaluable assistance, notably in situations where data-rich experimentation or innovative technologies have been employed as key elements of the control strategy. Finally, it may also be quite helpful to consider expectations for the conversion of batch manufacturing to continuous processes to facilitate these transitions. Overall, the expectations for assurance of reliable and predictive processing that is technically sound, risk-based, and relevant to product quality in a commercial setting are the same for batch and continuous processing. Therefore, identification of the most critical control elements from potentially dense processing data sets will be important to ensure that processes are efficiently maintained in a continuous state of control but not unnecessarily regulated when there is no impact on product quality. While is not yet clear which additional elements that are essential for continuous processing are currently absent from the existing ICH and regional guidelines and which elements pertinent to continuous manufacturing require further clarification, the ICHQ13 expert working group will certainly clarify these points as their first activity, and the authors encourage the team to seek opportunities for broad consensus and harmonization every-
potentially impact the ATP requirements. For routine use, analytical procedure performance should be confirmed to meet the ATP requirements, and continued verification/improvement should be considered throughout the life-cycle. The Step 2 version of ICH Q129 states that where there is an increased understanding of the relationship between method parameters and method performance, established conditions should be focused on method-specific performance criteria (e.g., specificity, accuracy, precision) rather than a detailed description of the analytical procedure. Such criteria could be derived either directly or indirectly from the ATP. The ICH Q2(R2)/Q14 topic has the potential to ensure that performance requirements of the analytical procedure are driven by the overall control strategy rather than through a set of generic mandatory validation expectations addressed at a single snapshot in time to support the life-cycle of the method. Furthermore, by demonstrating method understanding through presenting knowledge generated by applying enhanced approaches, this could facilitate development approaches that will reduce the risk (associated with data quality) incurred by postapproval changes to analytical procedures (as discussed in ICH Q129) and enable more efficient and science-based change management. The augmentation of ICH Q2(R1) and the creation of the new guideline ICH Q14 could, however, raise expectations on the amount of method understanding and validation data that are required without offering any useful flexibility to industry across the life-cycle. For example, the generation of an analytical procedure design spacethe method operable design region (MODR), defined as the combination of parameter ranges that have been evaluated and verif ied as meeting the ATP criteria for an analytical procedure10does not offer much useful flexibility in the manufacturing environment since most analytical parameters can be automatically set at tightly controlled target values. The use of “method performance criteria” (e.g., specificity, accuracy, and precision as defined in the Step 2 version of ICH Q129 and essentially the same as the ATP defined above) to drive flexibility within a given analytical technology (e.g., chromatography, spectroscopy) or between different technologies is where the real opportunity exists. Industry and regulators need to work together to define how a framework driven by scientific understanding and underpinned by sound knowledge management can be utilized to support such an approach. For example, Åsberg et al.11 describe a common type of flexibility sought that involves switching between HPLC and UPLC for the analysis of the drug Nexium, where the risk of generating nonequivalent data is low. The method performance criteria in this example were expressed in a single system suitability test.
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CONTINUOUS MANUFACTURING Continuous manufacturing technologies have been used for many decades within the oil and chemicals sectors and are becoming increasingly well-known within the pharmaceutical industry. Many NCEs are being developed using either flow chemistry for the API and/or continuous tablet manufacturing for the drug product, and biologics manufacturers are exploring the use of perfusion bioreactors as single-use disposable equipment in their manufacturing processes. Flow chemistry manufacturing processes can be cleaner, more flexible, and more efficient and can offer other advantages over traditional batch processing due to the enhanced control capability and the ease of scale-up. B
DOI: 10.1021/acs.oprd.8b00366 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Regulatory Highlights
acceptance criteria should have clinical relevance wherever possible. Such clinical relevance comes from understanding the impact of CQAs on safety or efficacy and can come from fundamental scientific understanding or from prior knowledge from related products. However, specification acceptance criteria (see ICH Q6A22 and Q6B23) can also be expected to be set on the basis of actual batch data. Such batch-databased acceptance criteria are determined by the variability of manufacturing (often from a few early batches) and may neither represent the true capability of the manufacturing process nor truly be linked to an attribute’s actual impact on safety or efficacy. When overly tight specifications based on limited data are set, there is a likelihood of batch failure, which can compromise the medicine supply. Where the impact of a given attribute on safety and efficacy is understood, variation beyond actual batch data can and should be acceptable when defining acceptance criteria. Such considerations are of great importance when considering change management of biological products, where quality rather than bioperformance equivalence is the main concern. Change management of biological products involves the informed assessment of selected critical aspects of the postchange product compared to the prechange product in terms of the characterized quality and the impact of quality attributes on safety and efficacy. Thus, the criteria applied for comparison of CQAs become vital. Regulators in the United States and Europe have recently been publishing their initial thoughts on whether and how statistical measures of similarity can be applied to quality attributes in a comparability assessment. Such statistical comparisons, if applied rigorously and driven by prior batch data relying on statistical similarity alone, could lead to very little attribute change being acceptable after a manufacturing change, irrespective of the actual impact of an attribute change. Such an “uninformed” approach could lead to setting of improper acceptance criteria that do not account for knowledge of attribute impact and also put in jeopardy the ability to optimize a process (e.g., for environmental impact or process safety) that has operated in the past with little variability. The European regulatory position was published as a reflection paper (https://www.ema.europa.eu/documents/ scientific-guideline/draft-reflection-paper-statisticalmethodology-comparative-assessment-quality-attributes-drug_ en.pdf) and was the subject of a workshop at the EMA in early 2018 (https://www.ema.europa.eu/events/workshopreflection-paper-statistical-methodology-comparativeassessment-quality-attributes-drug). The ability to discuss the pros and cons of using a statistical approach to similarity was very important. On the basis of these discussions, industry anticipates that the future approach to comparability assessment will allow a sponsor to make an informed proposal for comparability criteria for selected attributes needed to secure safety and efficacy (considering knowledge of the attribute impact). Some specification attributes will likely be more critical (and hence need closer similarity) than others. In addition, sponsors should be enabled to use all of the knowledge available to them (including from their development and manufacturing experience and from other products) when considering the impact of an attribute and proposing similarity criteria. In this way, informed clinical impact (rather than simple consideration of batch data for a single product)
where possible in order to lower potential barriers to global implementation.
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RECENT REGULATORY PERSPECTIVES ON CHANGE MANAGEMENTIMPACTS ON DRUG SUBSTANCE One of the fundamental principles of the regulation of pharmaceuticals is that the quality of the product provided to the patient across the product life-cycle is maintained equivalent to the product evaluated in pivotal clinical studies. With pharmaceutical products that contain small-molecule drug substances in solid form, this usually means focusing on maintaining the biopharmaceutical equivalence of the product through manufacturing changes, as other critical aspects of product quality are well-characterized by approved specification criteria. Conversely, the bioequivalence of a biological product can often be presumed on the basis of intravenous administration of biological products as solutions of the active substance. For such biological products, the focus of maintaining quality equivalence through the manufacturing life-cycle is on suitably assuring the comparability of CQAs of pre- and postchange drug product and drug substance. Recent regulatory perspectives on these matters have been published. First, the ICH has released a draft guidance (ICH M9)20 on the application of “biowaivers” (i.e., managing product change without the need for in vivo evaluation of pharmacokinetics) based on the biopharmaceutical properties of the active substance and product. This approach facilitates change management (in vivo studies are costly and take time to perform and report) and is based upon the Biopharmaceutics Classification System developed by Amidon and co-workers,21 which is currently used in several regions for change management of bioperformance. In this system, fundamental drug substance properties (solubility and permeability) are used to evaluate the degree of risk associated with manufacturing changes. Active substances classified as “highly soluble” are change-managed without recourse to in vivo evaluation. Thus, it is common for the manufacturing process of the drug substance to pursue delivery of the active moiety in a highly soluble form, e.g., as a salt or cocrystal, rather than as the “free” active moiety. Salt screening is often an activity that takes place early in pharmaceutical development to implement the desired form as early as possible. In addition, to pursue a biowaiver, the dissolution properties of the solid dosage form prepared from the active substance are evaluated. Rapid or very rapid release of the active moiety from the formulated product supports change management without in vivo evaluation. Again, decisions made by the process chemist can impact the relative rate of active release from a solid dosage form. Both the polymorph and particle size (achieved by crystal engineering approaches or particle reduction technologies) of a drug substance can impact its intrinsic solubility rate (but not the absolute solubility achieved at equilibrium). Specifications for drug substances frequently include acceptance criteria for particle size and polymorph when these attributes are expected to have an impact on product performance. In these circumstances, these criteria are important and clinically relevant, as they are focused on maintaining adequate release of the active substance from the formulated product. Specifications set for drug substances and drug products need to ensure the product’s consistent performance (safety and efficacy) for the patient, and ideally, specification C
DOI: 10.1021/acs.oprd.8b00366 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
Organic Process Research & Development
Regulatory Highlights
(10) Rignall, A.; et al. Analytical Procedure Lifecycle Management Current Status and Opportunities. Pharm. Technol. 2018, 42 (12), in press. (11) Åsberg, D.; Nilsson, M.; Olsson, S.; Samuelsson, J.; Svensson, O.; Klick, S.; Ennis, J.; Butterworth, P.; Watt, D.; Iliadou, D.; et al. A quality control method enhancement concept - Continual improvement of regulatory approved QC methods. J. Pharm. Biomed. Anal. 2016, 129, 273−281. (12) Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients Q7; ICH, 2000. (13) Quality Implementation Working Group on Q8, Q9 and Q10 Questions & Answers (R4); ICH, Nov 11, 2010. (14) Q11 Implementation Working Group. Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/Biological Entities) Questions and Answers, version 23; ICH, August 2017. (15) Allison, G.; Cain, Y. T.; Cooney, C.; Garcia, T.; Bizjak, T. G.; Holte, O.; Jagota, N.; Komas, B.; Korakianiti, E.; Kourti, D.; Madurawe, R.; Morefield, E.; Montgomery, F.; Nasr, M.; Randolph, W.; Robert, J. L.; Rudd, D.; Zezza, D. Regulatory and quality considerations for continuous manufacturing. May 20−21, 2014 Continuous Manufacturing Symposium. J. Pharm. Sci. 2015, 104 (3), 803−12. (16) Nasr, M. M.; Krumme, M.; Matsuda, Y.; Trout, B. L.; Badman, C.; Mascia, S.; Cooney, C. L.; Jensen, K. D.; Florence, A.; Johnston, C.; Konstantinov, K.; Lee, S. L. Regulatory Perspectives on Continuous Pharmaceutical Manufacturing: Moving from Theory to Practice. J. Pharm. Sci. 2017, 106 (11), 3199−3206. (17) C-SOPS Regulatory Working Group. Current Recommendations for Implementing and Developing Continuous Manufacturing of Solid Dosage Drug Products in Pharmaceutical Manufacturing; FDA docket FDA-2017-N-2697; Center for Structured Organic Particulate Systems, June 2016. (18) Innovative Manufacturing Technology Working Group. PMDA Views on Applying Continuous Manufacturing to Pharmaceutical Products, provisional draft; Pharmaceuticals and Medical Devices Agency, November 2017. (19) Innovative Manufacturing Technology Working Group. PMDA Views on Applying Continuous Manufacturing to Pharmaceutical Products for Industry, provisional draft; Pharmaceuticals and Medical Devices Agency, March 30, 2018. (20) Biopharmaceutics Classification System-Based Biowaivers M9, draft version; ICH, 2018. (21) Tsume, Y.; Mudie, D. M.; Langguth, P.; Amidon, G. E.; Amidon, G. L. Regulatory Perspectives on Continuous Pharmaceutical Manufacturing: Moving from Theory to Practice. Eur. J. Pharm. Sci. 2014, 57, 152−163. (22) Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances Q6A; ICH, 1999. (23) Specifications: Test Procedures and Acceptance Criteria for Biotechnological/Biological Products Q6B; ICH, 1999.
appropriately becomes the most important component of managing change. It is valuable to see the emphasis being placed on clinical relevance in the development of these regulatory positions. This is a topic at the forefront of regulatory science and is also being considered in the setting of impurity specifications (see the FDA Manual of Policies and Procedures (https://www.fda. gov/downloads/aboutfda/centersoffices/ officeofmedicalproductsandtobacco/cder/ manualofpoliciesprocedures/ucm590073.pdf) and dissolution acceptance criteria for pharmaceutical products, all of which matter to chemists and pharmaceutical scientists working in the pharmaceutical industry.
Andrew Teasdale* AstraZeneca, Macclesfield SK10 2NA, United Kingdom
Matthew Popkin GlaxoSmithKline, Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, United Kingdom
Ron Ogilvie Pfizer, Sandwich CT13 9ND, United Kingdom
Phil J. Borman GlaxoSmithKline, Medicines Research Centre, Gunnels Wood Road, Stevenage, Hertfordshire SG1 2NY, United Kingdom
Vincent Antonucci
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Merck & Co., Inc., Kenilworth, New Jersey, United States
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
E-mails:
[email protected]; ron.ogilvie@pfizer.com; phil.
[email protected];
[email protected].
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REFERENCES
(1) Pharmaceutical Development Q8(R2), Current Step 4 version; ICH, August 2009. (2) Quality Risk Management Q9, Current Step 4 version; ICH, Nov 9, 2005. (3) Pharmaceutical Quality System Q10, Current Step 4 version; ICH, June 4, 2008. (4) Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/Biological Entities) Q11, Current Step 4 version; ICH, May 1, 2012. (5) Borman, P.; Chatfield, M.; Nethercote, P.; Thompson, D.; Truman, K. The Application of Quality by Design to Analytical Methods. Pharm. Technol. 2007, 31 (10), 142−152. (6) Schweitzer, M.; Pohl, M.; Hanna-Brown, M.; Nethercote, P.; Borman, P.; Hansen, G.; Smith, K.; Larew, J. Implications and opportunities of applying QbD principles to analytical measurements. Pharm. Technol. 2010, 34 (2), 52−59. (7) Martin, G. P.; et al. Lifecycle Management of Analytical Procedures: Method Development, Procedure Performance Qualification, and Procedure Performance Verification. Pharm. Forum 2014, 39 (5). (8) ICH Assembly, Kobe, Japan, June 2018 (ICH press release). http://www.ich.org/ichnews/press-releases/view/article/ichassembly-kobe-japan-june-2018.html. (9) Technical and Regulatory Considerations for Pharmaceutical Product Lifecycle Management Q12, Step 2 version; ICH, Nov 16, 2017. D
DOI: 10.1021/acs.oprd.8b00366 Org. Process Res. Dev. XXXX, XXX, XXX−XXX
