Frank Diana

To ensure the quality of drug products and patient safety, pharmaceutical companies need to manage and justify changes in chemistry, manufacturing, and controls (CMC). Analytical methods are integral parts of CMC, and some common reasons to change analytical methods used in regulated environments include applying new analytical technologies and accommodating changes in chemical or formulation processes. When changes are made to analytical methods, pharmaceutical companies need to compare the new method and the existing method, and to demonstrate that the new method will provide equivalent or better performance to that of the existing method. 

There are two concepts related to comparing two analytical methods for the same test: analytical method comparability and analytical method equivalency. Chambers et al. considered that analytical method comparability refers to studies to evaluate similarities and differences in method performance characteristics between two analytical methods (i.e., accuracy, precision, specificity, detection limit, and quantitation limit), while analytical method equivalency is a subset of analytical method comparability and refers to studies to evaluate similarities between two analytical methods in regard to generating results for the same sample (1). In other words, analytical method equivalency evaluates whether the new method can generate equivalent results to those from the existing method. In a recent publication, Chatfield et al. suggested another way to differentiate these two concepts, where analytical method equivalency is restricted to a formal statistical study to evaluate similarities in method performance characteristics (2). In a United States Pharmacopeia (USP) stimuli paper, Hauck et al. also discussed other approaches to assessing equivalence such as “result equivalence” (3).

Unlike analytical method validation, where clear regulatory guidelines such as International Conference on Harmonisation (ICH) Q2, are available, there is little regulatory guidance on how or when to perform analytical method comparability or equivalency. In a draft guidance published by FDA in 2003, 

Comparability Protocols-Chemistry, Manufacturing, and Controls Information

, the agency stated that proper validation is required to demonstrate that the new analytical method will provide similar or better performance compared with the existing method. On the other hand, the agency also stated that whether an analytical method equivalency study is needed and how to perform it will depend on the extent of the proposed change, type of product, and type of test (e.g., chemical, biological) (4). Another relevant document on analytical method comparability is 

 General Chapter <1010> “Analytical Data-Interpretation and Treatment,” which was first published in 

In this General Chapter under the section of Comparison of Analytical Methods, statistical-based approaches to compare method precision and accuracy are discussed with some examples. Most recently, an FDA draft guidance on analytical method validation was issued in 2014 (6), and the concept of analytical method comparability is discussed. However, in this draft guidance, the use of formal statistical studies is recommended whenever a change is made to an analytical method that has stability indicating properties. While this approach is valid and rigorous, the draft guidance does not consider less formal but suitable alternatives for method comparison assessments by leveraging a quality- and risk-based assessment strategy. 

Based on a 2003 Pharmaceutical Research and Manufacturers of America (PhRMA) workshop, Chambers et al. published a position paper on analytical method equivalency (1). The authors summarized industry practice at the time and provided perspectives on when and how analytical method equivalency should be performed. The authors noticed that a wide range of different practices were used by pharmaceutical companies for analytical method equivalency, including only validation of the new method, side-by-side result comparison against pre-defined acceptance criteria, as well as formal statistical demonstration. Such wide variations are clearly not preferred by either regulatory agencies or the industry and may lead to delay in regulatory review. 

The International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) is a pharmaceutical industry association formed in 2010 with the mission of advancing science-based and scientifically driven standards and regulations for pharmaceutical and biotechnology products worldwide. In 2011, an IQ working group, Analytical Method Comparability, was formed to assess current practices by IQ member companies and to recommend best practices on analytical method comparability for analytical methods used in regulatory environments. Harmonized approaches on analytical method comparability, if in existence, will not only improve industry compliance to ensure product quality and patient safety, but also align with quality-by-design (QbD) principles and may also reduce the regulatory filing burden on method change control, which in turn may encourage innovation in pharmaceutical analyses. 

As a starting point, the working group purposely limited its initial scope to changes in high-performance liquid chromatography (HPLC) assay and impurities methods in registration and post-approval stages. The rationale for this decision is that new developments in instrumentation and column technologies led to the birth of ultra-high pressure liquid chromatography (UHPLC) (7). An HPLC impurities analysis that used to routinely take 30 min or more to perform by conventional HPLC can now be achieved within a few minutes by UHPLC with better sensitivity and less solvent consumption. Though UHPLC has witnessed increasing popularity by pharmaceutical companies for new products, implementation of UHPLC in legacy products has been slow, partially due to the heavy regulatory filing burden upon method change control. CMC related changes, including changes in analytical methods, are regulated most stringently in registration and post-approval stages. While HPLC assay and impurities methods were the starting point, it is reasonable to anticipate that the general concepts developed in this position paper can be applied to other analytical methods. 

The working group conducted a survey on analytical method comparability among IQ member companies, and the results are summarized in the next section. Based on the survey results and discussions among working group participants, the working group recommends a risk-based approach for analytical method comparability of HPLC assay and impurities methods in registration and post-approval stages. The views in this article are those of the authors and do not reflect the official policies of their respective companies.


A survey of industry practice on analytical method comparability for HPLC assay and impurities methods in registration and post-approval stages was carried out among IQ member companies. The survey contained 17 questions covering the following aspects with regard to industry practice on analytical method comparability: background and internal governing documents, regulatory interactions, general practice, quality assurance (QA) and statistician involvement, and detailed procedures. Nine questions were required to be answered as a “Yes” or “No” response, with the option to provide additional written details; written responses were required for the remaining eight questions. A total of 19 responses were received from 15 IQ member companies. Three companies provided multiple responses from different divisions within the same company. The survey results were discussed during subsequent working group meetings. Though this is a relatively small survey and the percentage numbers undoubtedly have a large margin of error, the authors believe that the results, described in the following section, provide a meaningful picture of current industry practice on analytical method comparability for HPLC assay and impurities methods. 

Background and internal governing documents


With regard to the definitions of analytical method comparability and analytical method equivalency, 68% of participants thought that these terms represented two different concepts. From subsequent working group discussions, it was clear that most participants agreed with Chambers et al. that analytical method equivalency is the evaluation of whether equivalent results can be generated by two different analytical methods; analytical method comparability is a broader and less defined term (1). Meanwhile, some participants also indicated that analytical method equivalency should be restricted to a statistical demonstration of equivalence, as described by Chatfield et al. (2).

With regard to internal governing documents, 79% of participants indicated that there are no specific standard operating procedures (SOPs) or guidelines on analytical method comparability within their company. On the other hand, 53% of participants mentioned that there are some general discussions on analytical method comparability within their company’s change control policies or SOPs. Some participants, for example,  indicated that it is part of their risk assessment workflow to evaluate if an analytical method equivalency study should be performed when a change is made to an analytical method.


With regard to regulatory interactions, 68% of participants indicated that they have had successful regulatory reviews of analytical method comparability packages for a registration filing or post-approval change. Additional written comments showed that a complete analytical method comparability package typically includes method information, method validation, equivalency data, and the reason for the change. Meanwhile, 47% of participants indicated that they have received questions on analytical method comparability from health authorities. Additional written comments suggested that regulatory authorities have expectations that analytical method equivalency needs to be demonstrated when changes are made to an analytical method; however, the feedback also indicated that there were no consistent requirements on what kind of data package should be provided. In general, more data are required when the method change is more significant.

In one example, when an HPLC assay method was replaced with an UHPLC assay method, method equivalency was demonstrated using a side-by-side comparison of both methods for three lots of material; this approach was accepted by FDA. In this example, the change was considered minor as the separation mechanism (i.e., reversed-phase HPLC) was not changed. In another example, however, when a normal-phase HPLC assay and impurities method was replaced by a reversed-phase HPLC method during registration stability testing, several questions were received from FDA requesting detailed explanations due to the significant difference in methodology, which impacted the impurity profile and the specifications. The agency requested detection limits and quantitation limits of all impurities by both methods and full disclosure of the impurity profiles by both methods on all lots tested. To help justify the change, the company also provided overlapping stability data for 3-6 stability time points to demonstrate that the reversed phase HPLC method provided better characterization of the drug product.


With regard to general practices, all participants stated that in addition to validation, they would also evaluate whether an analytical method comparability or equivalency study is needed when a change is made to an analytical method, while 63% of participants specified that not all method changes will need a comparability or equivalency study. From additional written comments, it was clear that risk-based approaches are adopted by most companies when evaluating whether an analytical method comparability or equivalency study is needed for method changes. The risks are typically evaluated based on the types of the changes, and in general, the more significant the change, the more likely a comparability or equivalency study will be needed. 

For example, as indicated by some participants, neither validation nor equivalency will be necessary for compendial HPLC method changes if the changes are within the ranges allowed in the 

 General Chapter <621> “Chromatography.” For non-compendial HPLC methods, such as those included in a new drug application (NDA) filing, no equivalency study will be needed if the change is within the established method robustness ranges. On the other hand, a comparability or equivalency study is typically required if the changes are outside of these ranges, such as a change in liquid chromatography (LC) stationary phase chemistry or a change in detection technique (e.g., from ultraviolet to mass spectrometry). Some companies also evaluated the risks based on the stage of the development. One participant mentioned that equivalency studies are performed for any changes to an HPLC method in post-approval stages.

If an analytical method comparability or equivalency study is deemed necessary, different practices still exist amongst the participants. A majority of participants (74%) agreed that, in addition to validation of the new method per ICH guidelines, a simple side-by-side comparison of representative batch results generated by both methods against pre-defined acceptance criteria (some companies referred this practice as cross-validation or as a bridging study) is usually sufficient. A more conservative practice (16%) is a demonstration of method equivalency through formal statistical analysis. One participant indicated that whether such a formal statistical analysis is necessary will also be evaluated based on the types of the changes as part of the risk assessment workflow. Another less common practice  (5%) is to conduct a full validation of the new method; the two methods are considered equivalent if they are both validated. 


With regard to quality assurance (QA) and statistician involvement, 68% of participants indicated that QA is involved in analytical method comparability or equivalency studies, such as approval of study protocols, while only 26% indicated that statisticians might be involved. One participant indicated that statisticians are involved in the design of the equivalency study, setting acceptance criteria, data evaluation, and report writing; while other participants stated that statistician assistance is only required when it is deemed necessary by analytical scientists.


With regard to detailed procedures, though the survey was on analytical method comparability for HPLC methods, responses from almost all participants were only focused on analytical method equivalency. This suggested that analytical method equivalency (i.e., demonstration of no practically significant bias in mean results) is the primary goal when a change is made to an HPLC method. Most participants did not use formal statistical approaches, but for those who did, statistical approaches are used throughout the study to ensure a statistically meaningful outcome.

An analytical method equivalency study typically consisted of acceptance criteria, study design (sample selection, sample size, and test plan), data evaluation, and documentation. With regard to acceptance criteria, most participants started with generic acceptance criteria derived from internal SOPs on analytical method validation or method transfer, such as 1.5-3.0% for assay, and 10-30% relative for impurities (or an absolute difference, such as 0.03%, for levels close to quantitation limits). Such acceptance criteria could be loosened or tightened based on the specific method and product involved (e.g., product types).

On the other hand, some participants indicated that a method specific criterion will be set based on the statistical evaluation of the precision of the method and the acceptance criteria of the relevant product specifications. With regard to study design, representative batches are typically used, with spiking of impurities if necessary. Some participants also suggested that stability samples over a few time points could be used (cross-over testing), though this practice was discouraged by Chambers et al. to avoid generating concerns of regulatory compliance.

A wide range of different practices exist among participants in terms of sample size (number of batches) and test plans. Some examples include using six replicate preparations of one or two batches, three replicate preparations of three batches in three runs (fresh reference standard preparations for each run), and one preparation for each of 20-30 batches, etc. Some participants indicated that statistical approaches are used to determine sample size (statistical power calculation based on acceptance criterion and method precision) and test plan (evaluation and control of other factors not related to the change). Some of these statistical approaches were discussed by Borman et al. (8). 

With regard to data evaluation, most participants simply compared difference in mean results against pre-defined acceptance criteria, while some participants indicated that a statistical test will be used. Concerning the specific statistical tests, the two one-sided t-test (TOST) is most often used (9), while the two-sample t-test is also used by some participants. With regard to documentation, most participants use a pre-approved study protocol and provide a study report once the study is completed.

In summary, it is fair to say that compared to analytical method validation, analytical method comparability or equivalency is a more science-driven and less regulated field. The survey results show that risk assessments are commonly performed by pharmaceutical companies to evaluate the impact of the changes, including whether an analytical method comparability study is necessary. If analytical method comparability is deemed necessary, different practices exist among pharmaceutical companies on how to perform the study.Though formal statistical approaches are used by some companies to provide a statistical meaningful declaration on whether the two methods were equivalent, a simple side-by-side comparison against pre-defined acceptance criteria remains the most popular approach for changes made to HPLC methods. On the other hand, the survey results also show that though regulatory authorities have expectations that analytical method equivalency needs to be demonstrated when changes are made to an analytical method, there seems to be no consistent requirements on what kind of data package should be provided. In general, more data are required when the extent of the change is more significant.

Overall, the survey results suggest that risk-based approaches should be adopted for analytical method comparability. In other words, whether an analytical method comparability or equivalency study is needed and how it is performed should be decided based on the risks associated with the changes. In the FDA draft guidance on comparability protocols, the agency states that “The need and plan for providing product testing to compare the two (analytical) procedures could vary depending on the extent of the proposed change, type of product, and type of test (e.g., chemical, biological)” (4). This statement suggests that risk-based approaches are expected by FDA as well. In the next section, a risk-based approach for analytical method comparability for HPLC assay and impurities methods in registration and post-approval stages is proposed based on the survey results and the subsequent working group discussions.

A risk-based approach for analytical method comparability


  When a change is made to an analytical method, a risk assessment should be performed to evaluate the potential impact. Though analytical method equivalency (i.e., no practically significant bias in mean results) is an important factor, other method performance characteristics, such as precision, should be evaluated as well. Impact on method performance depends upon the nature of the method as well as the type and the extent of the change. With regard to HPLC, the mechanistic understandings of both thermodynamic and kinetic aspects of HPLC separation processes have been well developed in the past few decades. In the same time period, improvements to LC instrumentation and column technologies have made HPLC one of the most reliable techniques in analytical laboratories around the world. The knowledge of HPLC separation and the reliability of modern HPLC instruments have enabled analytical scientists to better understand the potential impact on method performance from certain types of changes to HPLC methods. Therefore, changes to HPLC methods could be categorized based on the risks associated with the changes (e.g., low risk, medium risk, or high risk). These changes would be accompanied by a commensurate amount of work to assess comparability, as depicted in 

Small   changes to the high performance liquid chromatrography (HPLC) operating parameters within accepted ranges (e.g. 

 <621> or within established   method robustness ranges).

Changes   to the HPLC operating parameters outside of low risk ranges, but not   involving any change to the underlying principles of the existing analytical   method (e.g. column chemistry).

Changes   to the underlying principles of the existing analytical method (e.g. liquid chromatrography-ultraviolet (LC-UV) to   liquid chromatography-mass spectrometry (LC-MS)). 

Low-risk changes are small changes to the HPLC operating parameters, such as changes allowed by USP General Chapter <621> “Chromatography” for a compendial HPLC method or changes within the established robustness ranges in analytical method validation (10-11). Two examples of low-risk changes are the column temperature within ±10˚C or the flow rate within ±50% from the target values of a compendial isocratic HPLC method. In low-risk situations, additional method validation and comparability studies should not be required, as the changes have already been assessed within the initial validation experiments and any impact is generally understood and predicted based upon mechanistic models.  

Medium-risk changes are changes to the HPLC operating parameters outside the established robustness ranges evaluated during the method validation, but do not involve any change to the underlying principles of the existing analytical method. An example of a medium-risk change includes an HPLC column change to a smaller particle size and/or shorter column length or diameter with appropriate scaling considerations to speed up a gradient HPLC method (i.e., conversion from HPLC to UHPLC methodology without appreciable change in separation mechanism). Other medium-risk changes might include changes in column stationary phase from C18 to C8 or a change in organic solvent in mobile phases from acetonitrile to methanol as long as the characteristics of method performance (e.g., specificity, accuracy, precision) remains practically unaffected, which can be confirmed through successful completion of associated method validation activities prior to implementation of any comparability studies.  

Finally, high-risk changes are those changes that either involve a change to the underlying principles of the existing analytical method or a change in a critical method parameter that has high impact to method performance. Some examples of high risk “underlying analytical principle” changes include conversion of a microbiological potency method to a reversed-phase HPLC potency method, a normal-phase HPLC method to a reversed-phase HPLC method, a UV detection to a mass spectrometry detection, or an assay method by HPLC to a near-infrared (NIR) real time release method. 

The HPLC risk categorization examples discussed previously should serve as a general guideline for risk assessment, and it is recommended that each HPLC method change should be evaluated and categorized on a case-by-case basis. Application of QbD principles to analytical methods has been discussed recently (12-16) and can assist method change assessments. Identifying critical method parameters through a comprehensive risk assessment is an integral step in an analytical QbD workflow. The knowledge gained through analytical QbD should also be applied in risk assessment and categorization when a change is made to an existing HPLC method. For example, a change in detection wavelength for an HPLC impurities method may be an example of a medium-risk change or a high-risk change. If all impurities are quantified by calibration with external standards of each impurity, the change should be of medium risk; however, quantification of impurities based upon response-corrected areas could potentially represent a high-risk change if relative response factors are assumed to be 1.0, a common industry practice for impurities with calculated response factors between 0.8-1.2 (11). In such a situation, a change in detection wavelength could lead to an appreciable bias in impurity results. 

For changes in the low-risk category, potential impact on method performance is usually low. The risks will be further guarded by system suitability evaluation, such as the resolution between critical pairs, performed in each HPLC run; therefore, low-risk changes can take place without additional studies. Neither additional validation nor analytical method comparability studies are necessary. This approach agrees with the requirements from USP and ICH.

For any changes beyond low risk, justification and validation of affected method parameters are generally required. Additionally, both health authorities and pharmaceutical companies expect that analytical method comparability or equivalency studies should be performed. A question of interest is whether a formal statistical demonstration of analytical method equivalency is always necessary. Chambers et al. discussed the differences between validation and equivalency, and emphasized that validation alone cannot guarantee equivalence because validation experiments are not designed to detect small bias between mean results  (1). This statement is fair, but it should be emphasized that the risk of non-equivalency decreases as successful validations of both methods have been completed.

For medium-risk changes, where underlying principles remain the same for both methods (e.g., reversed-phase HPLC methods with UV detection), the risk of having a practically significant difference in mean results is rather low when both HPLC methods are successfully validated in the same manner with the same pre-defined criteria. For example, a co-elution of two impurities would potentially fail equivalency, and would fail validation on method specificity as well. In addition, validation studies also confirm improvement or similarities of other method performance characteristics, such as precision. Therefore, the authors recommend that a side-by-side comparison against pre-defined acceptance criteria should be sufficient for medium-risk changes. Though not a formal statistical approach, the side-by-side comparison study should be designed carefully. Acceptance criteria could be based on internal SOPs on analytical method validation or method transfer. Generic limits of 1.0-2.0 % for drug substance assay, 2.0-3.0 % for drug product assay, and 10-30% relative for impurities can be considered as a starting point. Such acceptance criteria can be loosened or tightened based on the specific method involved. Representative batches, preferably covering a wide range of results, should be chosen for the study. Spiking impurities should be considered, if no suitable batches can be identified containing the impurities at appropriate levels (e.g., the specification limit). QA should be consulted if active GMP samples, such as GMP release and registration stability study samples are considered to be used for comparison. Material limitation is usually not a concern at registration and post-approval stages, and typically three batches or more should be used for the study. Factors affecting intermediate precision and/or reproducibility, such as analyst, instrument, and environment, should be included in the study if possible. For example, a common test plan is triplicate preparations of three batches in three runs, with each run using fresh standard preparations, and altering factors of analyst, instrument, and/or environment as well. 

Because high-risk changes usually involve a change to the underlying principles between the existing and the new methods, the risk of being non-equivalent is high, even with successful validations of both methods. In some cases, the validation plan and acceptance criteria between the two methods have to be modified to accommodate the changes to the underlying principles. For example, the specificity evaluation for a NIR assay method will be different (test procedure and acceptance criterion) from that for an HPLC assay method. Therefore, the authors recommend that statistical principles should be followed throughout the study and a formal statistical assessment of the data should be applied for high-risk changes to ensure a statistically meaningful outcome. This includes selection of the acceptance criterion, design of the test plan, data validity evaluation (e.g., outlier testing), and an equivalency test (e.g., TOST). Note the two-sample t-test should not be used as an equivalence test (or as acceptance criteria for a side-by-side comparison) as it is designed to detect a difference of means, not to establish whether the means are equivalent based on a measure of practical importance (1, 9). Besides method equivalency, other method performance characteristics, such as precision, should also be evaluated (though note that a large difference in precision is likely to cause the TOST to fail (9). In other words, an analytical method comparability study should be performed for high-risk changes. Detailed procedures for statistically guided analytical method comparability and equivalency studies can be found in the USP General Chapter <1010> and some external scientific publications as well  (2, 5, 8, 9, 17). Due to the involvement of advanced statistics, statistician assistance should be sought. The proposed analytical comparability activities for a specific HPLC risk categorization does not preclude a more stringent assessment being applied (e.g., if the analytical method is to be applied in a situation where even a very small difference in means could be problematic). 


Analytical method comparability or equivalency remains as a more science-driven and a less regulated field, and different practices currently still exist among pharmaceutical companies. Harmonized practices will not only improve industry compliance to ensure product quality and patient safety, but also reduce the regulatory filing burden on method change control, which in turn will prompt innovation in pharmaceutical analysis. In this position paper, the IQ working group on analytical method comparability recommends a risk-based approach for analytical method comparability for HPLC assay and impurities methods in registration and post-approval stages. It is the working group’s hope that this paper can help to stimulate further discussions among the industry and health authorities to define acceptable industry practices for assessing analytical method comparability or equivalency in general.


This position paper was prepared with the support of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ). IQ is a pharmaceutical industry association formed in 2010 with the mission of advancing science-based and scientifically driven standards and regulations for pharmaceutical and biotechnology products worldwide. Visit www.iqconsortium.org for more information.

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Hafez Abdel-Kader is a director at Sanofi; Mark Argentine is a senior research advisor, and Jeff Hofer is a research advisor, both at Eli Lilly; Nancy Benz is a director at AbbVie; Rick Burdick is a quality engineering director at Amgen; Marion Chatfield is a manager statistician at GlaxoSmithKline; Frank Diana is a vice-president at Endo Pharmaceuticals; Hui Fang and Yuan Huang are both senior scientists at Eisai; Shreekant Karmarkar and Lakshmy M. Nair are both senior research scientists at Baxter; Theresa Natishan is a director at Merck; Andrea M. Pless is an associate director at Teva; Qinggang Wang* is a principal scientist at Bristol-Myers Squibb, qinggang.wang@bms.com; and Zeena Williams is a senior associate director at Boehringer Ingelheim. * To whom all correspondence should be addressed.

Articles

A risk-based approach is recommended for analytical method comparability for HPLC assay and impurities methods.

Analytical Method Comparability in Registration and Post-Approval Stages: A Risk-Based Approach

	The International Consortium on Innovation and Quality in Pharmaceutical Development (IQ) formed in 2010 is an association of over 25 pharmaceutical and biotechnology companies with a mission to advance science-based and scientifically-driven standards and regulations for medicinal products worldwide. In the June 2012 issue of 

, a paper was provided which described the IQs Good Manufacturing Practices (GMPs) in Early Development working group (1). This working group (WG) is focused on developing recommended approaches to applying GMPs in several areas of Early Phase CMC development activities (e.g., Phase 1 to Phase 2a). A key premise of the GMPs in Early Development WG is that existing GMP guidance documents for early development are vague and that improved clarity with options to meet GMP expectations would be helpful. Although more prescriptive guidance is not advocated, the sharing of best practices in this paper is done herein to advance innovation in drug product development by improving cycle times, while maintaining appropriate product quality and ensuring patient safety.

	A consequence of the absence of clarity surrounding early phase GMP guidance has been varied interpretation and application of existing GMP guidance within different companies and regulatory bodies according to their own culture and risk tolerance. Internal debates often result in conservative "one-size-fits-all" interpretations that rely on International Conference on Harmonization (ICH) guidelines that are relevant to commercial product development and do not distinguish differences in practices between early development and later-stage development (i.e., Phase 2b and beyond). A key driver of the IQ WG, therefore, has been to collectively define the minimum acceptable practices within industry regarding GMP expectations in early development that allow for added flexibility and that are consistent with existing guidance and statutes (2, 3).

	As outlined in the introductory paper to this series, the efforts of the GMPs in Early Development WG have been focused into the following four areas of Chemistry, Manufacturing, and Controls (CMC) activities: Analytical Method Validation, Specifications, Drug Product Manufacturing, and Stability (1). The initial scope of these efforts has been limited to small-molecule development, which support First in Human (FIH) through Phase 2a (proof-of-concept) clinical studies.

	A series of whitepapers describing a recommended approach to applying GMPs in each of these areas is being published within this journal. In past editions, approaches to Analytical Method Validation, and Manufacturing to support health authority submissions were provided (4, 5); approaches to Specification setting will be published in the October 2012 issue of 

	In this paper, Part IV, stability needs are discussed. During early drug development, stability data can be generated to support the manufacture and storage of clinical products to meet regulatory expectations for Investigational New Drug (IND), Investigational Medicinal Product Dossier (IMPD), or Clinical Trial Application (CTA) filings and to help understand the product and process. The authors illustrate some best practices for stability to support early phase clinical trials in this paper; however, some companies may choose to do more, or possibly less, at their discretion and with appropriate science- and risk-based justifications suitable for the phases and purposes of development. The GMP quality systems (e.g., chamber qualification, standard operating procedures) used to support such studies are not the focus of this paper.

	Stability studies to support early phase development

	Early in development, pharmaceutical research organizations develop products with a primary focus on patient safety. Data are generated at appropriate storage conditions to demonstrate or support the stability of the drug substance and product to assure product quality through the clinical study period. Guidance documents are available to indicate the type of information needed to support clinical trials (3, 6–8). Although ICH stability guidelines outline the stability data needed to support storage conditions and shelf life for commercial submissions, these guidelines are not applicable to early stages of development when less is known about new drug substances and products (9). However, there must be appropriate data to support storage of the products being proposed for clinical use.

	If a product is intended for human use, the concepts of cGMPs apply. For stability, this application often results in a written stability study plan or protocol, fit-for-purpose test methods, traceable and reliable documentation, and appropriate SOPs. Most compounds in early development end up being discontinued, for safety and/or efficacy issues and/or inadequate commercial viability. Therefore, efficiently assuring the quality of products being used in early human clinical trials is a challenge facing every pharmaceutical research organization involved in early trials. The common challenges faced in supporting drug substance (also referred to as API) and drug-product stability are discussed here. The authors offer some risk-based approaches for collecting data for small molecule, solid oral dosage forms used in Phase 1 and Phase 2a clinical trials, in hopes of guiding companies and health authorities towards harmonized strategies and best practices.

	In early phase development, CMC requirements include generation of appropriate stability data at suitable storage conditions to support filing the IND (or IMPD/CTA) and use of the clinical material through the end of the clinical study. These scientific and regulatory objectives for stability must be met while at the same time minimizing nonvalue-added operational expenses. Several factors from a business, regulatory, and scientific perspective need to be taken into account when designing early phase development stability studies:

		The risk tolerance of the sponsoring organization and their approach to the scientific mitigation of the risks.

		The inherent stability of the drug substance or product, and prior product, process and stability knowledge.

		The regulatory environment in the countries where the clinical trial will be conducted. For example, some countries may request stability data on multiple batches or actual clinical batches or may not accept extrapolation to justify use-date assignments.

		The projected future use of the product. Development teams may have some idea of the likelihood that a project will continue into Phase 2b. If a product is expected to be used for many months or multiple years through several development phases, then a use-date extension proposal based on additional long-term data may be necessary and further knowledge gathering may be warranted (3). This information may influence the scope of the initial stability study in the form of additional time points, additional conditions, and/or additional tests.

	Considering these factors, the industry must work to balance the perceived expectations of the regulators in the countries where clinical trials will be conducted using a science- and risk-based approach to generating and providing stability data in the regulatory filings.

	Discussed in this article are recommendations with regard to generating stability data for drug substance and solid oral dosage forms used for Phase 1 and Phase 2a (early phases of development). This paper presents a framework and guiding principles to this end. The examples presented are not meant to be a "how to" guide, but rather illustrations of the principles being discussed. Other study designs and conditions may also be feasible with the appropriate justification.

	The product development efforts for early clinical supplies often are simple formulations with limited development history. The early small-molecule oral products can be placed into one of two categories: drug-substance (DS) based products and formulated products. DS-based products include the use of neat DS (e.g., powder-in-bottle [PIB], powder-in-capsule (PIC), or DS shipped in bulk to clinical sites for on-site compounding). These products almost always have the same stability characteristics as the bulk DS, and DS stability data may be used to support the product use dating. Formulated products can be powders formulated with excipients, capsules filled with formulated granulation, or a tablet formulation. These formulations take more effort and are normally used because of a specific clinical need, a shortcoming of the DS-based product, or a desire to use the same formulation in Phases 1 and 2 studies. In most cases, they will be fairly simple formulations meant to have a short lifecycle. If the product advances further into development, more elegant formulations will need to be developed. Not covered in this paper are formulations that are extemporaneously prepared at the clinical site. These formulations are consumed quickly and long-term stability studies are not warranted.

	In the following sections, DS and drug product (DP) stability considerations for early development are discussed.

A representative batch of DS, or DP, is one that is expected to have similar stability to the batches used in clinical production, based on a science- and risk-based assessment of attributes expected to influence stability and knowledge obtained during development. Often non-GMP or GLP (good laboratory practice) DS batches are manufactured first and placed on stability to support a variety of product development activities. These batches often are representative of GMP batches from a stability perspective and can be used to establish an initial retest period for the DS and support a clinical submission. Stability data included in the CMC section are limited at this stage of development (5). The DS batch used for Phase 1 clinical supply manufacture may be placed on stability concurrent to the clinical trials, if additional study is warranted.

	In early development, it is common for the manufacturing process to be improved as a normal part of development. As the DS process evolves, an evaluation is needed to determine whether the initial batch placed on stability is still representative of the improved process. The authors advocate a science- and risk-based approach for deciding whether stability studies on new process batches are warranted. The basic principles are discussed below and further details of such an approach can be found in Ref. 10 and its citations (10).

	The first step is to determine which DS attributes have an effect on stability. This step can be completed through paper-based risk assessments, prior knowledge, or through a head-to-head short-term stability challenge (as discussed in the next section) comparing the new batch with the earlier batch. If the revised process impacts one or more of these stability-related quality attributes, the new batch should be placed on stability. If the revised process does not result in a change to a stability-related quality attribute, the new batch does not need to be placed on stability. There are certain changes that almost always require a new study. Different polymorphic form, counter-ion, or solvate forms of a compound cannot be assumed to have the same rates of degradation or the same degradation pathways. Therefore, these changes will almost always require new stability data (11).

	Typical changes encountered in early development include changes in synthetic pathway (including a change in the order of the bond forming steps), batch scale, manufacturing equipment or site, reagents, source materials, solvents used, and crystallization steps. In most cases, these changes will not result in changes in DS stability. A common misconception is that changes to the impurity profile will adversely affect stability. Most DS impurities, particularly organic impurities, are essentially inert and have no effect on DS stability. Some impurities, such as catalytic metals, acidic or basic inorganic impurities, or significant amounts of residual water or solvents, may affect stability, and if the new process changes the level of these impurities, additional stability may be warranted. Packaging changes of the bulk material to a less protective package may require stability data to support the change. Likewise, changing to a more protective package in order to extend the retest period, beyond what the original representative batch study could support, may require additional data in the new package.

	Physical attributes that may impact stability include particle size/surface area, the degree of crystallinity/amorphicity, polymorphic form, hydrate form, and moisture content. If a new process changes any of these attributes, a risk assessment is recommended to determine whether additional stability is warranted. In some cases, short-term accelerated or stress stability data can help decide if these attributes are in fact stability related quality attributes. The concepts detailed in the above two paragraphs attempt to differentiate major and minor changes and may result in different stability strategies to support these changes.

	A risk assessment may help to determine whether the current batch is sufficiently representative. Alternatively, additional data may be needed when the batch is not representative or when there is substantial doubt after the assessment.

Drug-substance stability data collection. 

Although the stability testing practices and the amount of collected data vary from company to company, three commonly used approaches are discussed here. One is that an early, representative DS batch is placed under real-time and accelerated conditions (e.g., 25 °C/60% RH and 40 °C/75% RH) and stability results for a few time points (e.g., 1–6 months) are generated to support an initial retest period (e.g., 12 months or more). If needed, the stability study can be continued to extend the retest period or the GMP material can simply be retested, as needed, as part of a retesting program commonly used for manufacturing components.

	The selected analytical tests for stability studies should cover the quality attributes related to stability. Typically, these tests would include impurities and description and may include assay. Chiral purity, polymorphic form (e.g., x-ray), and water content should be tested, as appropriate. It may not be necessary to perform all tests at every time point depending on the purpose of the test.

	A second approach is to use high stress conditions with a short time such as a high temperature and high humidity (HT/HH) model. For example, the DS is stored at 70 °C/75%RH in open and closed containers, while monitoring the chemical and physical stability up to three weeks. The chemical stability results are used to extrapolate the initial DS retest period up to 18 months, more or less if justified. The extrapolation is based on the principle of the classic Arrhenius relationship between temperature and the reaction (degradation) rate, assuming a pseudo-zero order reaction. It is a simple and fast prediction of DS stability (12). This approach is most applicable for DS that is considered to have good physical and chemical stability as demonstrated during drug discovery. Acceptance of this approach has been gained in a number of filings.

	A third approach is the use of stress studies at several conditions coupled with modeling, such as the Accelerated Stability Assessment Program (ASAP) (13). ASAP combines an accelerated aging protocol with a humidity-corrected Arrhenius equation to provide an early prediction for DS and DP use period. It involves statistical analysis for more complex modeling of non-single order kinetics of degradation in DS and DP, and it produces faster and reliable predictions of chemical stability. For DS or DP with potential chemical stability challenges, this approach can be very useful to define appropriate storage condition and use period within a relatively short time to enable progressing early development programs. More importantly, ASAP has potential for a broader scope of stability assessment for developing control strategy of DP stability, such as long-term stability prediction and packaging requirements in implementing QbD for commercialization. ASAP has been used by companies as part of regulatory filings in multiple countries and has provided the basis for formulation, packaging, and moisture content justifications. There is an ongoing dialog between industry and regulatory agencies about these newer ways for industry to meet its obligations with respect to assuring the acceptability of products at the end of their shelf lives.

	The knowledge gained from these studies can then be used to: support storage conditions and initial retest period assignments; design future stability studies; assess the impact of temperature excursions; and select packaging. The results can also be used to establish the initial use period for DS-based products (e.g., PIB or PIC). The accelerated or stress approaches may save time in arriving at a first estimate of a material's stability.

	The retest period derived from these types of accelerated or stress studies can be later verified by placing the first clinical batch into real-time stability studies under ICH accelerated and long-term conditions. Future extensions of the retest/use period can be based on real-time data.

Drug substance stability data, commensurate with the stage of development, can be generated to support use of the DS to manufacture clinical supplies through a system using retest dates. When a longer retest period is needed, the extensions are most commonly handled either through a stability program or through a batch-specific retest program. Wording may be provided in filings to outline how the retest period will be extended in the future. If using stability data from the second (HT/HH) or the third approach (ASAP), a retest period is extrapolated from the Arrhenius equation or moisture corrected Arrhenius equation (12). Stability testing also is used to support use period dating of simple DS-based products.

	Design of drug-product stability studies for early development

As noted earlier, early stage clinical supplies often are simple oral formulations or powder-in-bottle or powder-in-capsule. Stability studies at this early stage need to support the use of the product in the clinical studies and to facilitate further development. Unless a specific formulation is required for early phase studies (e.g., due to poor solubility, poor bioavailability, the need for once-a-day formulations, or the need for a sterile injectable formulation), a simple oral solid-dosage form is typically employed. For the DS in capsule or bottle, stability of the DS will support early stage development, however, the clinical supply may be placed on stability (e.g., retained samples) and tested, if necessary. The study would continue through completion of the clinical study and could also be monitored at later time points to increase product knowledge, if appropriate.

	For formulated oral solid-dosage products, preformulation and process development studies can be performed to define the initial formulation. These studies will also provide initial stability information on the DS and its compatibility with excipients, moisture, processing conditions, and so forth. At this stage, a development batch (non-GMP) may be manufactured and placed on stability. If this batch is representative of the clinical supply (same or closely similar composition, process, and packaging) it can support the IND/IMPD filing and the initial use date for the product. If more than one strength is required, a bracketing stability design can be used. Changes to the clinical drug product need to be evaluated and additional batches placed on stability, as necessary. Using the same tools and thought processes that were mentioned in the DS portion of this paper, the first step is to determine what DP attributes have an effect on stability. If the new DP changes one or more of the stability-related quality attributes, the new batch should be placed on stability. Identification of these stability-related quality attributes can be facilitated through paper-based risk assessments, prior knowledge, or through short-term stability challenges. Changes that could impact product stability include major DS changes (e.g., solid form), formulation changes (e.g., drug to excipient ratio, different excipients), significant process changes (e.g., direct compression to wet granulation), and packaging changes (e.g., contact materials, blister versus bottle, change in size/headspace). Changes unlikely to affect stability for simple oral dosage forms include changes in scale, equipment, and site of manufacture.

	Minimum requirements for a stability study to support early filings

Typically, there are limited batches in early development. Because these clinical studies are small, there is often a need for only one batch to be produced. For clinical materials expected to be used only through Phases 1 and 2a, the authors believe long-term data collected on the clinical batch or a batch representative of the clinical batch may be sufficient to ensure stability of the clinical product in early phase development. For stable products, additional batches of the same formulation do not need to be placed on stability.

Studies should generate data that give assurance that the clinical supplies retain their quality within acceptable limits at least through the use of the supplies in the clinic. Because early stage clinical studies can be relatively short, stability data need only support short-use periods. However, in many cases, extra samples are in reserve to extend studies for longer duration as a matter of practicality; for example, if the supplies are needed for longer duration than initial plans due to delays in the clinical program.

	As noted, the ICH Q1A guideline on stability testing includes recommendations for stability studies for market application requirements but these are not meant to support early clinical trials. However, many of the ICH constructs are still useful such as the storage conditions and spacing of the time points. Spacing of the time points should be designed to capture the overall stability trend, noting that having a few earlier time points during screening studies or more formal stability studies to establish a use date by the time of filing can be desirable.

	For DP, the early phase formulation usually will not be used in later clinical trials. As such, there is little value to carry the stability study beyond the time in the clinic.

	The selected analytical tests for stability studies should cover the quality attributes that may change with time. Typically, these tests would include assay, impurities (i.e., degradation products), drug release (e.g., disintegration or dissolution), and description. If chiral conversion has been shown to be an issue in DS then it should be monitored in DP. It may not be necessary to perform all tests at every time point depending on the purpose of the test.

	Data fromHT/HH stress studies may be useful in impact assessment for temperature excursions and to design efficient long-term studies. Another approach is the stress studies coupled with modeling, such as ASAP as discussed above. ASAP in some instances can give a good use period estimate in a shorter time than the traditional long-term stability approach. The use date derived from stress-extrapolation can be later verified by placing the first clinical batch into real-time stability studies under ICH accelerated and long term conditions.

Strategy for use dating and use-date extensions. 

Extrapolation of use periods is a commonly accepted practice and nearly a necessity in terms of getting clinical product packaged, labeled, released, and shipped to clinical sites with some use time remaining for storage at clinical sites. There has been much debate on how extrapolation of existing stability knowledge should be used to set use periods of clinical supplies. As was discussed at the beginning of this article, many factors will determine the amount of extrapolation that is defendable. Health authorities may be reluctant to accept extrapolations of more than 12 months past the existing long-term stability data, but it is possible to justify more or less extrapolation based on scientific grounds (see section on DS stability data collection). A one-size-fits-all approach is difficult to arrive at in terms of an exact number for allowed extrapolations, but an approach based on science and risk management is recommended.

	With sufficient DS and drug product stability knowledge and a stable clinical formulation, the risk to the quality of the material is low when allowing for stability retest/use period extensions 12 months beyond available real-time stability data. This, however, would not be appropriate for an unstable drug product or one for which there is insufficient stability knowledge. This risk-based approach is based on three principles:

		Stability attributes that limit shelf life are determined from early development studies and appropriate packaging and storage conditions selected.

		Use-date assignments are monitored and confirmed though traditional (real time and accelerated) stability studies and appropriate actions taken if required.

		Companies have internal procedures describing processes for setting and extending initial use dates. Internal procedures for updating use-date assignments normally involve coordination of clinical relabeling and in some cases CMC filings.

	It is worth stressing the point that stability data first included in regulatory filings are often just the beginning of a program to monitor the stability of the clinical supplies and continued monitoring to confirm storage claims and initial trends can be very useful for products that continue development.

	The authors support the following recommendation from A. Kane: Companies often struggle with the strategy for updating retest/use period assignments throughout development and the consequent updates to the CMC submissions for IMPD and IMPD type dossiers. "Arguably the preference of many applicants would be to update assignments as more stability data are generated without the need for submission of a substantial amendment. To avoid the need for subsequent substantial amendments, the IMPD should contain the proposed specification and provide a clear explanation of how extrapolation is/will be applied to assign the retest/use period assignments" (14). It is the authors' belief that with a well-planned monitoring program, extrapolation with limited initial data is justified.

	Demonstrating stability for clinical supplies should be driven by scientific knowledge gained in development as well a risk-based assessment to guide efficient use of available resources. In early development, clinical efforts are often focused on relatively simple products with short life cycles and the DS from which they are made are often produced by evolving chemical processes. The efforts to determine the stability of the DS and drug product should be fit for this phase of development and are designed to give the most basic stability information, namely, to ensure that the DS is of suitable quality when used to manufacture product and that the drug product is of suitable quality while in the clinic. To make this assessment, simple stability studies using ICH constructs and/or accelerated or stress data may be used. Other experimental data may be collected to increase the scientific knowledge of the DS/DP.

	It is our hope that providing the approaches to early phase stability outlined here, along with the approaches in this series of white papers by the other focus areas of the IQ Early Phase GMPs working group, will provide a springboard to stimulate discussions on these approaches within the industry and with worldwide health authorities.

	To encourage further dialogue, this IQ working group is planning a workshop in the near future to promote robust debate and discussion on these approaches. These discussions will hopefully provide improved alignment between development, QA oversight, and regulatory within the pharmaceutical industry, and most importantly with worldwide health authorities. Agreement between industry and health authorities regarding acceptable approaches to stability studies in early phases of drug development would clearly be beneficial to development scientists and allow for a more nimble and flexible approach to better address the dynamic environment typically encountered during the early phases of clinical development, while still providing appropriate controls to ensure patient safety.

	This article represents the opinion of the authors and not necessarily those of their respective companies.

 is in Analytical Sciences at Merck & Co. Inc. (Summit, NJ); 

is in Pharmaceutical Analysis and Microbiology at Allergan (Irvine, CA); 

 is at Pfizer Global Research and Development (Groton CT); 

is in NCE Analytical R&D at Abbott Laboratories (Abbott Park, IL); 

is in Pharmaceutical Development at Endo Pharmaceuticals (Chadds Ford, PA); 

 is in Pharmaceutical Development, both at Boehringer Ingelheim Pharmaceuticals (Ridgefield, CT); 

 is in Analytical and Bioanalytical Development at Bristol-Myers Squibb Company (New Brunswick, NJ); 

is in Analytical Science at Astra Zeneca R&D (Macclesfield, UK); 

 is in Analytical R&D at Amgen (Thousand Oaks, CA); and 

	*To whom all correspondence should be addressed.

 Part 211.166 Stability Testing.
	3. CHMP, CHMP/QWP/185401/2004, Requirements to the Chemical and Pharmaceutical Quality Documentation Concerning Investigational Medicinal Products in Clinical Trials (EMA, Mar. 31, 2006).
	4. D. Chambers et al., 

 (7) 76–84 (2012).
	5. R. Creekmore et al., 

Guidance for Industry: cGMP for Phase 1 Investigational Drugs

Guidance for Industry: Content and Format of Investigational New Drug Applications (INDs) for Phase 1 Studies of Drugs, Including Well Characterized, Therapeutic, Biotechnology Derived Products 

(Rockville, MD, November 1995).
	8. FDA, 

Guidance for Industry: INDs for Phase 2 and Phase 3 Studies Chemistry, Manufacturing, and Controls 

(Rockville MD, May 2003).
	9. ICH, Q1A(R2) 

Stability Testing of New Drug Substances and Products

, Step 4 version (2003).
	10. S. T. Colgan et al., "The Application of Science and Risk Based Concepts to Drug Substance Stability Strategies," 

(in press 2012).
	11. S. R. Byrn, R. R. Pfeiffer, and J. G. Stowell, Solid-State Chemistry of Drugs. 2nd Edition (SSCI, Inc., West Lafayette, Indiana) pp. 259–366. Also see, ICH, Q6A, 

Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances

, Step 4 version (1999).
	12. K.C. Waterman, "Understanding and Predicting Pharmaceutical Product Shelf-life" in 

Handbook of Stability Testing in Pharmaceutical Development

, K. Huynh-Ba, ed. (Springer Science Business Media, LLC, New York, NY, 2009) pp. 115–135.
	13. K.C. Waterman, 

 (3) 932–937 (2011).
	14. A. Kane, J. Williams, and L Yeo, 

IQ Consortium representatives explore and define common industry approaches and practices for applying GMPs in early development, with a focus on stability.