Stephen Colgan

The quality-by-design principles that enable a manufacturer to limit and control the sources of process variability are equally important to measurement systems, because the variability in any process is partly made up of the contributions of the measurement system variability used to understand the process. The authors use real-life examples from drug development projects to outline how an understanding of chromatographic measurement system variability might be achieved.

The concept of quality by design (QbD) was introduced to the pharmaceutical industry in the International Conference on Harmonization (ICH) guidance documents, ICH Q8-Q11 (1-4), as a way to develop robust manufacturing processes for pharmaceutical products and substances. The aim of these documents is to describe a framework for developing a deeper understanding of how variability in the parameters of a manufacturing process can affect the quality of the final product.

In 2010, the European Federation of Pharmaceutical Industries and Associations (EFPIA) Subteam on Analytical Methods introduced the concept of applying QbD principles to analytical methods (5) where they described two main objectives: improved method performance and increased regulatory flexibility. As yet, no pharmaceutical regulatory standards (analaogous to ICH Q8-Q11) exist that describe how to apply QbD principles to analytical procedures. This article, therefore, focuses on how QbD tools may be used to obtain improved chromatographic method performance in such a way that is aligned with holistic drug product and substance control strategies (regulatory flexibility will not be addressed here).

 A QbD approach to understanding a measurement system such as a chromatographic method involves more than the demonstration of a depth of understanding regarding the choice of chromatographic separation parameters (e.g., through multifactor experimental design/robustness studies). Instead, to comprehensively follow QbD principles, the process should start with a statement of method design intent incorporating method performance characteristics focused on the minimum quality standard of the data the method must achieve so as to be fit for purpose. The foundation of a QbD method is, therefore, a fundamental understanding of the requirements of what the method needs to measure and the reliability requirements to which the method will be judged so as to produce data in compliance with a minimum quality standard. In other industries, the understanding of data “quality” is commonly communicated through an expression of the “uncertainty” associated with a measurement “result”. This uncertainty is treated with equivalent importance to the result itself (as it gives confidence in the quality of the measurement result and facilitates understanding in situations in which, for example, pass/fail criteria with respect to specification limits are being assessed). The concepts regarding how to express the uncertainty associated with a measurement data result can be found in many publications focused on measurement uncertainty (6-13).

In the pharmaceutical industry, the approach to understanding the uncertainty associated with measurement results is being addressed under analytical QbD principles. Here, the design of method performance characteristics is the foundation for ensuring measurement data quality can be rigorously controlled. In line with this, the EFPIA subteam introduced the concept of the analytical target profile (ATP) (5), which describes the performance characteristics of the method such that data the method produces will be “fit for purpose” (e.g., for making decisions about whether a batch of drug substance or drug product meets the specification criteria for assay or purity).

Once an ATP has been defined, a systematic process follows that includes a focus on design of the method (i.e., choice of technique and drafting of suitable starting conditions) followed by a full evaluation of the method using risk assessment tools and multifactorial experimental approaches. The final step focuses on an expression of the method conditions or ranges across which the ATP may be met, together with specific instructions to ensure adequate control of the method each time it is used. This process is holistically defined in the schematic in 


. It is important to note that it is not a one-time process but instead is an iterative one that should be revisited throughout the lifecycle of a method. Risk assessments or experiments performed against the ATP should be made each time any change to the product or process is made or new knowledge is gained.


As outlined previously, the first step in QbD method development is to define the ATP. There are at least three important components to be included in this statement:

The range for which the analytical method is expected to quantify the measurand (i.e., analyte)

The total uncertainty, expressed in terms of systematic (accuracy) and random (precision) uncertainty (i.e., variability) components

A description of the analyte to be tested, including the sample or matrix in which it will be tested.

Accompanying the second consideration, the level of risk should be understood for making incorrect decisions.

The following discussion outlines ATPs for a combined assay and purity method for a real-life drug substance, referred to henceforth as examplain hydrochloride (HCl):

Assay: The procedure must be able to accurately quantify examplain HCl drug substance over a range of 90% to 110% of the nominal concentration with accuracy and precision such that measurements fall within ±2.0% of the true value with at least a 95% probability. 

Purity: The procedure must be able to accurately quantify all related impurities relative to examplain HCl in the presence of drug substance and other impurities over a range from the reporting threshold through twice the specification limit. The accuracy and precision of the procedure must be such that the measurements fall within ±15% of the true value for impurity levels ≤ 0.15% with at least 90% probability and within ±10% of the true value for impurity levels > 0.15% with at least 90% probability.          

Justification of ATP statements. Assay ATP

. The ATP describes method performance requirements that define the risk of making an incorrect decision concerning the measurand (14). Analytical methods that adhere to the criterion stated in the ATP allow decisions (e.g., to accept or reject a batch based on the reported value) to be made based on a predefined, maximum level of risk, which is particularly important when the reported value is near the specification limit. For instance, a method that conforms to the assay ATP discussed previously will produce measurements for which there exists at least 95% confidence that these measurements reside within ± 2% of the true (unknown) measurand. That is, there is no more than a 5% chance of making an incorrect decision against the stated bounds of ± 2%.

Suppose a potency result of 100% label claim for a release test of a particular lot is measured. Further, suppose the analytical method used to obtain this result has been shown to conform to the ATP discussed previously. The risk that the true, unknown potency of the lot is below the specification limit of 98% is less than 5%, because the method conforms to the statement that at least 95% of measurements will reside within ± 2% of the true value. Consequently, there exists less than a 5% chance that the true unknown value differs by more than 2% from the observed measured value (95% confidence true value within 100% ± 2% or 98-102%).

The specification criteria for the assay is 98-102% label claim. It should be noted that the initial assay specification was 97.0-103.0%, and the ATP was established based on this orginal specification. The specification was subsequently tightened to 98.0-102.0% based on global regulatory feedback, and the original ATP was found to be fit for purpose with respect to the revised specification. The ATP criteria, as with ICH method validation criteria, are established based on considerations for patient safety and product quality and are consistent with the capability of analytical methodology used to characterize APIs. 

 illustrates pictorially the ATP as a probability contour plot (i.e., parabolic region in dark grey) for the examplain HCl drug substance assay as described. Here, the total uncertainty is comprised of precision (σ, random variability) and bias (μ, systematic variability). 

 also illustrates a rectangular region corresponding to the more generally applied acceptance criteria established for analytical measurements, in which bias and precision are defined independently. In this case, the rectangle represents the following method criteria: the measurement has no more than ± 2.0% bias and no more than 1.25% variability.

. First, the probability curve (parabolic region in dark grey) is contained within the more generally applied acceptance criteria (rectangular region in green). As such, the ATP criteria are slightly more restrictive. Second, when using the probability curve approach, method precision criteria (y-axis) is dependent on bias criteria (x-axis) and vice versa. This is because the total uncertainty, which is specified in the ATP, is a combination of these two components. Intuitively, a method with no bias can accommodate more variability (or lower precision) compared to a method with some non-negligible bias while providing the same total uncertainty. As method bias increases towards the ATP limit (±2 in 

), the required method variability decreases to zero to maintain the same analytical performance in terms of total uncertainty. When using the traditional approach of independent bias and precision assessments, there is no natural trade-off between those criteria, thus implying that a method may have both high bias and high variability (indicated by the yellow diamond in the upper right-hand corner of the green rectangle in 

), which could be problematic if not properly linked to the specification range. That is, a method operating at the yellow diamond (bias approximately + 2% and precision approximately 1.25%) does not maintain a 95% assurance that measurements will be within ± 2% of the true value. If the bias can not be corrected for, then measurements have only approximately a 50% chance of being within ± 2% of the true value. Even if this method is corrected for a known 2% bias (i.e., bias can be measured as different from random uncertainty), there exist < 90% probability that measurements will reside within a ± 2% range.

The expression for defining the acceptance region is shown in 

 where µ is true mean/accuracy (a parameter); σ is true sigma/precision (a parameter); e is allowable analytical window (a fixed constant); y is individual assay value (a random variable with mean µ and standard deviation σ); T is true analytical content (fixed target); p is minimum probability for individual assay to reside within error bound e (fixed constant); ϕ is normal density function centered at µ, with standard deviation σ.

Using Equation 1, the interplay between the appropriate analytical window (e), maximum sigma (σ), and minimum probability (p) can be probed for each unique analytical method.

. In this example, the specification criteria detail the limits for all related (specified) impurities to examplain HCl with specified impurities A and B both with limits of not more than 0.15%.

 illustrates the ATP as a probability contour plot for the examplain HCl drug substance impurities as described previously (i.e., parabolic region in dark grey). The total uncertainty is comprised of precision (σ, random variability) and bias (μ, systematic variability).

 also illustrates a rectangular region corresponding to the more generally applied acceptance criteria established for analytical measurements, where bias and precision are defined independently. In this case, the rectangle represents the following method criteria: the measurement has no more than ± 15.0% bias and no more than 10% variability. Here, the maximum allowable bias and precision is consistent with what can be expected for analytical procedure performance at these levels. For example, for levels ≤ 0.15% relative to examplain, the maximum allowable precision is 9.1% RSD and the maximum allowable bias is ± 15%.

There is a trade-off between precision and accuracy, such that it is not acceptable for the method to exhibit maximum bias and maximum variability concurrently, and, as with the assay ATP, the purity ATP criteria is slightly more restrictive when compared to the ICH validation criteria that would have typically been applied. From a practical perspective, the ATP criteria can be interpreted as follows: 9 out of 10 measurements will fall within 100% ± 15% of the true value, which corresponds to a range in which at least 9 out of 10 measured values will reside within 0.13% to 0.17%. This level of measurement uncertainty ensures patient safety. It is consistent with the philosophy of ICH Q3A (Impurities in New Drug Substances) as well as the current capability of contemporary analytical methodology used to quantitate low-level impurities in pharmaceutical drug substances. In fact, contemporary method capability was taken into consideration when the limits in ICH Q3A were established.

Analogous statements can be made for ATP criteria for impurities > 0.15% where the maximum allowable precision is 6.1% RSD and maximum allowable bias is ± 10%. This means that an impurity present at 0.3% (true value) corresponds to a range in which at least 9 out of 10 measured values will reside within 0.27%- 0.33% (i.e., true value ± 0.1 x true value). This tiered approach ensures that performance of the procedure is maintained for higher level impurities while ensuring patient safety and aligning with contemporary procedure capability.

. Once appropriate ATP criteria have been established, a technique should be selected. This selection depends not only on the match between measurement technique capability and ATP, but also on other scientific, practical, and business requirements. Typical considerations to bring to the discussion table between scientists who may be involved in using the method across the development lifecycle could include the physicochemical characteristics of the molecules in question, whether the method will be run in an R&D environment or a manufacturing environment, if on-line capability might be required, what sample turn-around times (from sampling to data reporting) are going to be necessary, and a plethora of other scientific and business-focused factors.

In the case examples discussed in this article, following such a discussion between R&D and receiving laboratory analytical scientists, reversed-phase high-performance liquid chromatography (RP-HPLC) was the method of choice.

 Once a technique has been chosen, a systematic process to arrive at “starting” or “draft” method conditions should be followed. In the case of RP-HPLC, the approach is shown in 

. Here, experimental studies are combined with in-silico modeling software to maximize the value of the results by being able to predict between experimental parameters (15, 16).

At the start of the process, it is essential to define the correct key predictive sample set (KPSS). For a pharmaceutical example, the KPSS available will be highly dependent on the drug-development lifecycle stage, and the ideal KPSS for an API  purity method should include all known process related impurities and known relevant potential degradants. If structures are known, then the experimental screening strategy may be supplemented by the information to be gleaned from a Log(P) vs. pH plot (P is the octanol water distribution coefficient of all analytes of interest). The column screening strategy employed in our laboratories and for the examples discussed here encompasses four stationary phases; two organic solvents; and acidic, neutral, and basic aqueous mobile phases (15). The primary objective of the screening is to obtain the most promising starting conditions with respect to overall selectivity, peak shape, and chemical stability, as well as minimal reliance on accurate pH control.

The next step is to investigate the combined effects of temperature and gradient profile using the starting conditions from the first phase of screening experiments (i.e., stationary phase, pH, and organic modifier). This experiment aims to explore the impact of various gradient profiles together with a range of temperatures across six experiments. The data obtained are modeled using software (e.g., ACD Labs LC Simulator), which allows the scientist to interpolate or extrapolate beyond the tested range to gain maximum value from a relatively low number of experiments. In the example, the data from the six experiments are used as the input for in silico optimization experiments. The result is a resolution map and optimized chromatogram within which the optimum conditions with respect to overall peak shape, resolution, and analysis time may be predicted (

The final stage of this systematic approach to method development is to check the effect of small changes in pH on the method performance. The pH is typically varied by up to +/- 1.0 pH units across five experiments (e.g., +1.0, +0.5, 0, -0.5, -1.0 pH units). Again, the data resulting from these experiments may be evaluated using software packages, such as the LC Simulator software, which allows for a more thorough understanding regarding the most suitable pH that will yield a more robust separation.

Experience with this systematic approach to method development indicates that approximately 75% of all applications lead to a successful (i.e., fit for purpose) method. In the remaining cases, various degrees of variations from the workflows have to be explored. For example, use of alternative buffer components, ion-pairing reagents, alternative column chemistries, and even completely different separation mechanisms can be applied.

 The risk-assessment exercise involves a systematic assessment of the draft method. The risk assessment process is designed to map individual method steps (e.g., standard and sample preparation or chromatographic separation) and identify method variables with the potential to affect method performance with respect to the ATP requirements. In the case described here, this exercise involved experienced analytical chemists from the method development and receiving laboratories and included those with some experience running the method. These participants were included to ensure that knowledge from previous studies were included and to understand differences in lab practices between the development and receiving laboratories. Three distinct focus areas were examined: (1) sample and standard preparation; (2) chromatographic separation; and (3) detection and data processing. Method variables were scored based on their potential to affect method performance together with the likelihood of occurrence using a cause-and-effect Matrix. Each variable was categorized as follows:

Experimental (X). Those that may vary and require further experimentation to understand (e.g., temperature, flow rate, mobile phase composition)

Controlled (C). Variables that can be controlled or specified at unique levels (e.g., column stationary-phase type and particle size, column diameter, length, and supplier)

Noise (N). Those that cannot be controlled or are allowed to vary randomly from a specific population (e.g., column age).

Method variables with the highest scores (i.e., combined high probability and high impact on chromatographic performance relative to the ATP) were further assessed by way of multifactor experimentation. An example of the multifactor experimentation from the chromatographic separation focus area follows.

 Two separate design-of-experiments (DoE) studies were performed to identify and verify the optimum method conditions. The first DoE was conducted to explore and identify a preliminary set of chromatographic conditions for further verification. The second DoE was conducted to verify conformance of the method to the ATP criteria.

 represents the experimental region from the first wave of experimental design studies (DoE-1). This design included the following parameters which were identified during the risk assessment as having the highest potential to influence the chromatographic separation: flow rate, trifluoroacetic acid (TFA) content in mobile phase, column temperature, gradient change, and start and end times. A preliminary set of suitable operating conditions was identified by assessing the chromatographic performance measured during DoE-1 against the predefined criteria shown in 

The results of DoE-1 were used to identify the variables that may affect chromatographic performance. Statistically significant effects at the commonly-accepted 0.05 level of statistical significance were determined using Student’s critical t-values. Statistical models of these results were developed for each method attribute and used to define the variable ranges over which the method is expected to meet the predefined criteria in 

. These ranges of chromatographic variables defined a preliminary experimental design space referred to as the method operable design region (MODR).

Critical   pair resolution (impurity A: impurity B)

Relative   standard deviation (RSD) at limit of quantitation (LOQ): (impurity A at 0.05%   LOQ)

Examplain   hydrochlodride retention time

A subsequent experimental design study (DoE-2) was executed to verify that the method complied with the criteria specified in the ATP. Verification testing was performed using experimental conditions spanning the preliminary predicted MODR identified from DoE-1 results. Based on the data analyses from DoE-1, the three parameters that had the largest collective impact on both resolution and limit of quantitation (LOQ) were the gradient change time, the column temperature, and the mobile phase TFA concentration. To select the method conditions, a standard 23-1 design was chosen that spanned a predicted acceptable range of method performance. Specifically, the gradient start time was varied between 15-19 minutes, the column temperature between 25-32 C, and TFA content between 0.04-0.06%. The other parameters that had an impact on method performance were flow rate and gradient start time. For this experiment, however, those levels were fixed at values that would stress the system in terms of performance; that is, at levels nearing the predefined criteria. Flow rate was set at 1.05 mL/min and gradient start time at 0.5 minutes. Gradient end time did not affect method performance. Testing was conducted over four days, by two analysts, in two different laboratories (development and testing labs) using HPLC systems from two vendors (Agilent and Shimadzu).

The chromatographic variables used to verify the MODR are shown in 

. Verification testing was initially performed using conditions 1-4. 

 show how results using conditions 1, 3, and 4 all met ATP criteria. Results generated using condition 2, however, failed to adequately meet ATP criteria due to insufficient resolution (Rs < 1.0) for the critical pair. This is illustrated in

 where condition 2 is clearly within the red shaded region. As a result of this failure, the MODR model was refined, and a new combination of verification variables, condition 5, was added.

In lieu of preparing separate solutions, injection volumes of 9, 10, and 11 µL were used to verify conformance to the ATP over the range of 90-110% of the nominal injection concentration. The flow rate was held at 1.05 mL/min for the original verification study (conditions 1--4), as a flow rate slightly above the 1.0 mL/minute target was considered a worst case scenario based on the results from DoE-1. The flow rate was changed to 1.00 mL/min (the target condition) for condition 5. The final verified MODR incorporating verification condition 5 is illustrated in 

As a means of visualising how these results from both labs during DoE-2 comply with the ATP, 

 shows the probability contour plot (using 

) illustrating method variability (σ≈relative standard deviation or RSD) vs. calculated bias/process acceptance criteria (98-102% potency). The grey-shaded region is the graphical representation of the ATP criteria for the assay method. Each point represents 24 replicates at each of the five MODR verification parameters run in the two different labs. This graph illustrates minimal (statistically insignificant) bias relative to the proposed 98.0-102.0% assay acceptance criteria. Although slightly greater variability was observed for Lab 2 results, all results fall within the ATP for the assay method (grey region). The triangular regions surrounding each point represent the simultaneous 95% confidence interval for accuracy and precision for each of the points as described in Lindgren’s Statistical Theory (14).

Similarily, the probability contour plots in 

 illustrate method variability (σ≈ RSD) vs. calculated bias/process acceptance criteria for results generated from both laboratories for impurity A at > 0.15% and impurity B at ≤ 0.15%, respectively. Each point represents 24 replicates at each of the five DoE conditions run in the two different labs. The simultaneous 95% confidence interval for accuracy and precision is also shown on the plots. These results illustrate how impurity A and B quantitation data meets the ATP criteria for quantitation of impurities in that > 90% of data are within ± 10% of expected normalized value for values > 0.15%, and > 90% are within ±15% of the expected normalized value for values ≤ 0.15%.

Based on the statistical modelling from DoE-1 and DoE-2, the entire white region in 

 is predicted to be capable of meeting the ATP acceptance criteria. For operator simplicity, however, the operating ranges were constrained to the ranges listed in 

Articles

The quality-by-design principles used to control process variability are equally important to measurement systems because process variability includes contributions from measurement system variability. The authors use real-life examples from drug development projects to outline how an understanding of chromatographic measurement system variability might be achieved.

Using Quality by Design to Develop Robust Chromatographic Methods

This article provides a compilation of summaries of many of the presentations at the two- day workshop held in conjunction with the Annual Meeting of American Association of Pharmaceutical Scientists (AAPS) on October 21-22, 2011 in Washington, D.C. The workshop program comprised of twenty presentations encompassing many scientific aspects impacting pharmaceutical stability. The diverse topics included Current FDA thinking on stability practices, phase appropriate method design utilizing QbD concepts, stability indicating spectroscopic methods, design of stability studies for global requirements, strategies for controlling genotoxic impurities in drug products, regulatory perspectives for leachable impurities etc. A session on stability studies of biopharmaceuticals was also included. In other words the workshop topics included most aspects of the 

“science behind pharmaceutical stability”

. The program also included a regulatory round table in which questions were received from the attendees and answered by a panel of regulatory experts from industry.  

The presentation summaries have been prepared by the individual speakers, some speakers did not submit the summary of their presentations and therefore those could not be included.

Current FDA Thinking on Stability Practices for New Drug Products (Small Molecules)

The talk was divided into two sections addressing stability considerations at the Investigational New Drug (IND) stage and at the New Drug Application (NDA) stage. He discussed the regulatory and scientific reasons for including the appropriate stability data to support various stages of clinical investigations at the IND stage and to support a NDA for marketing pharmaceutical products in the United States. The CFR [312.23(a)(7)(iv)(a) and 312.23(a)(7)(iv)(b)]  states that the IND should provide information sufficient to support stability of the drug substance and drug product to assure their stability during planned clinical studies. It was emphasized that stability data commensurate with the duration of the clinical study are required in all phases of the IND to demonstrate that the drug substance and drug product are within acceptable chemical and physical limits for the planned duration of the proposed clinical studies. He provided some general observations from submitted INDs showing how these submissions addressed these statutory requirements to ensure that the clinical products will remain suitable for their intended use during the course of clinical studies. 

The second half of his presentation addressed the need to have appropriate stability data submitted to support an NDA for marketing a pharmaceutical product in United States. It was emphasized that each pharmaceutical product that is to be marketed in the United States needs to have an expiration dating period assigned.  This expiration period is assigned to all pharmaceutical products when packaged and stored under the pre-determined circumstances.  The data to support such expiration period is generated by studying the stability of the product using carefully designed stability studies. He elaborated on consideration for designing and executing a proper stability study that would generate appropriate stability data to support a proposed expiration period.  Finally he presented two case studies which demonstrated how the Agency was able to assign the proposed expiration period in one case and how the data provided in the second case did not support the proposed expiation period. 

Design of Stability Indicating Methods Utilizing QbD Concept – a Phase-Appropriate Approach

The importance of development and manufacture of pharmaceutical products utilizing Quality-by-Design (QbD) approach is well acknowledged by the industry and regulatory agencies. To achieve QbD-based product and process development, it is imperative that analytical methods be designed and developed utilizing a QbD approach as well. The question that is frequently asked is when to start using the QbD approach in drug development and analytical method design since many development candidates do not progress beyond Phase1 or 2  because of failure to meet the clinical objectives. 

A unique approach was presented on design of stability-indicating methods utilizing QbD concept in a phase-appropriate manner from the beginning of clinical development. The Analytical Target Profile (ATP) is defined early on to describe the method performance requirements to measure a specific critical quality attribute (CQA) of the drug product. A specific method can be designed to meet the pre-defined performance requirements. Method performance requirements in ATP can be defined in a phase appropriate manner. 

The presentation discussed a lifecycle approach to analytical method design and development starting with the early stage method. Critical method parameters are identified during early stage method design and a systematic optimization of critical method parameters is performed utilizing commercially available on-line software. Such optimization has significant advantages over manual optimization of parameters and can be achieved with minimal scientist time. Critical evaluation of data must, however, be performed. Risk assessment of the method is performed at key stages of development. The principle of continuous learning and improvement is applied as the method evolves in parallel with drug development process. 

Another advantage of this approach is that since the core method is developed during early development, and the method evolves with the changes in drug product formulation, the final method incorporates the knowledge of the impact of the critical method parameters and formulation and process variables on the method performance. It also provides a convenient means of tracking impurities as a function of formulation and process parameters. The method life cycle parallels the product development life cycle. 

In conclusion, applying QbD concept to the design of analytical methods in a phase appropriate manner provides a scientifically sound method at all stages of drug development with good understanding of method risks, critical method parameters and provides better assurance of the robustness and long term performance of the method. 

Drug Product Fingerprints: stability-indicating spectroscopic tests

The overall quality of drug products relies on management and mitigation (i.e. control) of risks.   One approach to managing risk elements considers severity, probability, and detectability of critical events (e.g. form conversion of API, formation of impurities, compositional variations, etc.), and instituting control(s) around each element.  Thus, analytical methods fill the need to detect critical quality attributes.  Detection, however, is merely one part of the risk management process- a system of actionable controls is responsible for mitigating risk and ensuring quality. 

Control strategies for drug products rely on stability data to identify acceptable ranges for ingredients, processing conditions, and storage/ shipping conditions. In one example, degradation product and impurity testing of drug products was waived by proving that: 1) Process-related impurities contained in the drug substance were the only source of impurity content of the drug product, 2) No new impurities or degradants were formed during the manufacture of drug product, and 3) No new impurities or degradants were formed at the long-term storage, accelerated, and stress conditions used in long term stability studies.  This testing waiver was complimented with other at-line and online tests to develop a proposal for real-time-release testing (RTRt) of the drug product. 

Another example described the use of molecular spectroscopy to monitor form conversion during a drug product stability program.  Stressed drug products were analyzed by near infra-red (NIR) as well as powder x-ray diffraction (PXRD), dissolution, and impurity testing.  Throughout the investigation, NIR and PXRD identified  change of crystallinity at moderate and extreme conditions; the dissolution method did not identify crystallinity changes of the API (BCS I), and impurities were detected in samples of lowest crystallinity. The use of NIR provided detailed understanding of the impact of storage conditions, temperature excursions and packaging types on crystallinity. 

In summary, both traditional and emerging techniques offer insight to stability profiles. Stability-indicating tests are an integral part of control strategies for new drug products. 

Method Validation at Pre- and Post- Approval Stages Utilizing QbD Approaches

The use of DOE/QbD method validation approaches was discussed to support stability programs.  Such approaches are needed to ensure methods have the accuracy and precision to detect stability changes and provide an understanding of the method variability.  Often, method variability alone can suggest stability changes that trigger unnecessary investigations and reformulation activities.   Another need is to support pre- and post- approval formulation and process changes without unnecessary method revalidations. 

A unique approach was presented using DOE to validate a range of formulations, so formulation changes within this range do not require revalidation. This is coupled with accelerated stability modeling tools to ensure formulation and process changes do not generate new degradation products requiring revalidation.  These combined tools minimize the impact of pre- and post-approval changes.

Case studies were presented using DOE/QbD to define a formulation operating range.  This can be done without more work than needed using a traditional approach.  Other key DOE outputs include a determination of critical method validation parameters that need to be monitored and controlled, such as resolution between critical pairs.  A case study was also presented using DOE to assess intermediate precision to ensure there is no increase in method variability. 

Another key DOE/QbD output is the Accuracy to Precision model.   This shows the balance between accuracy and precision and its influence on product acceptance/failure rates.  This can justify moving to new technologies as long as the change meets the accuracy to precision acceptance criteria.   An example is discussed starting in early development with a generic gradient HPLC method; and, then going to a product specific gradient method, an isocratic HPLC method; and, finally, to a UPLC or PAT method for product commercialization.  This use of DOE/QbD and accelerated stability models provides powerful tools for developing a lean stability program based on sound science and statistical rigor. 

ICH Q1B Photostability Guideline – Time for a Revision? 

The presentation was based on a recent publication in the 

 (99:7, 2934-2940, 2010).  This oral presentation highlighted some significant and some not so significant deficiencies with the ICH Q1B guideline on photostability, which was published in November 1996 and has been implemented in all three regions (US, EU, and Japan). The presenters noted that since publication in 1996, the guideline has provided a useful basic protocol for testing of new drug substances and associated drug products for manufacturing, storage, and distribution; the authors also noted that the guideline does not cover the photostability of drugs under conditions of patient use. While there were several areas within the guideline that would benefit from revision, a couple of notable issues were highlighted during the talk. 

First, the authors noted two significant problems with the Option 2 UVA and visible lamp choices.  The cool white fluorescent lamps currently in use in general do not match the spectral power distribution required by the guideline, as specified by ISO10977.  Further, the presenters assert that the UVA lamps commonly found in “ICH compliant” photostability chambers often do not meet the requirements of Q1B (where Q1B specifies “A near UV fluorescent lamp having a spectral distribution from 320 nm to 400 nm with a maximum energy emission between 350 nm and 370 nm; a significant proportion of UV should be in both bands of 320 to 360 nm and 360 to 400 nm”).  Second, the authors showed that the current recommendation of quinine as an actinometer should be specified only for a specific Option 2 UVA lamp.  Further, the timing of absorbance measurements is absolutely critical, since the quinine continues to react after the UVA source has been turned off at approximately one-fifth the rate of when the light is on. The authors provided examples and literature references for their assertions. 

The presenters called for the revision process, noting that nearly all of the Quality guidelines have undergone one or more revisions, including the parent Stability guideline, which has undergone two revisions since its first version. 

Designing Stability Studies for Global development Programs

Day one of the Stability workshop included a presentation on Global stability requirements beyond ICH requirements.  A recommendation for a global approach to stability and case studies on post approval changes and Emerging Market draft guidelines were shared.

The ICH and WHO stability guidelines were shared at a high level.  The discussion included information about countries where actual practice is different than the WHO recommendations, for example Ecuador, Bolivia, Nigeria, Peru and Venezuela. 

Recommendations for a global stability approach for drug substance supporting all markets was shared.   Additionally, a drug product stability decision tree with consideration of the stability of the product, and the countries where the drug is marketed provided a clear recommendation for long term and accelerated stability conditions. Current emerging market draft guidelines including the draft ASEAN Stability and Variations guidelines and challenges with those guidelines were outlined for group discussion. 

A case study for CMC Post Approval change with technology transfer from development to a commercial site and included two multivariate analysis models for stability and design space. Acceptance of the risk based approach and prior knowledge resulted in stability requirement waivers and enabled a different approach to process validation. Key messages from the presentation included that regional stability guidance exists for emerging markets and may be different than what is published in the WHO Stability Guideline.  Science and risk based approaches are not always accepted.  Some new guidelines indicate an acceptance of stability commitments instead of upfront data for process changes.  The ICH Global Cooperation Group which includes 6 regional harmonization initiatives APEC, ASEAN, Global Cooperation Council, PANDRH, SADC East Africa Community are making improvements towards harmonization. 

Artifactual Formylation of the Secondary Amine of Duloxetine Hydrochloride by Acetonitrile in the Presence of Titanium Dioxide: Implications for HPLC Method Development

This presentation was based on a recent publication in the 

Journal of Pharmaceutical and Biomedical Analysis

 (53, 432-439, 2010). The authors showed that duloxetine hydrochloride, a secondary amine containing pharmaceutical, currently marketed as Cymbalta, undergoes N-formylation as an artifact of sample preparation prior to HPLC analysis for impurities. They showed that the reaction is catalyzed by sonication and/or light in the presence of titanium dioxide and is proposed to occur via a hydroxyl radical-initiated mechanism. The proposed mechanism was supported by controlled sample preparation studies with deuterium-labeled acetonitrile, and LC/MS studies showed incorporation of one deuterium into N-formyl duloxetine, proving that the carbon of the formyl group was from the methyl group of acetonitrile. This artifactual reaction can be eliminated or minimized by the replacement of acetonitrile with methanol, or by simply adding at least 10% methanol to the sample diluents.  The authors provided rationale for the use of methanol using computational chemistry to show how methanol is able to sufficiently scavenge the hydroxyl radicals to prevent the oxidation of acetonitrile. The authors discussed how this discovery is broadly relevant since sonication is commonly used to aid dissolution of pharmaceuticals in acetonitrile for HPLC analysis, titanium dioxide is a commonly used excipient, the amount of light found in modern analytical laboratories is sufficient to cause the reaction to occur, and secondary amines are present in the structures of many pharmaceuticals. 

Strategies for Controlling Genotoxic Degradants in Drug Products: Mitigation Strategy and Case Study

This presentation focused on genotoxic impurities (GTIs) in drug products, a topic currently receiving significant attention in the pharmaceutical industry.  The EMA Guideline on the Limits of Genotoxic Impurities (2006) recommended that potential GTIs should be identified and when there is a structural alert, a bacterial reverse mutation assay should be conducted.  In addition, it states potential degradation products of the drug substance and drug product should be considered for genotoxic potential with little guidance to determine those degradation products that may be reasonably likely to form.  The authors outlined a strategy implemented at Eli Lilly that hinged upon well-designed stress studies to understand the most probable degradation pathways that a compound may undergo, thus limiting the number of potential degradation products to assess for genotoxic potential.  Internal Lilly data was presented that illustrated that degradation products observed on long-term stability were a perfect subset of the major degradation products observed during stress degradation studies (n=15 drugs). 

If the potential degradant had an alerting structure and was Ames positive, they recommended the development of an analytical method with an LOQ at 10% of the threshold of toxicological concern (TTC).  They proposed that if the degradation pathway was inactive (more than 10% TTC) in the drug product on long-term stability that appropriate due diligence had been demonstrated and there is no risk to patient safety. The proposed strategy is novel in that the assessment of potential degradation products (i.e., those derived from stress degradation studies) is dictated not by subjective judgment of what degradation pathways might likely be active, but rather by well-designed stress studies.  A final point made by the authors and supported by a case study was to leverage the information that can be gleaned from using Arrhenius predictions from accelerated stability studies in order to quickly screen multiple formulations in order to predict the GTI levels at the end of the recommended shelf life.  They advocated that this approach enables formulation and analytical development to make informed decisions around formulation, package, and storage conditions as they relate to GTI formation. 

Dissolution failure and failure mode analysis of a Hot melt extrusion product – a case study

The regulatory guidance and the CFR requirements were discussed as an introduction to the main theme of the talk.  The high lights of the Barr decision along with FDA’s Guidance on investigating OOS results for pharmaceutical products were discussed. Determining root cause and establishing CAPA is the key to successful OOS investigation.  Failure mode analysis tool like Fish bone diagram was discussed as a mean to identify the root cause. The step by step investigation of a dissolution failure of a melt extrusion product was discussed as case study. The product failed at 6 months at accelerated stability condition. Since the initial investigation did not result in identifying the root cause it was decided to evaluate the robustness of the method.  A five factorial/eight experiment design was used to evaluate the robustness of the method. The method was found to be very sensitive to the salt added in the dissolution media. A normal probability plot was used to assess robustness of the method using the data generated from the DOE. 

Other analytical techniques had to be used since the evaluation of the method did not conclusively prove the root cause of the failure. The product was analyzed using Solid state NMR, Environmental electron scanning microscope, time of flight-secondary ion mass spectroscopy (TOF-SIMS). Products cured at 50c were used for the analysis. SSNMR analysis showed that stearyl alcohol in the formulation if behaving differently after curing the product. A white coating on the product was observed when the product was viewed in an ESEM. The white coating was identified to be stearyl alcohol by TOF-SIMS. 

Based on a scientific investigation it was concluded that the dissolution failure was due to the stearyl alcohol migrating to the surface of the product when exposed to heat. 

Stability Testing to Support Distribution of Temperature Sensitive Pharmaceuticals

All drugs are, to some extent, temperature sensitive. Stability testing makes it possible to determine the appropriate long term storage condition and to evaluate the risk to product quality posed by exposure to temperatures outside that condition. The ICH stability guidances primarily focused on storage conditions and shelf lives for drug substances and drug products. This presentation discussed the other types of testing which may be done in addition to the standard ICH conditions that permit a stability budget to be created for a pharmaceutical. 

A stability budget is created using data from long term and accelerated testing such as that provided for in the ICH guidances, but adds freeze-thaw and temperature cycling studies to create a fuller picture of a drug’s susceptibility to changes in temperature that it may experience during the entire distribution process from manufacture to transport, to storage, to end use. The concept of time out of refrigeration has been used to allow for room temperature operations such as packaging and labeling on refrigerated products. This presentation showed how this concept can be expanded to the entire distribution process. 

Effective Approaches for Conducting Method Transfer

Analytical procedures are critical to determine quality of pharmaceutical products at release and throughout their shelf life.  Kim Huynh-Ba discussed several options to transfer analytical procedure from one laboratory to another laboratory and effective approaches to be considered when conducting method transfer.  Method transfer is a process of which an analytical laboratory is qualified to perform a testing procedure, as method transfer activity is required as part of method validation.  This training of performing an analytical procedure is done by The Transferring Lab to The Receiving Lab. It is well documented that there are four options that can be used for this purpose.  Three of these four options involve lab activities and the selection depends on the validation status of the analytical procedure and/or availability of lab personnel.  These are:  Comparative Testing, Co-Validation and Re-Validation.  The fourth option is to determine if the Transfer Waiver can be done.  Several references including USP new General Chapter <232> 1224 — have suggested this option.  Based on the knowledge, ability and experience of the Receiving Site, additional testing may not be needed to qualify The Receiving Lab to perform certain analytical procedure. 

As all other cGMP activities, transfer activities are conducted according to a protocol with predetermined acceptance criteria.  This protocol should be agreed upon by all sites involved. Elements of a transfer process were also discussed.  Depending on the types of labs involved, certain SOPs such as data review, data reporting, OOS or OOT investigation from both sites should be discussed prior to the transfer.  Conclusion of the transfer must be documented with all data reported including any representative chromatogram or spectra. It is important that validation data are available to the Receiving Lab as part of the Transferring Background Package and The Receiving Lab must conduct a thorough gap analysis before any testing can be done.  It is also advised to avoid cGMP materials to be used for transfer activities to avoid issue that may arise with data generated. 

Roundtable Discussion – Interesting and Challenging Stability-Related Regulatory Questions

Panelists: Stephen Colgan, Ph. D.; Robert J. Timpano, B. S.; Ganapathy Mohan, Ph. D.; David Lin, Ph. D.

Day one of the workshop concluded with a Roundtable discussion that focused on Regulatory Queries.  A quick show of hands at the beginning of the Roundtable indicated that the areas of most interest included Science and Risk-Based Approaches to Stability/Shelf-life and Stability Protocols. 

It was noted that the FDA has been advocating biorelevant specifications, but do not appear to embrace biorelevance when it comes to stability protocols.  An example is the mandate to include water content in post-approval proposals when the science clearly indicates that water content has no relevance to stability or biorelevance.  The panel noted that there is no guidance in this area, but encouraged the audience to use science to support stability testing protocols.  It also was noted that scientific engagement with the regulators in the ICH regions would be welcomed, this is not the case for most of the Emerging Market regions. 

The discussion continued with a discussion of science-based stability protocols that should only focus on the relevant product attributes.  This approach would be leaner, and would protect the patient as well as non-lean protocols.  The panel noted that the Quality Target Product Profile (QTPP) could be leveraged to advocated Lean Stability Protocols. 

The most enthusiastic discussion of the Roundtable focused on a liquid product in a semi permeable or non permeable container and whether a matrixed stability protocol would be suitable for containers stored upright, upside down, and lying down.  The panel noted that developing a matrixed protocol can be difficult and recommended that a statistician be engaged.  It also was suggested to review this type of protocol with the Regulatory Authorities before execution.  From a scientific point of view, the panel noted that a Stability Risk Assessment would help define what attributes should be monitored on stability and whether a matrixed approach should be considered.  For the question on container orientation, the stability scientist should determine what attributes may be affected by the container orientation.  If there is a medium or high risk that the orientation would have an affect on a potential shelf-life limiting attribute, a matrixed approach would not be advisable.  In the end, everyone agreed that science and a knowledge of the regulations should be the drivers when stability protocols are being developed.

A two-day workshop on the "science behind pharmaceutical stability" was held in conjunction with the Annual Meeting of American Association of Pharmaceutical Scientists (AAPS) on Oct. 21-22, 2011 in Washington, DC.

Pharmaceutical Stability: Scientific and Regulatory Considerations for Global Drug Development and Commercialization

A two-day workshop on the "science behind pharmaceutical stability" was held in conjunction with the Annual Meeting of American Association of Pharmaceutical Scientists (AAPS) on Oct. 21–22, 2011, in Washington, DC. This article summarizes some of the topics presented on various scientific aspects affecting pharmaceutical stability, including a regulatory roundtable discussion with a panel of regulatory experts from industry. The workshop presenters are noted herein.  

The full summary of the workshop is available at 

Current FDA thinking on stability practices  for new drug products (small molecules) 

The presentation addressed stability considerations at both the investigational new drug (IND) and new drug application (NDA) stages. It was emphasized that stability data which commensurate with the duration of the clinical study are required in all phases of the IND stage to demonstrate that the drug substance and drug product are within acceptable chemical and physical limits for the planned duration of the proposed clinical studies. Additionally, each pharmaceutical product that is to be marketed in the United States needs to have an expiration dating period assigned. The speaker elaborated on considerations for designing and executing a proper stability study that would generate appropriate stability data to support a proposed expiration period and presented two case studies on this subject.  

Design of stability indicating methods utilizing  QbD concepts—a phase-appropriate approach

The speaker presented a unique approach on the design of stability-indicating methods utilizing quality-by-design (QbD) concepts in a phase-appropriate manner from the beginning of clinical development. The analytical target profile (ATP) is defined early on to describe the method performance requirements to measure a specific critical quality attribute (CQA) of the drug product. The principle of continuous learning and improvement is applied as the method evolves in parallel with the drug development process; the final method will, therefore, incorporate the impact of the critical method parameters and formulation and process variables on the method performance. In conclusion, applying QbD concept to the design of analytical methods in a phase appropriate manner provides a scientifically sound method at all stages of drug development with good understanding of method risks and critical method parameters, hence offering better assurance of the robustness and long-term performance of the method.  

Drug-product fingerprints:  stability-indicating spectroscopic tests 

Control strategies for ensuring the quality of drug products rely on stability data to identify acceptable ranges for ingredients, processing conditions, and storage/shipping conditions. The speaker provided an example in which degradation product and impurity testing of drug products were waived by proving that process-related impurities contained in the drug substance were the only source of impurity content of the drug product and that no new impurities or degradants were formed during the manufacture of drug product or at the long-term storage, accelerated, and stress conditions used in long-term stability studies. The use of molecular spectroscopy to monitor form conversion during a drug product stability program was also described. Near infra-red (NIR) and powder x-ray diffraction (PXRD) were able to detect changes in crystallinity for stressed drug products subjected to moderate and extreme conditions. Dissolution testing, however, did not identify crystallinity changes of the API (BCS I). Impurities were detected in samples of lowest crystallinity. The use of NIR provided detailed understanding of the impact of storage conditions, temperature excursions, and packaging types on crystallinity. In summary, both traditional and emerging techniques offer insight to stability profiles.  

Method validation at pre- and  postapproval stages utilizing QbD approaches

The use of design of experiments (DOE)/QbD method validation approaches to support stability programs was discussed. The speaker presented a unique approach using DOE to validate a range of formulations, so that formulation changes within this range do not require revalidation. This is coupled with accelerated stability modeling tools to ensure formulation and process changes do not generate new degradation products which require revalidation. Case studies were presented using DOE/QbD to define a formulation operating range, including one where DOE was used to assess intermediate precision to ensure that there is no increase in method variability. The speaker also provided an example of the accuracy to precision model, a key DOE/QbD output, starting in early development with a generic gradient high-performance liquid chromatography (HPLC) method, followed by a product specific gradient method, an isocratic HPLC method and finally, an ultra-performance liquid chromatography (UPLC) or process analytical technology (PAT) method for product commercialization. This use of DOE/QbD and accelerated stability models provides powerful tools for developing a lean stability program based on sound science and statistical rigor.  

ICH Q1B photostability guideline —time for a revision? 

The presentation, based on a recent publication (1), highlighted the deficiencies with the International Conference on Harmonization (ICH) Q1B photostability guideline implemented in the US, EU, and Japan. The presenters noted that since publication in November 1996, the guideline has provided a useful basic protocol for testing of new drug substances and associated drug products for manufacturing, storage, and distribution; however, the guideline does not cover the photostability of drugs under conditions of patient use. Areas that would benefit from revision include specifications of the option 2 UVA and visible lamp choices as well as the current recommendation of quinine as an actinometer, which should be specified only for a specific option 2 UVA lamp. These assertions were supported with examples and literature references.  

Designing stability studies for global development programs 

A global approach to stability beyond ICH requirements was discussed. Case studies on post-approval changes and emerging market draft guidelines were shared. A decision tree with consideration of product stability and the countries where the drug is marketed provided a clear recommendation for long-term and accelerated stability conditions. Current emerging market draft guidelines including the draft ASEAN stability and variations guidelines and challenges associated were outlined for group discussion. Key messages from the presentation were that regional stability guidance exists for emerging markets and may be different from the WHO stability guideline. Science- and risk-based approaches are not always accepted. Some new guidelines indicate an acceptance of stability commitments instead of upfront data for process changes. The ICH Global Cooperation Group, which includes six regional harmonization initiatives APEC, ASEAN, Global Cooperation Council, PANDRH, SADC East Africa Community, are making improvements towards harmonization. 

Artifactual formylation of the secondary amine of duloxetine hydrochloride by acetonitrile in the presence of titanium dioxide: implications for HPLC method development 

This presentation was based on a recent publication (2) that showed that duloxetine hydrochloride, a secondary amine containing pharmaceutical, undergoes N-formylation as an artifact of sample preparation prior to HPLC analysis for impurities. The reaction is catalyzed by sonication and/or light in the presence of titanium dioxide and is proposed to occur via a hydroxyl radical-initiated mechanism. This reaction can be eliminated or minimized by replacing acetonitrile with methanol, or by simply adding at least 10% methanol to the sample diluents. The authors provided a rationale for the use of methanol considering that 1) sonication is commonly used to aid dissolution of pharmaceuticals in acetonitrile for HPLC analysis, 2) titanium dioxide is a commonly used excipient, 3) the amount of light found in modern analytical laboratories is sufficient to trigger this reaction, and 4) secondary amines are present in the structures of many pharmaceuticals.  

Strategies for controlling genotoxic degradants in  drug products: mitigation strategy and a case study

Brian W. Pack, Evan M. Hetrick, Linda Dow, Steve Baertschi, and Marvin Hansen 

This presentation outlined a novel strategy implemented at Eli Lilly that hinged upon stress studies which have been well designed to understand the most probable degradation pathways a compound may undergo, thus limiting the number of potential degradation products to assess for genotoxic potential. The development of an analytical method with a limit of quantification (LOQ) at 10% of the threshold of toxicological concern (TTC) was recommended if the potential degradant had an alerting structure and was Ames positive. It was proposed that an inactive degradation pathway of <10% TTC in the drug product long-term stability profile indicated that appropriate due diligence had been demonstrated, and hence would pose no risk to patient safety. The speaker used a case study to demonstrate that genotoxic impurities (GTI) levels at the end of the recommended shelf life can be predicted with the information based on Arrhenius predictions from accelerated stability studies used to quickly screen multiple formulations. This approach enables informed decisions to be made around formulation, package, and storage conditions relating to GTI formation.  

Dissolution failure and failure mode analysis  of a hot-melt extrusion product—a case study 

The step-by-step investigation of a dissolution failure of a melt extrusion product, which failed at six months under accelerated stability conditions, was discussed as case study. Because the initial investigation did not result in identifying the root cause, a five-factorial/eight-experiment design was used to evaluate the robustness of the method based on a normal probability plot of the data generated from the DOE. Products cured at 50°C were analyzed using solid-state nuclear magnetic resonance (SSNMR), environmental electron scanning microscope, and time of flight-secondary ion mass spectroscopy (TOF–SIMS). The dissolution failure was found to be caused by the stearyl alcohol migrating to the surface of the product when exposed to heat. 

Stability testing to support distribution of  temperature-sensitive pharmaceuticals 

This presentation discussed the other types of testing which may be conducted in addition to the standard ICH conditions that permit a stability budget to be created for a pharmaceutical. Besides using data from long-term and accelerated testing such as that provided for in the ICH guidances, the speaker proposed adding freeze-thaw and temperature cycling studies to create a fuller picture of a drug's susceptibility to temperature changes during the entire distribution process from manufacture to transport, storage, and end use. It was shown that the concept of time out of refrigeration, which allows for room temperature operations such as packaging and labeling of refrigerated products, can be expanded to the entire distribution process.  

Effective approaches for conducting method transfer

Method transfer is a process of which an analytical laboratory is qualified to perform a testing procedure as part of method validation. The speaker discussed the options of transfering analytical procedures from one laboratory to another and effective approaches to be considered when conducting method transfer. Transfer activities are conducted according to a protocol with predetermined acceptance criteria agreed upon by all sites involved. This includes certain SOPs such as data review, data reporting, and out-of -specification (OOS) / out-of-trend (OOT) investigation from both sites. Conclusion of the transfer must be documented with all data reported. It is important that validation data are available to the receiving lab as part of the transferring background package and the receiving lab must conduct a thorough gap analysis before any testing can be done.  

Interesting and challenging stability-related  regulatory questions: a roundtable discussion 

Panelists: Stephen Colgan, Robert J. Timpano, Ganapathy Mohan, and David Lin

The roundtable discussion was focused on regulatory queries, with science and risk-based approaches to stability/shelf-life and stability protocols being of particular interest. Firstly, it was noted that FDA does not provide guidance on biorelevance in stability protocols; the audience was, however, encouraged to use science to support stability testing protocols. Secondly, whilst scientific engagement with the regulators in the ICH regions would be welcomed, this is not the case for most of the emerging market regions. There was also a discussion that science-based stability protocols should only focus on the relevant product attributes because this approach would be leaner, and would protect the patient as well as non-lean protocols. The panel noted that the quality target product profile (QTPP) could be leveraged to advocated lean stability protocols.  

The most enthusiastic discussion was on a liquid product in a semi-permeable or non-permeable container and the suitability of a matrixed stability protocol for containers stored upright, upside down, and lying down. Developing a matrixed protocol can be difficult and the panel recommended reviewing the protocol with the regulatory authorities before execution. From a scientific point of view, the panel noted that a stability risk assessment would help define attributes that should be monitored for stability, including effects of container orientation, and determine whether a matrixed approach was required. It was agreed that science and knowledge of the regulations should be key drivers when developing stability protocols.  

*To whom all correspondence should be addressed. 

 1.  S.W. Baertschi, K.M. Alsante and H.H. Tonesen, 

AAPS Workshop Summary

	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.

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