Mark Alasandro

Accelerated stability analysis is a strategy used to quickly evaluate alternative formulations, packaging, and processes. Accelerated linear studies are commonly performed and modeled; however, accelerated multiple-factor non-linear modeling has been a gap, and statistical software tools such as SAS/JMP do not directly have any provision to model multiple factor nonlinear responses. This paper outlines an approach to model and predict non-linear multiple factor stability/tablet dissolution data under accelerated and nominal storage conditions. 

There are many non-linear stability cases such as dissolution, leachables, and moisture. Being able to model these non-linear processes is crucial to proper drug development.  In addition to general non-linear modeling, there are multiple factors that may influence the non-linear curve. The following is a list of factors that may impact the asymptotes, growth rate, and inflection point of a curve:    

Stability storage temperature and humidity


Proper design of experiments for data collection and curve isolation is crucial for building non-linear models. 

 illustrates the factors that should all be square relative to all other factors and have zero correlation relative to each other. For this tablet dissolution example, multiple time points (minutes), multiple storage conditions (temperature), multiple drug substance particle sizes, and multiple weeks were measured. Percent dissolution was the response of interest.


The following is a step-by-step procedure for non-linear stability modeling and expiry determination.

Measure the data at multiple time periods, using multiple particle sizes and at multiple temperatures. Generate a plot of the data to visualize the relationship of the curves over time  (25-10-0: 25=Temperature, 10=Particle Size, and 0 = days) (see 


 Fit each curve individually. In this example, each dissolution curve was fit using a four-parameter logistics (4PL) curve. The four parameters are: upper asymptote, lower asymptote, inflection point, and slope of the dissolution curve.  R-Square should be high (typically above 0.95) and RMSE error should be low for each curve.  Outliers should be checked using the residuals.  Save the parameters of the curve.  In this example, there are four parameters, upper asymptote, lower asymptote, growth rate (slope), and inflection point (see 

 Save the parameters from the curve and the factors that influence them into a table. For this example, the growth rate and inflection point are the coefficients that may change the most based on the factors under consideration. The upper and lower asymptotes are not of concern for this problem as all of the curves have similar lower asymptotes and similar upper asymptotes, but upper and lower asymptotes could be important for other problems, so generally it is best to model all of the curve parameters (see 

 Fit the curve parameters with a least-squares multivariate regression. Growth rate, the slope of the 4PL fit, and inflection point are the most important as the dissolution starting point and the upper asymptote are essentially the same for all curves. Main effects and interaction models generally work best and p-values and F tests can be used to evaluate each model term (see 

 Save the equation from the multivariate parameter model.  An example of the inflection point model is in Equation 1.
  [Eq. 1]
  
  
  


 Substitute the growth rate (slope) and inflection point coefficients from the multivariate model into the nonlinear prediction.  The red box in 

 shows the substitution for the inflection point.

Check the model to make sure it matches the actual data. Correct any modeling errors by adding or modifying a multivariate model term. A simple YX regression plot of the model versus the measurement will indicate model quality and any systematic errors (see

Create a profiler from the equation to predict future dissolution rates.  This can be done using a modern statistical package such as SAS/JMP (see 

 Predict dissolution at any time, temperature, or particle size combination using the profiler.  For this example, particle size was set to 5 μm, temp to 25 and time in weeks to zero.  The dissolution time was fixed at 100 min with a specification of not less than 90% (see 

 From the profiler at each time point (weeks), make sure the time (min) and particle size (5 um) are fixed, determine dissolution at the nominal temperature (non-accelerated condition).  Fit the rate of degradation using either a linear or nonlinear model from the profiler predicted data.  In this case, the rate of dissolution is not linear so a non-linear curve is fit to the data and the expiry is determined based on the extrapolated curve (see 

).
The same method is used for predicting both the nominal expiry and the 95% CI expiry.

 Finally, long-term stability evaluation at nominal storage conditions will be used to confirm the early model prediction and will provide an independent secondary determination of stability and changes in dissolution.  Understanding rates of change should factor into shelf life and release specification limits (1).


  Non-linear multiple factor analysis has long been a problem in a variety of process and product modeling and prediction. The novel procedure discussed in this paper for the characterization of multiple factor non-linear product performance provides a clear, statistically defendable method for determining dissolution and accelerated stability. Long-term verification of accelerated conditions should always follow early determinations of expiry, acceleration rates, and rates of degradation.

Q6A Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances

Mark Alasandro, PhD, is director, Allergan Irvine. Thomas A. Little PhD, is president, Thomas A. Little Consulting, drlittle@dr-tom.com. 

Articles

The right approach can provide a clear, statistically defendable method for determining dissolution and accelerated stability.

Multifactor Non-linear Modeling for Accelerated Stability Analysis and Prediction

The approach   provides the required International Conference on Harmonization   validation elements as well as information on                          interactions, measurement uncertainty, control   strategy, and continuous improvement. Despite being less resource   intensive than the traditional validation approach,   quality is not compromised. Additionally, through judicious planning,   the MVbD approach can encompass early formulation design efforts   so that a wide range of formulations is taken into consideration when   defining the method-validation design space.

Analytical method   validation is a crucial part of formulation development. It is needed   to ensure that methods provide accuracy                          and precision in detecting formulation   differences in drug dissolution, stability, active, and impurity levels.   Method validation is also key to meeting requirements of cGMP,   compendia, and the International Conference on Harmonization (ICH) for   testing and releasing clinical or commercial dosage   forms. During early development, formulations are often changed to adapt   to new                          preclinical and clinical data. Revalidating each   of these new formulations is resource intensive and affects development   timelines. 

The ICH Q2   (R1) validation guidelines (1) do not provide crucial information such   as how formulation changes affect method                          performance or what method critical validation   parameters need to be monitored and controlled. An ICH approach may not   provide                          a good understanding of a method-measurement   uncertainty, which is needed to ensure that the overall process   capabilities                          are met and that appropriate in-process controls   and specifications are set. This sort of understanding is needed to   meet                          FDA’s process validation guidelines (2). Once   the product acceptance criteria are established, the influence of assay   variation                          can be determined relative to product acceptance   rates.

This article   describes a method-validation-by-design (MVbD) approach to validate a   method over a range of formulations. It                          uses both design-of-experiment (DOE) and   quality-by-design (QbD) principles to define a design space that allows   for formulation                          changes without revalidation. The approach   provides the required ICH validation elements as well as information on   interactions,                          measurement uncertainty, control strategy, and   continuous improvement. This approach is less resource intensive than   the traditional                          validation approach without compromising   quality. Additionally, through judicious planning, it can encompass   early formulation                          design efforts so that a wide range of   formulations can be used to define the method-validation design space. 

MVbD is not   specifically addressed in ICH; however, it is supported by the   principles presented in ICH Q8, 9, 10, 11 (3–6)                          as well as ICH Q2 (R1). There are other industry   guidelines (2), publications (7–9) and presentations (10–15) that   support                          a QbD/DOE approach for analytical method   development and validation, including FDA’s 21st Century Quality   Initiative, which                          was first presented in 2001 and later updated in   2005 (15), and the outcome from FDA’s QbD pilot. 

The use of DOE is   well established for determining method robustness, such as how much   the mobile-phase composition, column                          temperature, and flow rate can vary. DOE is also   well used in formulation screening. This approach broadens DOE to   include                          method validation over a range of formulations.

The MVbD approach applies to these QbD principles: 

 of the potential critical validation parameters. Systematic analysis (e.g., fishbone diagram) is done based on historical                                knowledge. The QbD/DOE output confirms those that are critical. 

. Once the required process capability is known, the required method accuracy and precision acceptance criteria are defined                                in the ATP. 

. DOE output   defines those parameters that have the most impact on the method   performance. Monitoring these parameters throughout                                development will help define acceptable   ranges. 

. MVbD provides the acceptance criteria that must be met to move to new technologies. 

. Knowledge gained is cycled backed to accelerate the next program. 

Traditionally, each   new drug-product formulation requires validation to support clinical   testing. In early development, the                       method is validated for linearity, accuracy, and   precision. Method linearity is determined across five concentrations   from                       50% to 150% of the nominal (100%) concentrations.   Accuracy and precision can be combined with the linearity study by doing                       six replicates at the 100% (nominal) concentration   and three replicates at the other concentrations (50%, 75%, 125%, and   150%),                       which gives a total of 18 sample preparations. If   there are five new formulations during development that require separate                       validation, a total of 90 sample preparations would   be needed. This approach is resource intensive and affects project   timelines.                       In this given example, only one                       formulation component is varied. As more components   are varied, the workload increases proportionally. 

It does not statistically define a design space

A QbD/DOE approach   validates a method over a range of formulations within a defined design   space. Movement within this design                       space does not require method revalidation with   each new formulation. The DOE approach detects any excipient–API   interactions                       and critical validation control parameters. A DOE   approach is not necessarily more labor intensive than the traditional   method-validation                       approach and additional information gained is well   worth the exercise. As described, the traditional approach requires at                       least 90 sample preparations to validate five   formulations over the course of the development. Using DOE to validate   across                       a broader range that includes these five   formulations would require only three determinations for each of the   five formulations,                       resulting in a total of 15 sample preparations. 

Step 1: Define the range of formulations and required process capability

.   A formulation screening DOE may be used to determine all possible   clinical formulations for the study. Manufacturing process                             capabilities need to be considered to define   the ATP (i.e., the necessary accuracy and precision to ensure acceptable   data).                             Full factorial, fractional factorial and/or   custom (d-optimal) design all may be used in developing the study   design. 

Step 2: High-performance liquid chromatography (HPLC) method selection

.   A method should be developed such that sample preparations of the   different formulation can be diluted to the same API concentrations.                             The diluted sample from each formulation is   injected onto the HPLC column under the same chromatography conditions.   Standardizing                             these conditions will facilitate DOE and   latter method-robustness studies. 

. The set up of the DOE can be accomplished with or without using DOE software. Inputs to the DOE include a number of varying                             factors, such as the different API levels and/or excipient and preservative levels. 

.   Data are analyzed for linearity, precision, and accuracy, including   confidence intervals. Any interactions are reported                             and a design space is defined. The design   space is defined by fitting a model to the factors used in the   evaluation of assay                             concentrations and other key factors that may   interfere or influence assay precision or bias. After fitting the   model, the                             design space may be visualized using contour   plot or profilers. 

To illustrate the MVbD process, a simulated case   study is presented where three factors are varied over a range of   formulations                       (see Table I). The API concentrations are varied   from 0.005%, 0.01%, 0.015%, 0.02%, and 0.025% (w/w). Preservative   concentrations                       are either 0.01% or 0.03% (w/w) and concentrations   of Excipient 3 are either 0.5% or 0.8% (w/w).

. The DOE   pattern is presented as 1, 2, 3, 4 or 5 --, -+, +- or ++. The numbers 1   through 5 represent the five API concentrations                       and the “+” or “–” represent with or without the   two possible preservative and excipient concentrations. Three replicates                       are done for each combination of API, preservative,   and excipient concentration. A total of 60 sample preparations is   required.                       The DOE typically suggests a randomized sample   preparation to avoid any sample preparation variability; however,   because the                       variability is low, a standard sample-preparation   scheme can be followed.

Figure 1 also presents the percent recovery data.   The required ICH statistics can be obtained from these data. For   example, 

 shows linearity data along with   typical linearity statistics. One key output is the root mean square   error (RMSE); this parameter                       identifies method variability that is critical for   understanding the method contribution to the overall process   variability. 

 also shows linearity plots of   percent recovery versus the two excipient concentrations. The difference   in slopes indicates                       interaction (i.e., a lower API recovery at a higher   level of Excipient 3 concentration), possibly due to interaction of the                       excipient with the API. Such information is   important for the formulator and method developer to consider if higher   preservative                       levels are needed.

 presents the mean percent recovery   for each combination of API, preservative, and excipient along with the   corresponding                       confidence limits. In the example describe, there   was a somewhat lower API recovery with the higher excipient levels,   which                       is further illustrated in 

.   It is obtained by mathematically modeling the primary main effects and   secondary two-factor interactions as well as possible                       polynomials using a DOE software. The operating   range is the white space shown in Figure 4; it is where the method   accuracy                       and precision meet the acceptance criteria. Adding   formulations outside this range would require confirmatory testing.

System linearity, quantitation limits (QL), and detection limits (DL) 

.   To ensure the sample amount injected is within the linear range of the   detector, a separate experiment can be done where                       the sample concentration is varied from 50% to 150%   of the nominal (100%) concentration. If the potency method is also used                       to quantitate impurities, a wider linearity study   can be performed from 100% to 0.03%. The QL and DL for the impurities   can                       be determined by the ratio of RMSE to the slope, as   described in ICH Q2 (R1). 

 shows there is less precision (i.e., higher standard deviation and   confidence values) at the higher API levels for lower                       amounts of Excipient                       3. This lower precision is approaching the   acceptance limit. Similarly, accuracy is approaching the acceptance   limit as the                       excipient and API levels increase. These parameters   need to be monitored in case the method needs to be optimized prior to                       transfer to the final manufacturing site(s). 

 shows a graph of the balance between precision and bias and its   influence on product acceptance/failure rates based on the                       DOE data. Combinations of method precision and bias   must fall within the designated white space to meet the acceptance   criteria.                       The equation for how precision and bias influence   product acceptance rates is as follows:

LSL = lower acceptance criteria, USL = upper acceptance criteria, bias = mean percent recovery - 100%, nominal = 100%, and                       precision = mean standard deviation. 

The prediction profiler (bottom graphs) in 

 allows the precision and bias to be varied to determine the impact on %   acceptance rates. This tool can be used to justify                       moving to new technologies and new specifications   by showing that the acceptance criteria will still be met. 

. The lower recovery of API observed at high levels of excipient concentrations adds to the formulator’s knowledge base. If                       higher excipient concentrations are needed in future formulations, this aspect needs to be considered. 

Regulatory strategy and potential hurdles

Since the MVbD approach is not specified in ICH regulations, not all regulatory agencies may accept this approach. Some filing                       strategies are briefly discussed. 

: The MVbD approach can be   presented in an investigational new drug (IND) application and discussed   at the end of Phase II                             chemistry, manufacturing, and controls (CMC)   meeting. The details can be present in a MVbD design protocol along with   a rationale                             for moving within the design space without   revalidation. Moving outside the design space could be justified through   the use                             of comparability protocol. 

:   Submission of the MVbD rationale, justification, and protocol early in   the development process is warranted since a face-to-face                             conversation may not be possible.   Alternatively, this information can be supplied when responding to any   agency questions. 

The authors describe a method-validation-by-design (MVbD) approach to validate a method over a range of formulations using both design-of-experiment and quality-by-design principles to define a design space that allows for formulation changes without revalidation.

Method Validation by Design to Support Formulation Development

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.

Strategy for use dating and use-date extensions. 

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