Brian W. Pack

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.

Articles

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

Cleaning validation and verification are based on the premise of risk management. Several regulatory and guidance documents make this clear. The International Conference on Harmonization's (ICH) guideline on risk management outlines several approaches to making and documenting risk-based decisions (1). It clearly states that risk management should be based on scientific knowledge and that personnel should evaluate the effect of potential failures on the patient. In addition, it notes that the levels of effort, formality (e.g., use of tools), and documentation of the quality risk-management process should be commensurate with the level of risk.  

 states that equipment and utensils shall be cleaned, maintained, and sanitized at appropriate intervals to prevent malfunctions or contamination that would alter the safety, identity, strength, quality, or purity of the drug product (2). In accordance with 21 

 211.67, ICH issued recommendations on equipment maintenance and cleaning (Q7A, Sections 5.20–5.26) for compliance and safety that include similar, but more detailed requirements (3).  

The US Food and Drug Administration's 1993 guidance on cleaning inspections states that for a swab method, recovery should be established from the surface (4). The guidance contains no specific requirements about how to establish these recovery estimates, or the acceptance limits. It is up to the manufacturer to document the cleaning rationale (i.e., process and acceptance limits) for maintaining the quality and purity of the drug product being manufactured.  

Cleaning verification consists of routine monitoring (e.g., swab analysis) of equipment-cleaning processes. Cleaning validation confirms the effectiveness and consistency of a cleaning procedure and eliminates the need for routine testing (5). For example, cleaning limits are established to determine the maximum allowance of Product A that can carry over to Product B. The calculation of these limits is well documented and includes factors that increase the margin of safety to protect the patient (6, 7). Because it is not feasible to swab every square inch of the equipment, swabbing locations are chosen based upon factors such as how difficult the area is to clean, the size of the equipment, and the areas where product buildup is likely. All product-contact surfaces must be considered during cleaning verification to demonstrate that equipment is clean, and a recovery value is expected to be established for each product-contact surface during method validation. The recovery is used to correct the submitted swab result for incomplete removal from the surface and to compare it with the acceptance limit. This last aspect of risk management (i.e., establishing the surface recovery) is the focus of this article.  

Analysts have many ways to establish the swab-recovery value for a particular product-contact surface. Stainless steel is the most common material in a manufacturing environment (see Figure 1). Some companies therefore establish a recovery value for stainless steel and apply that standard to all swab submissions. Other companies attempt to establish a recovery value for each product-contact surface for every compound. From an analytical standpoint, supporting this activity becomes arduous, if not impossible to sustain. For example, equipment in a clinical-trial materials (CTM) manufacturing area is used for many compounds in the company's portfolio. New equipment might have different product-contact surfaces. Each compound in the portfolio manufactured on a new piece of equipment would require a method revalidation to add a recovery factor for the new product-contact surface. As the number of materials of construction increases, the difficulty of sustaining that approach also increases. Grouping materials of construction for analytical-method development in support of cleaning verification and validation activities is an excellent opportunity to apply a quality risk-management approach, especially when the total product-contact surface area is considered. Stainless steel accounts for approximately 95% of the surface area in a CTM manufacturing and packaging environment. Other product-contact surfaces account for only 5% of the total surface area. When polymer surfaces are considered in a CTM packaging environment, the number of minor product-contact surfaces can grow significantly. A risk-management approach allows the majority of the time and effort to be spent on activities that ensure the cleanliness of the stainless-steel area while identifying, analyzing, evaluating, and communicating the risks associated with the small fraction of remaining surfaces. This strategy does not ignore the surfaces other than stainless steel, but divides them into three recovery groups to support analytical-method validation. By choosing representative recovery surfaces for those nonstainless-steel materials, the effort proportionally addresses the risk.  

Figure 1: (ALL FIGURES ARE COURTESY OF THE AUTHORS) 

Several variables (i.e., roughness average, material of construction, active ingredient, and spiked amount) were evaluated in a randomized fashion to prevent systematic bias that could be introduced by going from the lowest to the highest acceptance limit, from the smoothest to the roughest surface, or from one material of construction to the next. The initial design of experiments included two active pharmaceutical ingredients (APIs), three spiked acceptance-limit levels (i.e., 0.5, 5.0, and 50 μg/swab), seven surface types, four target roughness averages (Ra < 25, 75, 125, and 150 μin.), and six replicates per surface. These Ras were targeted to evaluate whether surface recovery depended on the surface Ra. Coupons were divided into a group of polymers [i.e., Lexan (polycarbonate), acetal (Polyoxymethylene), and PTFE] and a group of metals (i.e., stainless steel 316L, bronze, Type III hard-anodized aluminum, and cast iron). These surfaces were chosen to represent a cross section of surfaces found in the CTM manufacturing and packaging areas and required 1008 swab determinations to complete the study. The remaining product-contact surfaces found in the clinical-trial manufacturing and packaging areas were evaluated according to the initial design of experiments. These surfaces included nickel, anodized aluminum, Rilsan (polyamide), Oilon (blended-oil nylon), and stainless steel 316L with a 4 × 4-in. area. 

The authors chose two APIs for this evaluation on the basis of their solubility profiles to represent the most- and least-soluble compounds a company would likely manufacture. Compound A, the less soluble, is slightly soluble in methanol and insoluble across the pH range, but Compound B is soluble in all solvents. In addition, Eli Lilly (Indianapolis, IN) identified Compound A as one of the most difficult compounds to clean from equipment, based on its low solubility and staining properties. A control (i.e., stainless steel 316L, 0.5 μg/swab, Compound A) was run each day that data were generated. 

The authors used an Agilent 1100 high-performance liquid chromatography (HPLC) analyzer (Agilent, Santa Clara, CA) for all experiments. The HPLC operating conditions were validated according to ICH standards for precision, linearity, limit of detection (LOD), limit of quantitation (LOQ) and specificity (see Table I) (8). Precision was 1.85% and 3.13% for Compounds A and B, respectively, and was determined at 0.025 μg/mL (i.e., 25% of the lowest spike). The method was linear across the equivalent range of 0.5 μg/swab to 5 μg/swab (R = 0.999). The LOQ was calculated to be 0.005 μg/mL for Compound A and 0.008 μg/mL for Compound B. The LOD was calculated to be 0.001 μg/mL for Compound A and 0.0024 μg/mL for Compound B. Swabs and solvents did not result in interfering peaks. The authors performed swabbing consistently using Texwipe Alpha large swabs (ITW Texwipe, Kernersville, NC). First, 10 vertical swipes, then 10 horizontal swipes were performed for the 2 × 2-in. surfaces. For the 4 × 4-in. surfaces, 20 swipes were executed in each direction. Methanol was used as the swabbing solvent. Spike amounts were 0.5, 5, and 50 μg per surface and were extracted into 5 mL of mobile phase, which corresponded to 0.1-, 1.0-, and 10-μg/mL standard concentrations, respectively. The authors used a Quanta FEG 200F field-emission scanning electron microscope (SEM, FEI, Hillsboro, OR) to generate the surface images.  

Table I: High-performance liquid chromatography (HPLC) operating conditions. 

In this study, a single analyst evaluated the analytical swab recovery from a representative set of surfaces found in the CTM manufacturing and packaging areas. The surfaces were manufactured specifically for this study to have a broad range of Ras. In addition to Ra, the effect of the material of construction, acceptance limit, compound, and method variability also were evaluated. Based upon these data sets, the authors used a strategy involving three groups of materials to represent all of the surfaces in CTM operations. Merck and Co. used a similar strategy to establish five recovery groups (9). The authors expanded on Merck's strategy by adding a detailed study supporting the groups and an approach for determining the appropriate placement of new surfaces into pre-established groups. 

 The Ra targets listed above were difficult to achieve. The intermediate Ra values were significantly lower than the target values given in the design of experiments section above. Both intermediate Ra values, initially targeted for 75 and 125 Ra, were measured to be approximately 40 μin. Although the machining process at each level yielded visually different surfaces, the measured Ra changed little from surface to surface. The authors decided to proceed with the surfaces and define smooth surfaces as Ra < 100 μin. and rough surfaces as Ra > 100 μin. This approach allowed for an assessment of the anticipated relationship between Ra and analytical recovery. 

The Ra had little impact on the observed analytical-swab recovery, but the recovery was expected to improve with lower Ras. Figure 2 shows roughness grouped by surfaces that had a measured Ra > 100 μin. and by surfaces that had a Ra < 100 μin. Only 5- and 50-μg spikes are represented in Figure 2; the variability in the 0.5-μg spikes confused the interpretation of the data slightly, but is consistent. As Figure 2 shows, the recovery within each roughness group was approximately the same for a given analyte on a given material and did not correlate to Ra. Therefore, Ra should not be used as a predictor of analytical recovery or as a grouping criterion.  

 Because Ra was eliminated as a factor contributing to recovery losses, the authors performed data analysis by combining all average recovery values and assessing the effect of the material of construction. The data in Figure 3 were first separated by API, and groups were generated to represent the logical separations in recovery. Figures 3(a–c) contain the data for the 0.5-μg spikes, the 5-μg spikes, and the 50-μg spikes, respectively. The data from the 0.5- and 5-μg spikes exhibited a trend similar to that of the 50-μg spikes. The variability in the results increased as the spiked amount decreased, and the 50-μg spike results were substantially less than that of the other spike levels.   

For both compounds, the Type III hard anodized aluminum exhibited the poorest recovery. The next logical break point grouped bronze and cast iron. The recovery of Compound B from bronze suggested that the material was representative of Group 1. The recovery of Compound A on bronze was lower and more variable, however, so the authors placed bronze into Group 2. For the majority of the surfaces, the recovery of Compound A was lower than that for Compound B at a given limit. In some cases, the recovery was approximately the same (i.e., of 5- and 50-μg spikes on cast iron, and of the 50-μg spike on Type III hard anodized aluminum). In addition, the predominant trend was that the average recovery of a compound increased as the spiked amount increased on a given material of construction. For example, the recovery of Compound B from stainless steel 316L was approximately 74%, 90%, and 95% at 0.5-μg, 5-μg, and 50-μg swabs, respectively. 

Ra was originally considered a variable in the experiments previously outlined and did not affect swab recovery. To understand the surface attributes that might contribute to incomplete recovery for the different materials of construction, the authors acquired SEM images for Group 1, Group 2, and Group 3 surfaces (see Figure 4). Stainless steel is a relatively smooth surface with some striations from machining (see Figure 4a). Cast iron has a pitted surface that could provide opportunities for an API in solution to be trapped during a spiking experiment (see Figure 4b). The anodization process makes Type III hard anodized aluminum, the worst recovery surface, porous, thereby creating the greatest opportunity to lose analyte (see Figure 4c).   

Note that polymers were grouped together with metals and might not be considered to be similar on first pass. The SEM image of Lexan in Figure 4d, however, illustrated that the polymer surface was smooth, albeit with some surface debris, which prevented the loss of analyte. The polymer surface was grouped with stainless steel in Group 1. The SEM images were good supporting evidence that the groupings were logical based upon surface characteristics.  

Table II is based on the data shown in Figure 3. The top surface in Table II represents the surface that was validated for recovery in each group. This recovery value represented all others within a given group. The groupings were supplied to the CTM areas, and the group number was included on the swab submission to the analytical laboratory so that the correct recovery factor was applied to each surface. In addition, the table served as a tool for engineering to determine whether newly purchased equipment contained a new product-contact surface.  

Table II: Grouping of material surface of construction.  

 The model and worst-case compound evaluation did not replace any analytical-method validation activities. Analytical recovery must be established for each compound in the portfolio, but not on all surfaces. If multiple limits are to be considered, or if a range of reporting is required, the lowest limit may be evaluated, and that recovery can be applied to all acceptance limits as a conservative estimate. In the analytical method, three recovery factors were presented: Group 1, Group 2, and Group 3. Methods could be validated for any surface within a group and could be considered representative. The authors chose stainless steel 316L because it is the most prevalent, and cast iron because it is a common material on a tablet press. Type III hard anodized aluminum is the only surface in Group 3. This strategy did not ignore any uncommon surfaces. It grouped them appropriately, swabbed them, and applied a representative recovery factor. 

 Method variability was evaluated by performing a control sample (Compound A, 6 replicates, 0.5-μg swab, stainless steel 316L, Ra = 3.5) each day. The mean recovery of the entire experiment was 52%. These data suggested that the swabbing ability of the analyst did not change over time. The standard deviation within a day typically was less than 6. The pooled-within-run standard deviation was 3.99 over the course of the experiments. This value was used as a criterion for grouping new surfaces. The day-to-day standard deviation was 15.34. 

Incorporating new materials of construction into the grouping strategy.

 Periodically, new equipment will be introduced into the CTM area that incorporates a product-contact surface made of a material of construction that is not listed in Table II. This problem is often caused by alloys of metals that have already been evaluated and by polymers of proprietary composition. Because surface recovery must be evaluated, personnel need a way to incorporate new surfaces into the groupings outlined in Table II. When a new piece of equipment is purchased, CTM-engineering employees prepare the needed documentation to evaluate the equipment with regard to the cleaning program before use. If an identified sampling location is made of a new material of construction, the engineer asks the person responsible for the cleaning program and analytical development to perform the next steps, which are shown in Figure 5.  

Suppose that new equipment incorporated three new materials: a crystalline thermoplastic polyester marketed under the trade name of Ertalyte (Quadrant Engineering, Reading, PA), stainless steel 420, and stainless steel 630. Without the grouping strategy in place, method revalidation would have to occur for all compounds handled by this piece of equipment. With the strategy in place, these surfaces are placed into groups based on model-compound recovery. No method revisions are required. 

The analytical recovery of Compound A was evaluated for Ertalyte, stainless steel 420, and stainless steel 630 at the 5.0-μg/in.

  level. The authors used the validated method to evaluate the recovery of the three new surfaces compared with a representative surface from Group 1 (i.e., stainless steel 316L), Group 2 (i.e., cast iron), and Group 3 (Type III hard anodized aluminum). Recovery was evaluated for both the group representative and the new surfaces on the same two days with three replicates on each day. As an alternative, six replicates may be performed on the same day as the controls because the comparison of recovery is relative. 

The new surfaces are placed in one of the three groups or define a new lower group, based on how close their average is to that of the group control. The authors obtained a cutoff value of 3.0% in the following manner. Based upon the data for the control, the within-day standard deviation was calculated to be 3.99 and was used in Equation 1. A series of one-sided hypothesis tests with an error rate of α = 0.10 were performed to assess whether the new surface mean was less than a specified control-surface mean. The confidence limit half-width for the difference between the means of two surfaces was computed using the within-day standard deviation because the replicates for each surface had to be run on the same two days, with each day treated as a block. For these calculations, it was assumed that this standard deviation was known. The lower one-sided confidence limit for the difference in means was derived using the following steps:  

This calculation did not indicate a difference between a control surface and the new surface under evaluation if the recovery differed by less than 3.0%. This approach was conservative because Eq. 1 categorized a new surface into Group 2 if it differed from stainless steel by more than 3.0%, which could be viewed as a strict criterion. Because the results were obtained on the same days and runs, the authors believed that this approach was reasonable. When evaluating the recovery of a new surface, this strategy helps personnel to place each material into the appropriate group. The grouping starts with a comparison of the new surface average to that of Group 1 (stainless steel 316L) and continues sequentially. If the new surface recovery (NSR) is more than 3.0% less than that of the group reference, it is compared with the reference surface in the next lower group until a group is found with which it does not differ by more than 3.0%. If no such group is found, then the new surface forms a new, lower group. The procedure is as follows:  

If the NSR > mean stainless-steel recovery – 3.0%, the new surface belongs in Group 1.

If the NSR > mean cast-iron recovery – 3.0%, the new surface belongs in Group 2.

If the NSR > mean Type III anodized aluminum recovery – 3.0%, the new surface belongs in Group 3.

If the NSR < mean Type III anodized aluminum recovery – 3.0%, the new surface becomes a new group or becomes the worst-case surface for Group 3 and is used in all future method validations.

The data for the three new surfaces are outlined in Table III. Based on this approach, Ertalyte was placed into Group 1 because the difference between its recovery and that of stainless steel 316L (i.e., Group 1) was less than 3.0% (i.e., 2.48%). The recovery from stainless steel 420 and stainless steel 630 was more than 3.0% less than that from stainless steel 316L, but greater than that from cast iron. The authors placed stainless steel 420 and stainless steel 630 into Group 2.  

Table III: Swab recovery of three new materials of construction compared with controls from each representative group. 

The placement of these two grades of stainless steel into Group 2 highlighted the conservative nature of this approach because their recoveries were only 4% and 8% less than that from stainless steel 316L. The recoveries were 12% and 9% greater than that from cast iron for stainless steel 630 and 420, respectively. Table II was updated to reflect this placement. Because the grouping strategy was conservative, it prevented the underestimation of recovery factors when assay values were reported and prevented the formation of additional groups for method validation unless the recovery value for a new surface is sufficiently low to warrant such an addition. 

The authors' data-driven risk-management approach to cleaning verification methods uses analytical-recovery values for a model compound to place product-contact surfaces into groupings for analytical-method validation. The data generated during the studies supported the formation of three recovery groups to validate analytical swab methods. Groups 1–3 were represented by stainless steel 316L, cast iron, and Type III hard anodized aluminum, respectively. This approach allowed all surfaces to be considered during analytical-method validation and provided an objective mechanism to incorporate new surfaces into the strategy.  

The benefits of this strategy are numerous. First, only three surfaces must be validated on each compound, which drastically minimizes the number of recovery values established to support the entire portfolio. Second, the strategy includes a way to add new materials of construction to the cleaning program if new equipment is purchased. Traditionally, all swab methods must be revalidated to incorporate the new surface. With this strategy in place, a model compound is evaluated, the new surface is grouped, and no changes to existing methods are required. Third, the strategy allows for a constant state of compliance. A relative recovery value is known for any material of construction for all equipment.  

Because the grouping strategy is applied to a small fraction of the total surface area, no surface material of construction is ignored, each molecule undergoes a typical method validation, and the strategy places surfaces into groups conservatively. The authors believe that the strategy controls risks appropriately and that the data set given in this study scientifically supports the strategy of grouping materials of construction to support analytical methods within the cleaning program.  

The authors would like to acknowledge the following colleagues at Eli Lilly: Gifford Fitzgerald, intern, for generating the swab-recovery data; Ron Iacocca, research advisor, for the SEM data; Sarah Davison, consultant chemist; Mike Ritchie, senior specialist; Mark Strege, senior research scientist; Matt Embry, associate consultant chemist; Kelly Hill, associate consultant for quality assurance;  Bill Cleary, analytical chemist; and Laura Montgomery, senior technician, for their contributions and insightful suggestions throughout the project. In addition, Leo Manley, associate consultant engineer, provided the roughness measurements in support of this project. 

* is a research advisor for analytical sciences research and development, and 

 is a research advisor for statistics, discovery and development, both at Eli Lilly and Company, Indianapolis, IN, tel. 317.422.9043, 

Submitted: Oct. 12, 2009. Accepted: Dec. 22, 2009. 

The authors recommend a strategy for classifying similar nonstainless-steel surfaces into three groups based upon the analytical recovery that was observed in this study.