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Best Practices for Characterizing Formulation Design

BioPharm International, March 2010 Issue (PDF)

India has long been an important producer of small-molecule active pharmaceutical ingredients (APIs) for Western pharmaceutical companies, particularly in the generics sector. In fact, India currently accounts for approximately 8% of all global pharmaceutical production, and  India's contract manufacturing market is growing more than three times the rate of the global contract market, according to a new survey conducted jointly by the Organization of Pharmaceutical Producers of India and Ernst & Young analysts.

Now, as the biopharmaceutical sector continues to grow, many wonder whether India can take a similar role in the biologics arena. Key questions, however, surround India's regulatory oversight, intellectual property protection, and compliance with current good manufacturing practices (cGMPs) (see box). Furthermore, recent high-profile problems with India's small-molecule manufacturing, such as the US Food and Drug Administration's September 2008 ban on imports from two Ranbaxy sites, because of consistent failure to comply with cGMPs, heighten concerns about quality. 

Ongoing Concerns about Offshoring to India 

Yet the increasing importance of biologics makes the eventual offshoring of biologics manufacturing to India seem a likely path. Biologics are expected to account for almost 50% of all approved new pharmaceuticals by 2010.

  Yet biologics also have tended to be very costly, and it is expected that biosimilars will become increasingly important in the West, as Europe's biosimilars market grows and especially once legislation is passed to create a regulatory pathway for biosimilars in the US. The biosimilars market is likely to offer India the greatest opportunity for manufacturing biologics for the West. 

COLLABORATION BETWEEN WESTERN AND INDIAN COMPANIES

One way that some Western companies are seeking to take advantage of the cost advantages of offshoring to India while reducing risk is through collaborations.  

For example, the Swiss-based contract manufacturing organization (CMO) Lonza, has recently announced plans to invest in two major projects in the Genome Valley outside of Hyderabad—India's first state-of-the-art biotech complex for life science research, training, and manufacturing. Lonza's investment, which is scheduled to begin in 2011, is expected to take place in two phases. Both phases will include expanding manufacturing capabilities as well as biologics research and development.

  Another example is the Indian CMO, Kemwell, which recently announced plans to build a new biopharmaceutical manufacturing plant in Bangalore, in collaboration with the German company Boehringer Ingelheim (BI).

Lonza and BI together hold over half of the market for outsourced protein APIs.

  The decision by Lonza and BI to make these important investments in manufacturing facilities to India reflects the West's changing view on offshoring biologics to India and will facilitate future collaborations between Indian manufacturing companies and other multinationals. 

Western CMOs are not the only ones investing in India, of course. For example, Mumbai-based Reliance Life Sciences, which started off in 2001 developing stem cell products and expanded into biopharmaceuticals in 2006, set up a collaboration in 2007 with GeneMedix, a UK company with a pipeline of biosimilars.

Other Indian biotech firms, meanwhile, are developing biologics based upon technology transferred from abroad. For example, Bharat Biotech International (Hyderabad) and the Serum Institute of India (Pune) have licensed various vaccine technologies from institutions in Canada, the United States, and the Netherlands. Bharat Biotech International is the first vaccine manufacturer in a developing country to produce a foreign proprietary product, i.e., Wyeth's (now Pfizer's) 

Despite the success of some of these international collaborations, however, India's biotech sector has not yet reached its potential, and Indian CMOs have not yet acquired significant quantities of foreign biologics manufacturing contracts. Collaborations have been limited by the concerns of Western companies regarding both quality and IP protection, as mentioned above. 

Therefore, India's continued success in competing with other emerging countries, such as China, will depend on the country's ability to address the concerns of Western biopharmaceutical companies. The Indian government must better ensure that regulations to improve quality control and regulatory oversight are enforced, and that training programs for both biologics regulatory approval and manufacturing practices are improved.  

Western companies who  choose to work in India, meanwhile, must make a conscious effort to address India's regional cultural and linguistic differences by incorporating professional translation and interpreting services into their business strategies, and help to provide specific training in the areas in which India is lacking.  

Greater collaboration between Western and Indian companies means fostering an unprecedented level of partnership between the two. However, the result—new quality products that are available to more people for less—may be worth the effort. 

 is the director of biopharmaceutical and pharmaceutical research at Language Connections, Brighton, MA, 617.731.3510, 

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http://www.contractpharma.com/articles/2009/09/india-report

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3. Martino M. Lonza invests 150M in Hyberabad. Fierce Biotech. 2009 May 22. Available from: 

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http://pharmtech.findpharma.com/pharmtech/News/Kemwell-To-Build-Biologics-Manufacturing-Facility-/ArticleStandard/Article/detail/602702

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http://www.icis.com/Articles/2009/01/20/9185770/asian-contractors-aim-for-growth-in-biologics.html

6. Frew SE, Rezaie R, Sammut SM, Ray M, Abdallah S, Daar AS, Singer PA. India's health biotech sector at a crossroads. Nature Biotechnol. 2007;25(4):403–17.  

7. Dhatta J. India turning capital for counterfeit drugs. The Hindu Business Line. 2 Aug 2003. Available from: 

http://www.blonnet.com/bline/2003/08/03/stories/2003080301260500.htm

Perspectives on Outsourcing

Collaborations between Western and Indian companies may provide the best path for offshoring successfully and for developing India's readiness.

India's Future as a Biologics Manufacturing Hub

Downstream processing used to be the Rodney Dangerfield of biopharmaceutical manufacturers ... cleaning up crude bulk product got no respect, especially after the relatively glamorous upstream manufacturing from living organisms. Today, that's changing because outdated filtration, chromatography, and purification steps are creating real bottlenecks.

  As a result, both manufacturers and vendors are looking hard at new technologies to improve their downstream systems. This is the first column in a series that will discuss new technologies for downstream processing.  

Most manufacturers agree that the cost and complexity of chromatography steps are the real sticking points, and our current 7th Annual Biomanufacturing Survey data shows that 53% of biopharmaceutical managers feel it's the biggest downstream problem today. Yet, even as internal company pressures to reduce operating costs grow, most managers still concede that major breakthroughs are unlikely in the short term. On the other hand, they also accept that small, incremental improvements are unlikely to dramatically lower overall costs. The technical change that led to the downstream bottlenecks is, of course, the increase in upstream fermentation and cell culture yields. This is unlikely to slow, and the continuous yield improvements for target proteins continue to burden downstream operations.  

So, where are we going to find relief? There's an increasing push to move away from traditional Protein A as an affinity chromatography ligand and find solutions that are cost-effective and readily acceptable to regulatory authorities. And even though few companies want to be the first to blaze the regulatory approval trail, many are considering the move. In fact, for new production units, 35% of the industry is considering alternatives to Protein A today.

At present, few real commercial options exist, but promising technologies are on the horizon or entering commercial production. We do expect to see improvement, including membrane processes, monoclonal-fragment technology, and more specialty resins and synthetic affinity matrices that are priced near Protein A.  

It's a matter of time before an alternative to traditional chromatography for antibody purification becomes an industry norm. Eventually, the industry and the FDA will move away from tried-and-true methods of purification, but when that happens, simpler, cheaper, and FDA-approvable alternatives are likely to take hold rapidly.  

Our survey data show that most companies are already investigating new technologies. Those not paying attention may get stuck with manufacturing processes for their pipeline products that are simply not competitive. 

So it's not surprising that most are not sitting still on the issue. Our current study illustrates the dramatic changes now emerging. Nearly two-thirds (65%) of respondents are increasing their budgets for acquisition of new downstream processing technologies in 2010. This shows that adoption of new purification technologies is a distinct trend. Table 1 includes some of the technologies from our study that biopharmaceutical companies are currently examining.

Table 1. Downstream technologies that iopharmaceutical companies are currently examining 

 Even as end-users are investigating broad technologies, specific alternatives to Protein A and traditional purification are becoming commercialized. Some of these are listed below.  

: Novozymes's new patented Dual Affinity Polypeptide technology platform replaces Protein A process steps with similar, but disposable, technology

 enable complexation and manipulation of proteins and allow for control of polymer and protein complex solubility, which results in the direct capture of the product without centrifuges or Protein A media, from Millipore Corp

 to replace traditional Protein A and ion exchange, for improved selectivity and capacity with shorter residence times. These media, with novel chemistries, include hydrophobic charge induction chromatography, such as MEP, and Q and S HyperCel from Pall Corp

, involving chromatography medium as a single-piece homogeneous column,  such as Convective Interaction Media monolithic columns from BIA Separations

, involving multicolumn countercurrent chromatography, such as BioSMB from Tarpon Biosystems 

Single domain camel-derived (camelid) antibodies

, including synthetic dyes, such as Mabsorbent A1P and A2P from Prometic Biosciences 

 chromatography systems, such as the Rhobust platform from Upfront Chromatography  

Ultra-durable zirconia oxide-bound affinity ligand

 chromatography media from ZirChrom Separations 

 (ADvanced SEParation Technology) from Nysa Membrane Technologies 

 for affinity chromatography from Prometic Biosciences, Dyax, and others 

 based on expression of proteins or MAbs as fusion proteins with removable portion (tag) having affinity for chromatography media, such as His(tidine) tags licensed by Roche (Genentech)  

 in development, including reverse micelles (liposomes), liquid–liquid extraction systems, crystallization, immobilized metal affinity chromatography, and novel membrane chromatography systems

 with disposable components (e.g., ReadyToProcess), process development ÄKTA avant with design of experiments capability, and multicolumn continuous capture, from GE Healthcare.

Those not paying attention to what's happening are likely to miss out on critical opportunities for both near- and long-term process improvements. New purification technologies are being actively pursued by both vendors and end-users. Suppliers, such as Pall Corporation's Global Technical Director Jon Petrone believes, "Downstream purification has the potential to become a critical bottleneck in large-scale monoclonal antibody production as titers continue to increase." 

Eric Grund, senior director of Biopharma Applications at GE Healthcare, agrees, "Resolving [downstream purification challenges] with new, cost-effective technologies that will meet safety expectations is a priority ... flexibility is the most desired feature of any downstream processing chain. A manufacturer may have to handle increased demand one day and alternative products the next." 

From the end-user's perspective, bioprocessing improvements are becoming a major focus. In fact, last year, over two-thirds of biomanufacturers (67%) reported either "some" or "significant" improvements from changes to their downstream operations.

This will continue as the industry deals with downstream processing challenges.   

Disposable equipment may deliver the greatest shift in how biomanufacturing is done in the future. Today, a majority of manufacturers are reporting the use of at least some single-use equipment in commercial-scale production. So, when fully disposable downstream processes are introduced, there may be relatively rapid adoption and the potential for substantial growth. They may open the way to completely modular, mobile biopharmaceutical operations. The cost, time, and quality improvements derived from single-use components may then extend to separation and chromatography steps. In fact, most large biomanufacturers are now seriously considering integrated disposable alternatives. According to Robert Blanck, bioprocess strategic marketing manager at Millipore Corp., "We are working on new integrated disposable process solutions [that incorporate] bioreactor, chromatography, TFF, virus filtration, sterile filtration, buffer/media storage, and intermediate handling." 

More biopharmaceutical products are moving through the pipeline and cost pressures are continuing to mount.

  These competitive pressures are pushing new downstream technologies toward commercial and, ultimately, regulatory acceptance. The next column will cover regulatory aspects and the receptivity of regulators toward adoption of new downstream processing technologies. 

 is president and managing partner at BioPlan Associates, Inc., Rockville, MD. He is also a member of 

 editorial advisory board and the editor of 

Advances in Biopharmaceutical Technology in India

1.  7th Annual Report and Survey of Biopharmaceutical Manufacturing. 2010 preliminary data. BioPlan Associates, Inc; Rockville, MD. Available from: 

2.  6th Annual Report and Survey of Biopharmaceutical Manufacturing, April 2009 online edition. BioPlan Associates, Inc; Rockville, MD. Available from: 

3. Rader RA. Biopharma:Biopharmaceutical Products in the US and European Markets. BioPlan Associates; Rockville, MD. Available from: 

http://www.bioplanassociates.com/publications/pub_bpuseu.htm

Downstream Trends

The new technologies being developed to improve downstream systems go beyond traditional chromatography.

Downstream Processing: Promising Technologies are on the Horizon

 (CAPA) is traditionally associated with good manufacturing practices (GMP) and ISO, and some would argue it has no relevance in its good laboratory practices (GLP) counterpart. Regardless of the working environment, however, the ability to monitor and establish control over processes is an essential element of any quality program. A structured approach to identifying and addressing nonconformance can provide performance data necessary to successfully integrate improvements into the system. Although managing deviations is a requirement, CAPA is a quality system that makes good business sense for any organization.  

Three types of events will typically result in the need for a CAPA solution plan: an anomalous result, an external finding, or a deviation from a written procedure. The anomalous result, which is known as an out-of-specification or out-of-trend result, falls outside of normal method behavior or manufacturing specifications. Anomalous results can stem from poor system suitability, equipment maintenance, or the improper preparation of samples or standards, or may be indicative of an unknown matrix effect. A thorough investigation will usually pinpoint an assignable cause or reason for the inconsistent result. There are instances where the assignable cause may not be discovered, however, and it is in these circumstances where a follow up CAPA program can prove useful.  

The external finding is generated as a result of an audit or complaint. The solution to these findings can fall into two categories. Short-term corrective actions are immediately apparent, such as a documentation error or safety violation. Long-term corrective actions may require extensive effort or cost, or may be multi-layered. Without the periodic review built into an established CAPA program, these long-term actions may fall between the cracks and never come to fruition. 

Finally, a deviation is generally the result of human error, but is nonetheless crucial for identifying weaknesses. Corrective action may or may not be appropriate in the case of a deviation, but the preventive actions can help limit the recurrences seen over an extended period of time and may even result in stronger support mechanisms such as training. 

The characteristics of these events do not necessarily lend themselves to an easy investigation or root cause determination. In some instances, such as an anomalous result, an investigation is straightforward and determines if the result is true or the by-product of a failure in some part of the testing system. Depending on the nature of the external finding, an investigation and root cause determination may not be needed in the traditional sense, but rather used to rule out causal factors.  

Having an established CAPA program can help track the follow-up actions needed to close out an observation with a customer or regulatory agency and effectively demonstrate control over the quality of the systems. Also important is trending to identify repeat occurrences, which can be handled by a CAPA solution plan. The trending can point to systemic issues, such as procedural clarity, and exhibit a proactive approach toward risk management and continuous improvement.  

There are four main elements of a CAPA program that will demonstrate control over the procedures and processes that make up the working environment: documentation, investigation, CAPA, and measurement. These elements often are in place informally, but without adequate follow-through they will be ineffective in demonstrating the systemic control desired.  

An appropriate level of documentation must take place immediately following discovery or occurrence of the event. Quality and management will need to characterize the type of events anticipated and determine a suitable course of action. This also may be the point in the process where customers, sponsors, or study directors are notified of the event. Notification will depend largely on contractual obligations or protocol directions or the discretion of management. 

This documentation will help recreate any variables that may affect the outcome of the investigation. Documentation also enables personnel down the line in the investigation or measurement phases to accurately gauge the risk associated with the event or effectiveness of the implemented actions. With risk assessment, management can determine the level of resources to be allotted for the investigation and CAPAs. 

The investigation phase is the most fluid of the CAPA process, and the amount of work effort should be commensurate with the risk associated with the event. The primary focus of the investigation should be a determination of a root cause, and there should be concrete evidence of active searching. Documentation during the investigation phase should demonstrate the development and testing of theories, but procedures should be in place to limit or control the amount of secondary testing and outline decision-making guidelines. The appearance of testing-into-compliance must be avoided.  

The investigation, while determining the root cause, should also look for deficiencies in records, audits, and reports. These may be indicative of a broader problem that continually contributes to an event. For instance, a routine freezer alarm may be attributed to a door being left open too long. However, the trending data provided by a structured CAPA program may indicate other issues are at play. An investigation should review that the maintenance records are up to date and completed according to pre-set standards. If a routine maintenance item has been overlooked, there may be larger issues at stake than just the door being left open. The investigation may need to ascertain if the preventive maintenance schedule is adequate, if poor documentation skills are at fault, or if the vendor is not providing appropriate support and service.  

After the investigation has identified a root cause for the event, the investigators and management should focus on identifying the appropriate corrective actions needed to resolve the immediate issue and preventive actions aimed at reducing or eliminating recurrence. CAPAs should be assigned a responsible owner and given a definite timeline for completion.  

CAPAs may be fairly straightforward, but in some instances, determining an appropriate action may be difficult. An anomalous result is either shown to be true or replaced with data that are proven accurate. In the case of an external finding, a written procedure may not contain all the elements needed, and the root cause points to a subject matter expert being left out of the collaboration steps. This item is corrected by revising the document. Depending on how the document management system is controlled, ensuring all appropriate collaborators take part in the revision is more easily said than done. In the end, preventive actions may simply be a system of checks and balances aimed at eliminating as many of the variables as possible.  

Of the four elements of a CAPA system, measurement or trending may be the most important. To combat the ever-changing kaleidoscope of personnel, documents, instruments, and equipment, maintaining a CAPA system will permit a consistent and unbiased look at how an organization is managing the procedures and processes that make up its operations. Periodic review of open and closed CAPAs may reveal previously unknown contributing causes to the occurrence of events.  

Trending events according to factors such as personnel, department, instrument, or type of event can assist in better allocation of resources for training, maintenance, or continuous improvement.  

By keeping the CAPA system up-to-date with the events, responsible personnel, and target dates for completion, an organization can build in an accountability strategy that keeps customers satisfied that their concerns or problems are being addressed. An effective CAPA system can demonstrate control, mitigate risk, and reduce costs, which are strong indicators of an organization's focus and commitment to quality. 

 is the vice president of quality at BASi, West Lafayette, IN, 765.497.5877, 

Regulatory Beat

An effective CAPA plan provides a mechanism for responding to the unexpected.

Corrective and Preventative Action Programs: A Mechanism of Control

Design of experiments (DOE) is a valuable tool for identifying aspects of a formulation that are critical to product quality. The formulation design space can be characterized by performing excipient robustness studies that use DOE. This paper presents considerations for performing robustness studies as well as two case studies in which DOE was used to determine the robustness of protein formulations to changes in protein, excipient, and pH levels. The results from the DOE studies identified formulation components that must be tightly controlled and showed that variations had a minimal impact to product in formulation component levels within the formulation design space.

The US Food and Drug Administration's Quality by Design (QbD) initiative encourages pharmaceutical manufacturers to use modern tools that facilitate the implementation of robust manufacturing processes and reliably produce pharmaceuticals of high quality.

  Filing a new drug application (NDA) or biologics license application (BLA) under the QbD initiative may reduce the extent of regulatory oversight and may result in faster review times. Implementing a QbD approach in the development and characterization of manufacturing processes and products provides several advantages. These include a more thorough understanding of the manufacturing process and the product, as well as the potential for increased process and product robustness and process efficiency. The International Conference on Harmonization (ICH) Q8

  guidelines describe principles, tools, and examples for implementing QbD. One of these tools is the use of formal experimental designs or design of experiments (DOE) to characterize and establish a functional design space.  

DOE is a tool that can be used during formulation development to screen for stabilizing excipients, determine excipient levels that provide optimal stability with adequate robustness, and characterize the formulation design space. The design space is defined in ICH Q8 as, "the multidimensional combination and interaction of input variables (e.g., material attributes) and process parameters that have been demonstrated to provide assurance of quality." The formulation design space would thus define limits for the active pharmaceutical ingredient (API), excipients, pH ranges, and other critical characteristics in the formulation that maintain product stability. Because multiple formulation components are screened simultaneously, the combinations that provide optimum stability and interactions among formulation components can be identified. For example, in protein formulations that contain sodium chloride (NaCl), an interaction between pH and NaCl concentration is likely to be observed because both modulate electrostatic interactions. A DOE formulation screening study can thus help to identify optimum levels of pH and NaCl for stability.

  Similarly, in lyophilized or spray-dried protein formulations, an interaction may be observed between protein and cryo/lyoprotectant levels because an optimum ratio of the stabilizer to protein is required for cold and dehydration-induced denaturation.

  DOE also can be used to identify effective preservatives for multi-dose protein formulations at optimal concentrations for antimicrobial efficacy and protein stability, to characterize the effect of stress conditions and degradation pathway mechanisms in forced degradation studies, and to characterize the effect of formulation components on drug delivery systems.

The robustness of the formulated product can be characterized further in excipient robustness studies that use DOE.

  Excipient robustness studies performed using DOE can:  

identify critical formulation components; these are formulation components whose levels must be tightly controlled to maintain product stability or performance

provide limits in which variations in the levels of formulation components have minimal or no effect on product stability or performance

determine the effect on product stability of variations outside normal operating and proven acceptable ranges

identify and characterize the interactions among formulation components

confirm that the product is not formulated near a design space cliff or discontinuity.

Excipient robustness studies can, hence, be used to evaluate and characterize the formulation design space (Figure 1).  

CONSIDERATIONS FOR PERFORMING ROBUSTNESS STUDIES

When designing an excipient robustness study, the following factors should be considered to appropriately select the formulation ranges, analytical methods, and experimental design used in the study: 

 The extent of robustness studies required is dependent on protein availability and resource commitment. Thorough robustness evaluations typically are performed in late-stage development, as the commercial formulation and configuration are being locked.  

 Protein, excipient, and pH levels in historical lots can help give guidance for selecting appropriate ranges for the study. This is especially important for biotechnology products because purification processes such as the ultrafiltration–diafiltration (UF–DF) step typically used to formulate the product may result in pH and excipient levels different from the formulation buffer.

  The number of lots and manufacturing campaigns used to assess the manufacturing history also should be considered. If there is limited manufacturing experience before starting a robustness study, the ranges of the formulation components used in the study can be set relatively wide to cover potential future ranges. Ideally, the excipient robustness study is performed early enough in product development so that changes can be made to the target level and acceptable formulation ranges if warranted.  

 Development, characterization, and historical manufacturing data typically are used to set target levels and normal ranges in manufacturing batch records and a product specification before performing a robustness study. The formulation ranges selected for the study must go beyond the acceptance criteria defined in batch records and product specifications. Selecting wider ranges helps to confirm that variations within current normal operating ranges do not statistically or practically affect product stability. By evaluating wider than normal operating ranges, one also can define the acceptable range that does not effect the product (design space). The ranges selected for the study are limited by levels that may result in significant degradation (see below) or affect patient safety. Previously established levels of generally regarded as safe (GRAS) excipients can be found in the FDA inactive ingredients database and used as a guide. Results from the robustness study can then be used to justify the batch record ranges and product specification. 

Results from development and characterization studies:

 Development experience can be used to ensure that ranges selected are not so wide that high levels of degradation are observed making interpretation of the data difficult. Data from previous studies that provide information on product impact from variations in formulation ranges (i.e., results from formulation screening studies) can be assessed and used to select appropriate ranges for the excipient robustness study.  

Material availability to perform the study: 

Because parameters are evaluated simultaneously in a DOE study, the material requirements can become very large. The study design must be evaluated against the material availability and modified appropriately (if possible). Options to reduce material needs include the use of scale-down models of the bulk drug substance (BDS) and final drug product (FDP) container-closure configuration, reducing the testing frequency on long-term storage, and using accelerated stability data to establish robustness at earlier time-points. Screening designs also can be used (see below).  

Examples of designs include screening, full factorial, fractional factorial, and response-surface designs. Screening designs are used to screen the effect of factors on different responses and are amenable to experiments with a large number of factors. A full factorial design allows the identification of the formulation components that have a significant effect on stability and all the interactions among the formulation components. However, depending on the number of formulation components, a fractional factorial design that also allows for the identification of significant factors, but not all the interactions, may be more appropriate. To identify curvature (for example, an optimal range for stability), a response surface design is required. Examples of response surface designs include central composite design (CCD) and Box-Behnken design. Central composite designs can be used when evaluating at least two factors, whereas Box-Behnken designs can be used only for three or more factors.  

Central composite designs contain points in a factorial design (cube points) with additional points on the axes that allow curvature to be estimated (Figure 1). Box-Behken designs, on the other hand, contain points on the center of the edges of the cube and can allow for fewer design runs while still being able to analyze curvature in the responses. The main benefit of a Box-Behken design is that none of the factorial design points get run. This means combinations of extremes, for instance the high-high-high or low-low-low combinations in a 3-factor design, do not get run. Table 1 gives examples of the number of runs required for full-factorial and fractional factorial screening, central composite design, and Box-Behnken designs as a function of the number of factors being evaluated.  

Table 1. Number of runs1 as a function of the number of factors (formulation components) evaluated for each type of experimental design 

It is typical to use a screening design when there are a large number of factors that must be reduced to a manageable few. Sometimes follow-up screening designs are needed to separate confounded (confused) interaction terms from one another. After the important few factors are determined, a response surface design is used to get a complete understanding of the response and how it is correlated to the factors. Because of the use of DOEs, where the changes in the responses are directly correlated with the changes in the factors, the analysis of response surface designs provides a mathematical model that can be used in manufacturing as a control scheme. 

In any design, it is important to run some replicate points—points that are run multiple times—to be able to asses the random error in the response models. It is typical, but not necessary, to make these replicates the center-point condition and to run somewhere between 3 and 6 center-point runs. The other benefit of using centerpoints for the error analysis is that these runs can be used to determine process stability through the use of a statistical process control (SPC) analysis. 

 Analytical methods used must be sensitive and appropriate for detecting changes in the stability of the product within the experimental design space. In addition to the standard methods used to release the product, characterization methods provide a more thorough evaluation of the formulation design space. Similarly, replacing qualitative methods (such as visual inspection) with quantitative (such as turbidimetry and the 

 tri-stimulus method for color analysis) also help to provide a more thorough understanding of the design space. Analytical method attributes such as repeatability, intermediate precision, the limit of detection (LOD), and limit of quantitation (LOQ) determined during method qualifications must be considered when interpreting results obtained from statistical analysis of the experimental design (see below). 

 Results obtained from statistical analysis of the experimental data are based on the input parameters. Accurate interpretation of the data may require consultations with statistical experts. In addition, the formulator's knowledge of degradation pathways and analytical method capabilities is needed to properly interpret the data. For example, methods with high data precision may result in identifying many statistically significant factors while the practical significance of the results observed requires the formulator's knowledge of quality attributes and what constitutes an acceptable change.  

Two case studies are presented in which a DOE approach was used to determine the robustness of protein formulations to changes in protein, excipient, and pH levels. In case study 1, the results indicated that the formulation was robust to wide variations in excipient, protein, and pH levels; much wider than could occur during manufacturing of the product. In case study 2, the results indicated that the formulation was robust to wide variations in excipient and proteins levels, but not pH. Thus, in case study 1, the results were used to support the conclusion that variations in excipient levels had a minimal impact to product whereas in case study 2, results indicated that the pH of the formulation needed to be tightly controlled.  

In case study 1, the robustness of a high protein concentration lyophilized product to protein, excipient, and pH ranges was evaluated. The excipients consisted of a buffering agent, lyo/cryoprotectant, and surfactant. During manufacturing, excipient levels are weighed within 1.5% of target, but some vary wider in the product because of the retention of excipients during the UF–DF process. Excipient levels evaluated in the study were well beyond excipient concentrations expected so that a broad design space could be evaluated. Ranges were ±25% of target concentration for the cryo/lyo-protectant, ±50% of target concentration for the surfactant, and –50% to +100% of target concentration for the buffering agent. The buffering agent was evaluated up to +100% to establish design space at higher buffer concentrations. To accommodate the nonlinear nature of the buffering range, the factor levels were log-transformed, arising in a buffering range of ±0.301 log units of target. It is important to keep the design dimensions equidistant around the center point of interest because this allows for an analysis in which each of the design points gives equal weight to the responses.  

Table 2. Screening design for case study 1 

Although a full-factorial, response-surface design would have provided information on curvature in the response and all possible interactions, this would have required the preparation of 42 different formulations excluding the center points. To reduce the number of formulations and still be able to determine formulation components and some 2-factor interactions that significantly affected stability, a fractional factorial screening study was used (Table 2). Samples were monitored at intended and accelerated storage conditions by size-exclusion and ion-exchange chromatography, as well as SDS-PAGE, and tested for moisture and potency. Degradation observed was limited to aggregation. Statistical analysis of the stability data using JMP (Cary, NC) showed that protein and cryo/lyo-protectant concentrations were the only formulation components that significantly affected stability. The prediction profile for the impact on stability as a function of formulation components is shown in Figure 2A. Increasing protein concentrations and decreasing cryo/lyoprotectant concentrations negatively affected stability. In addition, a protein:cryo/lyo-protectant interaction was observed such that the impact of the cryo/lyo-protectant on stability was more evident at the higher protein level. Similarly, the impact of protein concentration on stability was more evident at lower cryo/lyo-protectant concentrations (Figure 2B). The robustness of the formulation was demonstrated by the limited degradation observed at 5 °C, the intended storage temperature for the product, even in the least stable formulations containing the highest protein:cryo/lyoprotectant ratio.  

In case study 2, the robustness of a high concentration liquid product to protein, excipient, and pH concentrations was evaluated. The excipients consisted of a buffering agent, tonicifying agent, cryoprotectant, and surfactant. Excipient ranges evaluated in the study were within 20% of cryoprotectant and tonicifying agent target concentrations and 50% of buffering agent and surfactant target concentrations. Because of the number of formulation components, a fractional–factorial screening design was also used in this study. Samples were monitored at intended and accelerated storage conditions by size-exclusion, ion exchange, and reverse-phase chromatography, as well as by potency assay. Degradation was observed by size-exclusion and ion exchange chromatography. The only factor that had a significant effect on stability was pH, resulting in increased aggregation and deamidation (data not shown). The results from the excipient robustness study prompted well-defined pH acceptance criteria in buffer preparation records and on the product specification.  

The two case studies illustrate two outcomes that can be obtained from an excipient robustness study:  

the product is robust to wide variations in formulation components

the product is not robust to wide variations in one or more of the formulation components and limits are put in place to control.

Irrespective of the outcomes, controls for protein, excipient, and pH levels must be established in the batch records or product specifications. Controls in the batch record may include acceptance criteria for buffer and excipient level weigh-outs for the formulation buffer, the pH of the formulation buffer, as well as pH and protein concentrations of the formulated BDS and FDP. Additionally, controls in the BDS and FDP specifications may include acceptance criteria for pH, protein concentration, and osmolality. The acceptance criteria are selected such that the quality of the drug product is not affected beyond an acceptable level. If the robustness study indicates that the formulation is not robust to wide variations in one or more of the formulation components, controls are put in place to ensure that acceptable levels are achieved consistently. 

Quality by Design tools such as design of experiments (DOE) help to provide a more thorough understanding of a product's design space. Excipient robustness studies using DOE are, thus, used to evaluate and characterize the formulation design space. The formulation design space is identified by the ranges established during the excipient robustness study to provide an assurance of quality in the product. Controls included in manufacturing batch records and product specifications ensure that the product is maintained within the formulation design space so that the quality of the product and safety of the patient are ensured. 

 was a senior scientist in the department of drug product sciences, biopharmaceutical development, Human Genome Sciences, Rockville, MD. She is currently an assistant professor in the department of pharmaceutical sciences at the Feik School of Pharmacy, University of the Incarnate Word, San Antonio, TX, 210.883.1099, 

 is an associate director of process statistics in the department of biostatistics, 

 is a bioprocess associate in the department of drug product sciences, and 

, is the director of the department of drug product sciences, all in biopharmaceutical development at Human Genome Sciences, Rockville, MD, 

1. US Food and Drug Administration. Guidance for industry. Pharmaceutical cGMPs for the 21st century—A risk-based approach final report. Rockville, MD; 2004 Sept. 

2. International Conference on Harmonization (ICH). Q8(R1), Pharmaceutical Development. Geneva, Switzerland;  2008 Nov. 

Features

Design of experiments is a valuable tool for identifying aspects of a formulation that are critical to product quality.

Characterizing the Formulation Design Space

Public and private healthcare experts have been struggling for years to establish electronic health information systems able to track and transfer a broad range of data in patient medical records. The inability of the nation's fragmented health IT (HIT) systems to communicate with one another has made the task extremely difficult, as do concerns about patient privacy and protecting access to personal health information (PHI).  

The US Food and Drug Administration hopes that increased connectivity among healthcare entities will support more efficient drug testing and development, along with more timely medical product monitoring and oversight. To take advantage of these developments, the FDA is working to update its internal IT operations to improve its capacity for reviewing applications for new drugs and medical products, for receiving and archiving clinical trial data and regulatory submissions, and for tracking manufacturing facilities and product supply chains.  

A main goal is to expand oversight of the safety of drugs and medical products on the market. To this end, the FDA is centralizing adverse event analysis through an all-FDA adverse event (AE) reporting system and is creating a MedWatch Plus single portal for public reporting of AE information. Work continues on a final rule requiring electronic filing of AE reports for drugs, biologics, vaccines, and medical products, a mandate that smaller drug and biotech manufacturers fear will be costly and challenging.  

Probably the most high-profile project involves establishing a proactive information system that can detect signals of adverse events for regulated products. The aim, as specified in the FDA Amendments Act of 2007 (FDAAA), is to augment the agency's passive AE reporting system with a more active program able to monitor health records on 100 million people by July 2012.  

To meet this goal, FDA launched the Sentinel Initiative in 2008 and is now establishing a mini-Sentinel system that will tap into medical records held by large health plans and insurers. FDA will pose questions triggered by risks seen in clinical trials or by early AE reports to databases established by CIGNA, Kaiser Permanente, and the HMO Research Network, among others. A second phase next year will broaden access to include data from Medicare and other government health programs.  

To coordinate operations, FDA recently signed a $72 million contract with the Harvard Pilgrim Health Care system to implement a distributed data model that can obtain near real-time signals and ensure data quality from appropriate sources. The system permits FDA to ask Sentinel partners to monitor for certain events and to assess evidence of health conditions associated with drug use. The program already can access information on 60 million patients, according to Project Director Richard Platt of Harvard Pilgrim and Harvard Medical School. That's well above the 25 million patients that FDAAA instructs FDA to monitor by July 1 of this year. Mini-Sentinel also will work with researchers and technical experts at academic centers, private firms, and non-profit organizations to examine methods for querying against a common data model and to establish policies and standards for validating and analyzing information from diverse information sources.  

Platt and others discussed the technical, legal, and administrative issues involved in building the Sentinel system at a January workshop organized by Mark McClellan, former FDA commissioner and now director of the Engelberg Center for Health Care Reform at the Brookings Institution. FDA Commissioner Margaret Hamburg opened the conference by emphasizing the importance of post-marketing surveillance of regulated products. To have a fully functioning Sentinel system, she noted, we need to examine how to design a common data model that can compare and analyze data sets, and to reach consensus on methodologies for proving and disproving causal relationships between a product and an outcome.  

Janet Woodcock, director of the Center for Drug Evaluation and Research, described Sentinel as one element in a broader FDA effort to encourage the safe use of medications, to revamp the agency's pharmacovigilance system and to explore the use of social media to publicize safety problems. Sentinel is "very much a work in progress," Woodcock commented, noting that it will be very different in five years as the science and technology mature. 

The FDA's decision to launch Sentinel based on a distributed data model reflects earlier research by academic experts and by the Observational Medical Outcomes Partnership (OMOP), an industry-funded collaboration involving the FDA, the Foundation for the National Institutes of Health and the Pharmaceutical Research and Manufacturers of America. Through this partnership, manufacturers are working to define viable approaches for assessing drug safety and for communicating those findings to health professionals and patients.  

OMOP's agenda reflects strong industry interest in shaping and supporting Sentinel policies and operations. Unfortunately, this coalition is the main way for manufacturers to influence the project at this time because there are no industry representatives on the Sentinel planning board and OMOP is not an official participant in the program, largely because some stakeholders believe that manufacturer involvement could taint the validity of results. A main concern of the industry is that companies will be denied access to Sentinel data for their own analysis or for postmarketing studies. Woodcock noted that the mini-Sentinel system cannot yet support third-party postmarketing analyses, and that the FDA will have to deal with industry access after the full "industrial-strength" Sentinel emerges.  

Ensuring the privacy and security of patient health records is another key issue shaping the Sentinel program. The main advantage of the distributed data model is that the FDA avoids building its own mega-database and instead leaves individual patient health information with the insurance company or health system that holds the records. That data source evaluates the information, transmits summaries to Sentinel, and confirms a specific diagnosis or report if needed. It remains to be seen how well the FDA can assess safety signals through this arrangement; even direct access to de-identified data may not be sufficient to confirm that a safety issue is real.  

Another tricky issue for industry and policy makers is the timing of public disclosure of safety information. Releasing information too early increases the possibility that a report may be wrong or incomplete and thus raise unnecessary alarm. But delaying communication on an emerging safety problem may result in patient harm and expose program participants to "failure to warn" liability charges. Moreover, the FDA has to determine how it will use Sentinel findings in regulatory decisions. Confirmation of safety signals could result in changes in a product's labeling, agency alerts to healthcare professionals, and public warnings about appropriate drug use. Despite concerns about the completeness, objectivity, and timing of drug safety reports, "what we're going to get is going to be better that what we have right now," Woodcock predicted.  

Although Sentinel's prime purpose is to serve the FDA's regulatory mission, the long-term vision is that the program will become part of a larger health information system that also provides data for outcomes studies, comparative effectiveness research (CER), and health system quality reporting. Manufacturers support the goal of building such a multipurpose network, said Paul Stang of Johnson & Johnson at the workshop, but this requires more investment in research methods, in standards for data sources and evidence, and in governance of emerging models.  

Carolyn Clancy, director of the Agency for Healthcare Research and Quality (AHRQ), concluded the program by describing AHRQ initiatives to build distributed data research networks and to improve patient registries that can answer queries related to the effectiveness and safety of medical services and products. An over-arching goal is to identify synergies between postmarketing surveillance and CER and to provide incentives for healthcare providers to participate in e-health activities. 

Washington editor, Chevy Chase, MD, 301.656.4634, 

The new Sentinel system aims to expand access to data on medical product safety and patient effects.

FDA Seeks More Timely Drug Information Electronically

It is essential to develop sufficient process history before transferring any process to a contract manufacturing organization. This article presents case studies illustrating two key components of technology transfer: demonstration and documentation of process reliability at two representative scales before technology transfer and the establishment of clear and rigorous process transfer criteria based on process history with which to gauge the efficacy of the transfer.

Millennium: The Takeda Oncology Company has outsourced the manufacturing of several biopharmaceuticals at every stage of product development. A critical element of the success of those projects was developing sufficient process history before transferring the process to the contract manufacturing organization (CMO). This article presents actual case studies illustrating the following key components of technology transfer:  

demonstrating and documenting  process reliability at two representative scales before transfer to the CMO 

establishing clear and rigorous process transfer criteria based on process history with which to gauge the efficacy of the transfer.

THE IMPORTANCE OF SUFFICIENT PROCESS HISTORY BEFORE TRANSFER

Process history plays a critical role in the development and implementation of a manufacturing process at the CMO. If the client organization does not take the time and effort upfront to develop a robust manufacturing process, it is doubtful that a productive and robust process will evolve in the production suite of a CMO. If the client has insufficient process history at both bench- and pilot-scales, one cannot expect that process to operate in a sufficiently reliable manner at large scales.  

Sufficient process history also is key to the rapid and efficient transfer of a client process to a CMO. Without a basis for comparison, the client and the CMO cannot determine if the process has been successfully transferred. For example, if the yield at the CMO is 25% lower than expected, are variant equipment design parameters or operational conditions in the CMO production suite at issue, or does the smaller yield simply reflect the normal variance of the process regardless of where it is manufactured? Without a sufficient process history, there is no way to know.  

Finally, even after the process is operating in the production suite of the CMO, client process history can be invaluable if problems arise. Process history can provide impartial evidence when deviations occur or when the CMO suggests minor changes to the client process to achieve some benefit for itself (e.g., improved convenience, reduced labor, reduced paperwork, optimized suite scheduling).  

Developing a robust process and establishing clear and rigorous transfer criteria is highly beneficial for technology transfers. The first prerequisite for establishing transfer criteria is a documented process history.  

A CMO will not agree to meet pre-set transfer criteria unless it has documented evidence that the client has met these criteria in the client's facility several times. Bench-scale demonstration of process reliability is necessary, but not sufficient. If process performance problems arise at the CMO and the only process history from the client was generated in the laboratory, one can be sure that the process variance will be attributed to an elusive "scale issue." Augmenting bench-scale data with pilot-scale data will demonstrate that the process can be scaled up and documents a rational basis for further scale-up. 

Process history should be established using representative bench-scale and pilot-scale systems. As often as possible, these systems should be scaled-down versions of clinical and commercial scale processes. For example, equivalent cell ages (i.e., population doublings from thaw) should be used to inoculate both bench-top and pilot production-phase bioreactors and large-scale production-phase bioreactors. Additionally, the seed trains used to inoculate the production phase bioreactor should be equivalent to those used at clinical scale. Bench-top and pilot production-phase bioreactors should be inoculated from seed bioreactors rather than shake flasks. Clinical-grade raw materials, filters, and resins should be used whenever possible to maintain the same or equivalent materials during transfer to the CMO. Bench-scale and pilot-scale chromatography steps should be taken through entire cleaning, storage, and regeneration cycles, and evaluated with new and at least somewhat used (>10 cycles) resin. 

Although the focus during process development often is centered on bioreactor titer and purification yield, it is vital that the process history also documents product quality characteristics.  

After sharing client process history with the CMO, discussions to establish mutually agreeable transfer criteria can begin. Examples of cell culture process transfer criteria jointly agreed to by Millennium and a CMO are shown in Tables 1 and 2.  

Table 1. Process transfer criteria for transferring Millennium (MPI) bench-top cell culture bioreactor process to a CMO 

These tables demonstrate a few key features. First, the transfer criteria should be a direct comparison: compare bench-top data with bench-top data and pilot-scale data with pilot-scale data. If undesirable results are attained, a comparison of CMO pilot data to client bench-top data alone or to client pilot data alone cannot distinguish between generic transfer issues (e.g., a misunderstanding of the process by the CMO) or a scale-up issue. Thus, it is prudent to first evaluate the efficacy of the transfer with a laboratory-scale to laboratory-scale comparison as illustrated in Table 1. There typically is much more client laboratory-scale data than pilot-scale data available to enable statistically valid comparisons. Only when the efficacy of this laboratory-scale transfer is confirmed should a pilot-scale to pilot-scale comparison be completed (Table 2), although these activities can overlap to save time.  

Table 2. Process transfer criteria for transfer of pilot-scale cell culture bioreactor process to CMO 

Figures 1 and 2 present actual data generated by the transfer activities represented in Tables 1 and 2, and illustrate the wisdom of this approach. Figure 1 demonstrates similar titer performance between the CMO's 2-L bench-scale production-phase bioreactors and Millennium 5-L bench-scale production-phase bioreactors. However, Figure 2 shows that the CMO's 300-L pilot-scale bioreactor generated approximately 20% lower titers than the Millennium 100-L pilot-scale bioreactor. In light of the close agreement between bench-scale systems in Figure 1, the CMO quickly agreed that there was an implementation problem with the 300-L process that required investigation.  

This evaluation procedure quickly identified a serious issue well before current good manufacturing practices (cGMP) manufacturing was scheduled to begin. Moreover, this procedure pointed to the most fruitful area for investigation. A careful comparison between the operation of the CMO's 300-L bioreactor and the Millennium 100-L bioreactor and both sites' bench-scale bioreactors identified three operating variables that were unique to the 300-L bioreactor: the age of the bioreactor feed; the percentage carryover of medium from the inoculum bioreactor; and bioreactor pH. Regarding the pH, the set points were identical for all systems. Unfortunately, the actual pH of the 300-L bioreactor was approximately 0.1 pH units lower than all the other systems, because of differences in control algorithms and the reduced frequency of re-calibration of the pH probe in the 300-L suite.   

Based on this investigation, a factorial-designed experiment with three variables as inputs was executed in the Millennium 5-L bioreactors (Table 3). The data clearly demonstrated that only the pH had a significant impact on the titer. Consequently, the CMO changed its bioreactor pH control and recalibration procedures for the large-scale GMP runs, which were successfully implemented without an engineering run.  

Table 3. Bench-scale bioreactor experiment to troubleshoot a lower- than-expected titer from a CMO pilot-scale bioreactor 

This example highlights another benefit of establishing a process history and transfer criteria before transferring a process to a CMO. Most CMOs have established their own tightly controlled procedures over many years. These procedures have been proven to meet practical, regulatory, and business needs, making CMOs reluctant to change standard practices. However, when scientifically sound data suggest that deviation from standard practices is warranted, most CMOs will be quite willing to cooperate. 

Another essential feature of process transfer criteria illustrated in Tables 1 and 2 is the comparison of key product quality attributes. The acceptance criteria for product quality presented in this example were intentionally vague. Unless there is significant process history approaching the level attained nearing a formal process validation or a biologics license application filing, there is usually insufficient process knowledge either to establish definitive product quality acceptance criteria or to guide process troubleshooting efforts. 

Therefore, it is best if the CMO and client assess the quality of material produced at the CMO in a collegial and collaborative manner. If there is a significant variance from expectations, there are several possible responses: 1) delayed progression into GMP production while troubleshooting efforts are undertaken to determine the cause of the variance; 2) delayed progression into GMP production to generate more pilot runs or engineering runs at scale that can define the variance, so that new specifications can be established to release CMO-produced lots; or 3) live with the variance and proceed as planned, which is probably acceptable only for early-stage projects. 

Figure 3 presents one such example evaluation, where Millennium and a CMO statistically compared the peaks from an oligosaccharide analysis of product from the pilot plants at both organizations. The analysis of both samples should be analyzed by the same assay from the same laboratory, especially if the assays have not yet been qualified or validated, as is often the case during process transfer.  

Process transfer criteria also should be established for all downstream purification steps. Table 4 presents an example illustrating the benefits. This table represents the process transfer of a polishing chromatography step to a CMO (a different CMO from the one used in all the previous examples).  

Table 4. Transfer of early-development process to a CMO. Data represents the purification yield and percentage of high molecular weight (HMW) species in the load and eluate of a polishing chromatography step for lots from the Millennium (MPI) pilot facility, the CMO pilot, and the full-scale manufacturing suite at the CMO. 

In this case, because of time constraints and the early nature of the project, a full-scale engineering run was deemed prudent because of the limited process history generated at that point. Millennium and the CMO decided to generate more process history as part of the transfer by executing pilot lots in parallel at both sites. Data from these seven pilot lots are presented in the first seven columns of Table 4. The percentage of high molecular weight species (% HMW) in both the load to and eluate from this step was similar at both sites and the two organizations agreed that this step was transferred successfully.  

However, after executing the first cycle of the full-scale engineering run, it was clear that the HMW percentage in both the load and eluate were significantly higher than in the transferred process. Because the process was transferred successfully, it was neither a process issue nor a transfer issue. Instead, focus was trained on the scale-up parameters and the full-scale equipment. It was quickly determined to be an equipment issue with the full-scale chromatography skid (imprecise valve timing resulted in brief product contact with sanitizing solution). After correction, the second cycle of the engineering run and the next two GMP runs achieved a HMW percentages of 0.6%, 0.3%, and 0.3%.  

Good transfer criteria based on solid process history can foster and enable effective client–CMO interactions. It is vital to clearly demonstrate process reliability before a transfer and to set guidelines for evaluating a transfer based on client process history. If these guidelines are followed, standards will be met and client–CMO interactions will be smooth. 

 is the director of biologics process development at Millennium: The Takeda Oncology Company, Cambridge, MA, 617.679.7000, 

Sufficient process history is key to the rapid transfer of your process.

The Role of Process History in Establishing Clear Technology Transfer Criteria

As peptide-based therapies are increasingly becoming viable drug discovery and development targets, the industry is paying more attention to the quality concerns that underlie peptide manufacturing processes. Peptide synthesis for pharmaceutical manufacturing can be tedious and time-consuming given the complexity of the product and the lengthy, intricate synthesis process. Regulatory compliance, quality control, and quality assurance efforts are critical for the successful development and manufacture of peptides as active pharmaceutical ingredients. As a key element in the peptide production process, quality should be built into every step, and thought of as a process parameter, not a process outcome.  

As a key element in the peptide production process, quality should be built into every step.

BioPharm International-03-01-2010