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Antiquated manufacturing processes cost pharma money-a fact widely known and accepted in the industry. At some facilities, rejected batches, rework, and lengthy investigations have become a way of life, and by some estimates can inflate production costs by as much as 10 percent. According to G.K. Raju, executive director of the Pharmaceutical Manufacturing Initiative at the Massachusetts Institute of Technology, manufacturing consumes an estimated 25 percent of drug company revenues.
Philippe Cini, PhD, is a managing consultant of Tunnell Consulting, located in King of Prussia, Pennsylvania. He can be reached at firstname.lastname@example.org or (610) 715-1888. Raymond E. Schneider is Tunnell Consulting’s vice-president and practice director of Process/Organizational Excellence. He can be reached at email@example.com or (610) 337-0820.
Antiquated manufacturing processes cost pharma money—a fact widely known and accepted in the industry. At some facilities, rejected batches, rework, and lengthy investigations have become a way of life, and by some estimates can inflate production costs by as much as 10 percent. According to G.K. Raju, executive director of the Pharmaceutical Manufacturing Initiative at the Massachusetts Institute of Technology, manufacturing consumes an estimated 25 percent of drug company revenues.
That is a far cry from the standard of excellence cited by new FDA commissioner Mark McClellan, who wants pharma to match the semiconductor standard of only 0.0001 percent rejected for unacceptable quality. Why such a discrepancy? The FDA regulations that require approval of nearly every change to manufacturing processes give companies little incentive to modernize.
But FDA wants to change that. In August 2002, it launched the Process Analytical Technology (PAT) initiative, which it says is a "a framework for allowing regulatory processes to more readily adopt state-of-the-art technological advances in drug development, production and quality assurance." More important, the agency is promoting a transformative vision of pharma manufacturing: every batch of product manufactured right the first time and automatically released as soon as it reaches the end of the production line.
Although achieving that vision would produce quantum benefits in cost, compliance, and safety, uncertainty about the real meaning of the initiative has hindered its acceptance. Many in the industry saw PAT as a purely technological effort. But the agency wasn't just encouraging the use of near infrared spectroscopy and other in-process measuring tools. So in August 2003, it issued a new guidance that clears up much of the uncertainty and makes it clear that its initiative covers far more than technology. "It is important to note that the term analytical in PAT is viewed broadly to include chemical, physical, microbiological, mathematical, and risk analysis conducted in an integrated manner," says the August 2003 document. It also outlines the set of tools involved, which are grouped into four broad categories. (See "More Than Technology," page 92.)
Yet transformation won't come easy. Formidable obstacles remain, including the industry's ingrained aversion to risk (which was exacerbated by the former regulatory environment), a scientific culture that sometimes resists change, and a failure to import best practices from other process industries, most often because of academic and professional silos as well as regulatory barriers.
This article outlines the benefits of modernizing manufacturing, addresses the reasons companies are reluctant to embrace the initiative, explains the various technologies covered by the initiative, and shows how companies can adopt a step-by-step approach to manufacturing innovation that can be applied to both new drugs and the processes used with existing drugs.
The benefits of improved manufacturing are well known: higher quality, higher compliance, improved operator safety, fewer lost batches, fewer deviations, shorter cycle times, and more data-driven decision making. Yet overall industry performance remains poor. For example, Raju has shown that quality-control (QC) testing times are at least as long as processing times and significantly greater in several instances. (See "Time Well Spent?")
With manufacturing costing 25 percent of revenues, even a 1 percent improvement in efficiency produces significant financial benefits. For a company with $20 billion in annual revenue, every 1 percent reduction in manufacturing cost translates into savings of $50 million a year (.25 x $20 billion = $5 billion x .01 = $50 million).
Pharma companies often overlook two other significant benefits of using advanced production technology. First, the developing and filing of manufacturing processes that use proprietary or analytical technology can provide a significant barrier to entry for generic competitors. Second, the ability to provide evidence that a drug was consistently manufactured to exacting standards may prove persuasive if its quality or consistency is questioned in court. That is especially important today, when plaintiffs' lawyers, flush with cash from tobacco and asbestos litigation, are taking aim at drug makers.
Dispel the Fear
Despite the benefits of PAT, conversations with pharma executives reveal some common, but misguided, reasons for rejecting it. Some of the most frequently heard rationalizations—and their counter-arguments—are as follows:
The big drag. Many executives believe submitting process applications that involve PAT techniques may slow down the regulatory review and approval process.
Keenly aware of that concern, FDA is training and certifying a team of reviewers, compliance officers, and investigators on PAT issues and new technology to manage the review and inspection process. With a thorough understanding of policy goals and innovative technology, those teams should be able to respond to companies' initiatives quickly and comprehensively. "Our new strategy is intended to alleviate the fear among manufacturers that introducing new manufacturing technologies will result in regulatory impasse," says the 2003 guidance.
FDA also urges pharma companies to communicate their PAT plans early and to consider the agency a partner in moving PAT forward. A subcommittee composed of senior pharma and generic manufacturers, government officials, and private and academic consultants provided their recommendations for the PAT guidance. The document itself urges the creation of "communication mechanisms" such as meetings between the agency and industry, and informal communications between FDA and manufacturers during drug development. In addition, the guidance suggests that when manufacturers consult with the agency, they may want to discuss not only specific PAT plans but also thoughts on a possible regulatory path.
Pandora's Box. Executives' second-biggest concern is that applying analytical technology to existing processes may reveal situations better left alone. Some companies fear that the application of better manufacturing techniques will uncover problems with current processes that must be reported to FDA, resulting in costly and time-consuming remediation.
Problems are likely to surface eventually anyway, but with a PAT program in place, manufacturers are more likely to detect problems in their early stages rather than at the final release of the product or after the problem has become a full-blown regulatory crisis. Early detection allows early correction, often while the product is still within specifications. And it is far better for a company to develop a corrective plan on its own terms rather than under the pressure, direction, and deadlines of regulatory authorities. If a serious problem does emerge, it must, of course, be reported—PAT does not confer a waiver of such regulations—but even a serious problem is better caught early, before it becomes a disaster.
Too much money. Ever conscious of the bottom line, companies also fear that applying on-line (in-process) technology could be prohibitively expensive.
Costs will skyrocket only if the technology is indiscriminately applied to every process parameter. But by selectively applying technology to the few key parameters that affect variation, companies can not only keep costs down but also significantly increase their return on investment.
Generally, on-line technology, which provides nearly instantaneous and continuous measurement, should be applied as close to the front end of the manufacturing process as possible, which allows companies to monitor and control the true source of process variation and get the most out of their PAT investment.
Too much of a good thing. As FDA points out, "real-time or near real-time measurement tools typically generate large volumes of data," and production managers fear that analytical technology will generate more data than can be managed and used.
Just as reducing technology costs requires managers to identify key process parameters, managing the information generated requires them to precisely target what information is useful, how it can best be shared, and with whom.
Old vs. new. There seems to be some misunderstanding about which processes FDA had in mind; the original PAT initiative appeared to emphasize the use of innovative manufacturing during drug development.
But FDA's 2003 guidance explicitly says, "We encourage the use of PAT strategies for the manufacture of currently approved products." FDA also recognizes that processes created during small-scale drug development cannot simply be transferred to commercial production. Scale-up is far from an exact science. The processes based on the limited data available during drug development may be improved in light of the mountains of new data that emerge from commercial-scale manufacturing.
Considering the enormous potential benefits, pharma companies should view PAT as a long-term strategic initiative rather than as a series of short-term projects. The framework for such a comprehensive initiative includes five interdependent elements:
1. Develop a strategy. Company leaders should begin with a vision. By developing a vivid description of the end state desired, they can establish the basis for strategy development. For example, many pharma companies focus their vision on quality. They want every batch in every plant to be done right the first time: No rejections, no rework, no deviations. But that represents only one of many alternative visions—each company must develop the overall view that is right for its circumstances.
A clear vision enables leaders to identify the critical areas on which it needs to focus:
Although a company may ultimately choose to concentrate on a few areas only, by considering all of them in the context of its vision, it will avoid the pitfalls of isolated and uncoordinated elements that do not add up to a strategy.
Despite FDA's assertion that companies should be bold—that they need only communicate fully with the agency, which is prepared to accommodate new strategies and new technology—many fear that genuine innovations will take longer to win approval. To allay that fear, companies should also make mitigating the risk of pursuing PAT an integral part of their strategy.
2. Identify/reduce variation. Improving manufacturing requires companies to identify what causes variation in critical release parameters (the specifications that must be filed with FDA) and to reduce those variations. That doesn't mean companies should apply on-line technology to all measurements that would otherwise be made off-line—which is unnecessary and prohibitively expensive. PAT technology should be applied to the upstream parameters that are responsible for the variation in the finished product, enabling corrective action before out-of-specification problems occur.
Statistical tools such as process capability indexes including Cpk—which provides a quantitative assessment of how capable a process parameter is of meeting its specification limits—control charts, regression analysis, and design of experiments can establish the causal relationships between a finished product release parameter and other in-process parameters and raw-material specifications. In existing manufacturing processes, control charts help identify process data patterns that indicate a potential problem. When using control charts, shifts, trends, or outliers (statistical anomalies) can be correlated with a change in the process or a raw material, providing insight into the root cause of the problem.
For processes under development, the challenge is somewhat different. New processes yield limited amounts of data. Another powerful tool can help: the design of experiment. This statistical technique enables quantitative testing of the effects of several parameters at once, reducing the number of experiments required. As with regression analysis, it generates a table of effects that identifies the key drivers of variations and thus the prime candidates for PAT applications.
3. Manage the data.To achieve the highest level of quality manufacturing, the right data must be available to the right people at the right time. An effective data management strategy begins with an understanding of the ideal flow of information among the operational, tactical, and strategic levels of a manufacturing site. In general, objectives are set at the top by the site's leadership and rolled down to the managerial and shop-floor levels. There, operational data is gathered and monitored continuously, then frequently sent up to the engineers and managers at the tactical level and reviewed periodically at the top, strategic level. (See "Information Flow," page 90.)
Unfortunately, in many companies today, the data spewed by various computers and analytical devices on the shop floor remain unintegrated and unformatted. The data generated by those many platforms must be extracted and integrated in a database that can organize it by time and origin. Only then can a facility perform all of the functions that uncover the source of variation, then package that information in usable reports.
With easy and timely access to critical information through a web-enabled application interface, the right people can act on process variations before they become full-blown crises. And the software and hardware investments are relatively small: a data warehouse, workstations, and two types of software: ETL (extract, transform, and load) applications to extract data, and analytical applications to analyze and display data.
4. Develop analytical technology. As a result of pharma's initial perceptions of the PAT initiative, on-line analytical technology has received the lion's share of attention. Near infrared or Raman spectroscopy and chemical and thermal imaging provide almost instantaneous measurements of critical processes, and, ultimately, could help move pharma manufacturing from a batch-processing model to continuous processing-although that remains a long way off.
But before applying analytical technology to a specific process, those involved must have a thorough understanding of that process. That doesn't mean pharma companies shouldn't develop on-line analytical technology. For each class of drugs—solid dosage, parenterals, creams and semi-solids—companies can define the manufacturing steps that are most critical and therefore most likely to benefit from PAT. For example, in many solid-dose processes, the characteristics of the granulation blend will be key in determining the finished product properties. Therefore, developing on-line technology to measure particle-size distribution should be a reasonably safe investment for a solid-dose drug manufacturer planning to use PAT.
5. Reorganize for sustainability. Organizational changes bring the process full circle: the vision and the strategy must be communicated throughout the company. Leaders must anticipate a PAT deployment's organizational effects and understand the company's capacity for change. They must engage key stakeholders early and often. In implementing analytical technology, the vision and strategy must be translated into processes, operating procedures, and behaviors that can be measured and sustained.
Above all, PAT should not be treated as just another technology project, but as a long-term strategic initiative. If properly defined and implemented, analytical technology can bring sweeping changes to the way companies develop and manufacture medicines. One day the release of a production batch may not be done in an office by an individual looking at a batch record and analytical reports, but by someone on the shop floor reviewing in-process and raw-material data. The sooner a company undertakes a strategic PAT initiative, the sooner that day will come.