Biotech companies appear to be caught on the horns of an irresolvable dilemma. On one hand, they face more pressure than ever to reduce costs. On the other hand, the greater complexity of biotech manufacturing and the more challenging therapeutic areas it often addresses considerably raise the bar for achieving compliance. The conventional wisdom holds that Lean might reduce costs but it will put compliance at grave risk. And noncompliance isn't an option.     

As is often the case, the conventional wisdom is wrong. Rightly understood as a tool for improving business and manufacturing processes, Lean can help reduce costs and improve compliance simultaneously. The principle is simple: reduce waste. Eliminate redundancies and unnecessary steps and cost savings will not only occur, but compliance will improve as well. In fact, many compliance activities themselves involve unnecessary steps that not only waste money but also actively damage compliance. 

Consider the case of a biotech and its attempt to meet FDA requirements. After an inspection, the agency informed the company that its quality systems were not robust enough to assess the effects of all the incremental changes the company had made to its processes over the years. In response, the company decided to build a "system evaluation operation," a redundant quality system that soon grew to nearly three dozen people. This elephantine operation only made compliance harder because collecting all of the data and assessments that had been promised to the FDA was virtually impossible to accomplish in a timely manner. As a result, the company often had to report instances of nonconformance. It was the worst of both worlds—higher costs and lower compliance. And it was an entirely self-inflicted wound that could have been avoided if the company had concentrated on improving its existing quality systems and showing evidence that those systems had matured.   

In other cases, biotech companies accumulate costly and unnecessary compliance activities because of what amounts to company folklore about the FDA. When asked why they engage in a particular compliance activity, company personnel will often reply "because the FDA requires it." Often, however, it turns out that the agency requires no such thing. For example, at a biotech production and packaging site for a major global pharmaceutical firm, we noted that the good manufacturing practice (GMP) space was being cleaned by company employees when outsourcing the job could have saved money. When we asked about the practice, the response was: "The FDA requires that company employees clean GMP space." There is no such FDA requirement. In fact, with a little digging, we discovered that there was no such corporate requirement either.   

In other cases, biotech companies know that some of their practices are redundant and costly, but they believe stripping out a prior commitment to the FDA and reporting the change will just precipitate more compliance headaches. The company doesn't want to simply stop supplying data from, for example, an extensive assay that has always been performed, so the practice continues, even though it's unnecessary. Further, redundant compliance activities suggest to the agency that the company doesn't trust its own methods to yield accurate results. The company paints itself into a corner and costs itself money year after year. Meanwhile, the FDA welcomes improvements in processes and has made it clear that it intends to encourage continuous improvement.   

The big spending to gold-plate quality, the complying with non-existent regulations, and the care taken not to stir up the FDA are all intended to improve compliance. Ironically, those good intentions often produce the opposite result.  And they're costly.  

Instead of operating out of good intentions, it's far better to strive for best practices. It begins with a clear-eyed assessment of end-to-end processes guided by the simple Lean principle that waste is bad and should be eliminated now. The assessment may include step-mapping and in-depth interviews with personnel about what they do. And there should always be the question: why? Why do you do it that way? And if they say that the FDA requires it, then the question is "are you sure?" The next step is to check agency guidance and review correspondence with the agency, ideally in a searchable database.  

In an assessment of two biotech plants operated by a leading global pharmaceutical company, we found hundreds of opportunities for cost savings. In isolation, many of the wasteful and unnecessary activities appeared to be relatively small matters, but in the aggregate they added up to millions of dollars in waste and significant amounts of time spent on compliance problems. Using Lean techniques to identify opportunities and eliminate wasteful and unnecessary activities, the plants were able both to improve compliance and lower costs. For example, the chances for noncompliance, whether caused by personnel or equipment, were greatly reduced by:         

eliminating process steps such as the 15-L inoculation in fermentation and the drying step in formulation to simplify the work flow 

eliminating unnecessary testing steps such as filters testing in media prep that caused the filter to fail 

increasing the short validated dirty hold time 

increasing batch size in purification reduced the overall number of batches run per year 

reducing the frequency of process steps such as column packing in purification from every 50 to 100 runs 

reviewing the environmental testing frequency to determine permissible reduction and elimination of tests, resulting in less testing 

evaluating the feasibility of setting frequency by location, based off trended historical data 

evaluating what was really necessary for non-aseptic class C

automating laboratory air results to eliminate manual or paper-intensive processing.

All of these improvements were based on genuine FDA requirements, not phantom regulations, folklore, or merely good intentions.  In effect, compliance was treated as a "pull" system, analogous to the pull system in heavy manufacturing, where the amount of material and the timing of activities are determined by what is necessary—and only what is necessary —as the product moves through the factory. In this case, however, pull is exerted by genuine, documented requirements, which determine what compliance activities are really necessary as the product is produced. By contrast, a "push" system heaps unnecessary compliance activities on products and processes in the mistaken belief that more is better.  

In a pull system, less is more—producing dramatic improvements in return on investment, quality, efficiency, and cost. And because of the regulatory complexities of biotech drugs and the unnecessary activities they often generate, the number of opportunities for improvement is far greater than with small-molecule drugs. All that is required is a determination to take a hard look at business and production processes with fresh eyes, free of the conventional wisdom that efficiency puts compliance at risk. Then the operations executive under enormous cost pressure and the head of quality concerned about the next inspection can link arms and confidently declare that they want to eliminate waste because it saves money and improves compliance.  

 at Tunnell Consulting, King of Prussia, PA, 215.422.2044,  

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Use Lean techniques to improve manufacturing compliance

When Less is More: Lean Can Help Reduce Costs and Improve Compliance Simultaneously

 Quality by Design (QbD) is a promising opportunity for biopharmaceutical companies to capitalize on the current regulatory and industry focus on drug product quality and process control by leveraging science, compliance, and investment for the benefit of patients and stockholders. Companies that recognize the potential benefits have made excellent progress with QbD and have successfully filed applications with the US Food and Drug Administration, QbD's primary advocate. Others, who have used QbD tools informally, are considering more structured cross-functional approaches for product development. Many others, however, are standing on the sidelines waiting for what they see as the latest quality management flavor-of-the-month to run its course. The challenge for QbD implementation is to convince these sideline skeptics. This article discusses reasons for the skepticism and provides suggestions to managers for how to implement QbD in their companies.    

Depending on whom you talk to, you will get different descriptions of what QbD is. Some see it as a product approval 

 to raise the regulatory compliance bar or the latest flavor-of-the-month that adds bureaucracy, cost, and time to product development. All QbD really means, however, is that products, and the processes that make them, are designed in advance to meet their product quality specifications and process control requirements.  

The truth is that QbD is based on solid science, valid statistical tools, and sound management techniques that have proven their industrial value for many decades. These include product profiling, experimental design, process mapping, risk assessment, and automated process controls. The goal of QbD is to apply these tools in a structured manner. 

These techniques are suspected of taking too much time and costing too much compared with the traditional trial-and-error methods that have been prevalent in development. But a better approach is to structure an experimental design that optimizes the available development time and project funds while maximizing the product and process data delivered. If this sounds too good to be true, consider that design of experiments (DOE), the heart of QbD, offers returns that are four to eight times greater than the cost of running the experiments in a fraction of the time that it would take to run one-factor-at-a-time experiments. (See box on DOE). Furthermore, these approaches are the only way to unlock interactions of multiple factors, something trial-and-error and one-factor-at-a-time experiments cannot. When the QbD approach is used, products are purer and more potent and processes are more robust and have higher productivity. Also, technology transfer risks are reduced because fewer start-up runs and less start-up time are needed, which can lower start-up costs and speed the time-to-market. 

The univariate trial-and-error approach to product development is traditional and can be safe in the short term. With the time pressure to be first to the market, it is an easy way out. Although this methodology may produce safe and effective products, there is considerable room for improvement and risk reduction. Product quality, process productivity, and profitability can be improved with further in-process refinement and reduction of product variability.  

If the traditional approach is ok, why should we be concerned with cost and productivity? Companies, governments, and health maintenance organizations (HMOs) face conflicting budget priorities, expanding demand, and higher costs per person for healthcare. Product cost and the cost of quality and compliance are under increasing pressure to be justified or reduced. In short, improved quality, higher productivity, lower cost, and improved compliance are the roadmap for the future. These goals can be achieved with QbD application. Neway has efficiently made the business case for QbD.

Most people are willing to change; they just don't like being changed. The desire for change needs to be internal. Culture is a big factor in the adoption of new ideas and approaches. Some companies are open to change and others are resistant. Management must lead the way by setting a good example. Although management support is critical, it can only go so far. At some point, scientists and engineers must understand and accept the reasons for and benefits of changing to a QbD approach. One way to do this is to identify and discuss why they are skeptical and less than willing to change. 

Activities like QbD and process analytical technology (PAT) have been standard practice at chemical companies since the mid 1950s. These companies embraced these approaches because it saved them large amounts of money and time. But chemical companies, of course, are not regulated the way the pharmaceutical industry is. Our regulations create a different environment, and we must adapt to that difference. Validation presents the most obvious constraint.  

But even validation, now accepted as a basic requirement, was once a new concept. When validation was first expected of companies, a number of articles were published that argued against it.

  Interestingly, despite all the skepticism about QbD today, we have yet to see an article challenging it. Instead, the doubts seems to be expressed more quietly, perhaps out of fear of contradicting the regulators who support it. But there must be a discussion of the pros and cons of QbD. We must be able to justify QbD in real terms of reduced risk to the patient and money and time savings. Without a vigorous discussion, it will quietly fade away and the tremendous benefits will be lost. 

The skeptics have valid concerns that must be answered clearly. During the webcast of "Pharmaceutical Quality by Design: The Road Ahead," the participants were polled for their concerns about QbD.

  According to the responses, 39% were concerned about lack of clarity on what the concept means; 15% had time constraints (it takes too long) and 13% had budget constraints (it costs too much) for QbD implementation; 13% were concerned about the lack of management support and 11% about the inability of quantifying potential benefits; and 9% had concerns about lack of skilled personal. These concerns are expected and timeless. Every new endeavor faces similar comments.  

The lack of clarity is being addressed by the FDA and industry organizations by presenting conferences, seminars, training, and publications. The FDA has been very proactive in giving talks and being available for discussions. Participants must continue to read, reread, and discuss the available information until the concepts and ideas become clear enough for implementation. 

Time is money, and thus the concerns about time and cost can be discussed together. Any new activity is awkward, slow, and inefficient. A student just learning to use a keyboard is frustrated. But with determination and practice the student gains proficiency and speed. Eventually, the keyboard becomes second nature and the attention is on the contents of the document and not the skill of typing. So it is with QbD. At first, it is strange and uncomfortable. The old approach seems faster with fewer trial runs. In the short term, the old ways seem better. But QbD takes a lifecycle approach. The goal is to minimize total costs and time from initial development to product retirement. "Pay me now or pay me later," was once a jingle for motor oil, meaning you could pay to change the engine oil as needed or replace the engine later. The same applies to development. If you short change the development stage, you may pay later for more rejected lots, stability failures, 483 citations, warning letters, and recalls. 

Management's support is essential; without it few initiatives prosper and succeed. As W. Edwards Deming so forcibly told us, "It is management's job to work on the system so the employees can work within the system." For example, management needs to make QbD easy to implement. Anything less than full support is worthless. 

The inability to quantify potential benefits is a management issue. Cost of quality systems have been used for many decades in the field of quality control.

  Modifications to these systems can potentially be an easy way to initially carry out a cost–benefit analysis. A paper published in the year 2000 titled "The Cost of Non-Conformance: The Linkage Between Quality Performance and Business Results" also proposed an approach to be considered.

  The authors developed the "Cost of Non-Conformance Model" to capture the business impact of non-conformance with quality standards and regulations. 

Management should start with the employees that are eager to participate, and encourage, support, and reward them in public. Others will join in as they see the rewards and benefits of participating. Formal and informal training is needed for topics such as statistics and DOE, and the related software.

Other comments by skeptics have been used to deflect encouragement to implement QbD and DOE. Here are some of the more common ones with replies. 

"This is just the latest fad, the flavor-of-the-month. Just watch, this will be replaced by some other new corporate initiative by the next VP or CEO." This could be the case in some companies. Progressive companies that have a long-term view of success, however, recognize the benefits of embedding QbD into the company culture. 

"Time-to-market is our primary driver. We need to be first in the market; we will fix any problems later." Time-to-market is important, but being first in the market with a third-rate product and process is not a good route to success either. Again, the concept of lifecycle optimization  underlies QbD.  

"Our development is more art than science. Designed experiments don't work for this. It takes years and years of experience to develop our products." This is an admission that sources of variability are not known and are not being controlled. Process understanding is a key concept in QbD and PAT. Without control of material and process variabilities, the process capability of any new product is just a guess

A foundation of variation control is fundamental to any development. 

"Statistics was my most difficult class in college." Unfortunately, many university statistics classes are too theoretical and are often intended for mathematics majors. The field of statistics was born at the junction of biology, genetics, and mathematics in the mid-to-late 1800s as practical way to deal with variability and large amounts of data. Applied statistics courses, however, can be very helpful, particularly if they are sufficiently pragmatic and data oriented. Most applied courses require only algebra. The root cause of the problems is that most students are not exposed to any statistical concepts until they are adults in college. If the process development staff lack a solid foundation in statistics, management must support inhouse training or send staff out for applied courses. 

"If my major professor didn't think this (QbD, DOE) was important enough to teach it to me, then it must not be anything I need." This is understandable, regrettable, and self-perpetuating. There can be two reasons for the professor's failure to promote QbD. First, the professor's goal is to teach the science subject, not statistics. Like knowing algebra or grammar, the professor assumes the student has the background or will get it later. The second reason is that for most courses, the focus is on theory and not on applying or implementing the concepts using data. 

Finally, we must acknowledge two human failings—the failure to get expert help and the lack of willingness to endure failure. It can be difficult for successful people to ask for help in a subject they don't know. They feel that they should be able to master the topic themselves. Again, management needs to step in with support and encouragement. Encouragement and money are further needed to weather the inevitable failures.  

Not all endeavors succeed and not all experiments are breakthroughs, but we learn from the failures. Experimentation should be seen as guided learning that builds the knowledge base of the company and thus competitive advantage. QbD is a process, not an event. Knowledge gained in one set of experiments is used to refine and design the next set of experiments. QbD is an investment, not an expense. 

It is human nature to resist new and different ways of thinking and working. Given past management fads, skeptics have a legitimate concern about the long-term sustainability of QbD. But the 50-plus years of its application in the major chemical companies is an assurance that it can be implemented successfully. QbD offers future benefits to companies and management willing to invest in the time and effort to be competitive. 

If QbD really is the competitive future, how can we learn more about it? The key industry organizations delivering education and training in the principles and tools for successful QbD implementation are the American Society for Quality, the Parenteral Drug Association, the American Association of Pharmaceutical Scientists, and the International Society for Pharmaceutical Engineering. The courses, seminars, and workshops sponsored by these organizations have demonstrated that projects using QbD approaches can be more efficient, less costly, and data rich in the development of new products. Process scientists have also learned how to mine data using these tools to improve existing products and processes.  

Take advantage of this opportunity. Learn more about QbD and use the tools to enhance the products delivered to patients and also improve the financial bottom line.  

 1. Neway J. How to make the business case for Quality by Design. BioPharm Int. 2008:21(12):42–47. 

  2. The Problem of Process Validation," J. R. Sharp, The Pharmaceutical Journal, January 11, 1986. 

 3. PharmaQbD web cast; 2008 Oct 14. Available from 

 4. Gryna FM. Quality and Costs. Juran JM. Godfrey AB, editors. Juran's Quality Handbook. 5th ed. New York: McGraw Hill; 1999. p. 8.1–8.26. 

 5. Dwyer T, Keresty G, Sherry B. The cost of non-conformance: the linkage between quality performance and business results. Pharmaceutical Eng. 2000 Sept/Oct:8-18. 

 6. Design Ease, Inc. Design Expert, Version 7.1. Available from: 

 7. Fisher RA. The arrangement of field experiments. J Ministry Agriculture, England. 1926;33:503–513. 

 8. Torbeck LD, Branning RC. Designed experiments-a vital role in validation. Pharm Technol. 1996;20(6):108-114. 

 9. Fisher RA. The design of experiments. London: Oliver and Boyd;1935. 

 10. Box GEP, Wilson KB. On the experimental attainment of optimum conditions. J Royal Statistical Society. 1951(13):1–45. 

 11. Rathore AS, Branning R, Cecchini D. Quality: design space for biotech products. BioPharm Int. 2007;21(4):36–40. 

Features

Without a rigorous discussion of the pros and cons of QbD, its tremendous benefits will be lost.

QbD: Convincing the Skeptics

Already being actively followed by several industries, the overall equipment effectiveness (OEE) approach quantifies the percentage of time that equipment operates to produce an acceptable product. It measures how effectively machines are being used by examining productivity and performance diagnostics at the equipment level.

  It also monitors actual performance relative to performance capabilities under optimal manufacturing conditions.

  OEE breaks down non-operable time into shutdown losses (such as preventative maintenance, personnel breaks, and training), operational downtime, changeover downtime, equipment failure, process failure, and production adjustment losses, which then are measured to calculate availability, performance, and quality losses.

 Overall equipment effectiveness (OEE) helps maximize value-added activities by indicating precisely where potential improvements might be most effective. This makes it an ideal measure for capital equipment-intensive businesses such as biopharmaceutical manufacturing.

  Other typical OEE improvement opportunities include faster changeover, less idle time, optimized equipment maintenance, shorter production cycle times, increased equipment reliability, and optimized equipment purchases.

OEE VERSIONS, CALCULATIONS AND QUANTIFICATION

Different versions of OEE have been developed and adapted to specific industry problems. Some are oriented to measure overall factory or plant effectiveness instead of equipment (Table 1).

  At a micro level, OEE can focus on a specific piece of equipment; at a macro level it can focus on a processing suite, equipment process train, or even the facility itself. Different OEE versions use similar methodologies.

Table 1. Versions of overall equipment effectiveness 

In many industries, a plant-wide view is needed to optimize factory effectiveness, especially for complex, resource-constrained processes that often have significant human and equipment interactions.

  A composite picture is developed for key attributes such as equipment effectiveness, cycle-time efficiency, on-time delivery, manufacturing costs, process yields, production volumes, inventory turn rates, and ramp up performance.

  The effectiveness of this approach was demonstrated by wafer fabricators, and it is readily applicable to biopharmaceutical manufacturing.

OEE's goal is to develop systems interacting and interfacing with all process equipment to ensure "the right material is with the right tool at the right time."

  This approach avoids instituting locally beneficial controls and improvements that may unintentionally reduce overall efficiency.

  Activities and relationships among different equipment and processes are combined, integrating information, decisions, and actions across several independent systems.

  Such an approach is explicitly applicable to several aspects of biomanufacturing (such as water for injection and clean steam usage across processing suites, and product stream flow from cultivation to harvest to isolation suites). Computer integrated manufacturing (CIM) through automated manufacturing execution systems (MES) supports these integrated improvement goals by 1) managing complexity, traceability, and genealogy, 2) simplifying quality and yield management, 3) facilitating production planning and scheduling, and 4) managing data to support decisions.

OEE is calculated based on the product of availability, performance, and quality, each expressed as a time-based ratio:

), is the operating or "up" time divided by the total time; performance efficiency, (P

), is the theoretical processing time to achieve output goals divided by actual processing time, and the quality efficiency (Q

), is the time spent producing good product output divided by total time spent making all product lots.  

Simple OEE is calculated as the ratio of good to total (theoretical) output, each expressed as a count: 

 is the number of actual conforming (good) lots and 

 is the number of theoretical possible lots, assuming maximum levels of availability, performance, and quality.

OEE data permit benchmarking within and across industries that drives targets for continuous improvement initiatives (Table 2).

  Typically, quantitative data is desirable but qualitative data (e.g., estimates from subject matter experts) also can be useful.

  An OEE around 85% is considered world class performance across industries for a batch plant.

  If OEE approaches 85% but is still constraining, then likely additional capacity or process redesign is needed. If OEE is <70%, then usually the desired improvement goal is achievable using current equipment and processes.

Table 2.  Overall equipment effectiveness and component values for various industries 

OEE associated with continuous manufacturing plants (e.g., chemical, petroleum, or paper industries) typically have high 

  OEE associated with batch manufacturing plants have lower 

 owing to more frequent set up and clean-up steps. Most biomanufacturing processes are batch in nature with a few notable exceptions. OEE data can be used to create either a histogram of OEE level versus its frequency or a progressive run chart showing OEE levels before and after improvement implementation.

A major part of OEE is time. Waterfall charts and similar tables are useful ways to visually depict time losses (Table 3). Starting with the total available hours as 100%, the hours that production is not planned to run (such as planned preventative maintenance, shutdowns, and holidays) and the time lost to set up or clean up and breakdowns (availability loss) are subtracted. Next, the time caused by capacity losses caused by slow running speeds is subtracted (performance loss), followed by the time caused by losses from waste and defects such as discarded lots (quality loss). The result is the effective hours of processing for output of acceptable product lots.

Table 3.  Breakdown of overall equipment effectiveness availability time calculations2,6 

Availability efficiency is the fraction of time that a piece of equipment, suite, or facility is in a condition to perform its intended function or simply the amount of time processing actually occurs.

  There are six main states: 1) the unscheduled state (not planned to be used); 2) the unscheduled down state (not able to perform); 3) the scheduled down state (not planned to be available); 4) the engineering state (used to conduct equipment or process trials); 5) the standby state (not operated because of lack of personnel or support equipment); and 6) the productive state (performing as intended).

Availability is limited by: 1) equipment, process and facility shutdown, maintenance, or failures, which lead to the unscheduled state and both the scheduled and unscheduled down states, and 2) set up and adjustment which primarily lead to scheduled downtime.

  The unscheduled state and scheduled down state includes planned maintenance, operational shutdowns, unworked shifts, and holidays. The unscheduled down state generally includes unplanned shutdowns, lack of demand, breakdowns, and operator unavailability.

  Set up or adjustment losses occur when production of one product ends and equipment is adjusted to meet requirements of another product [such as changeovers, preventative maintenance, cleaning and sterilization, equipment or process trials (engineering runs), and qualification]. These changeover times can be greater than production runs, and in multiproduct bioprocessing facilities, they typically are substantially greater.

  Changeover is often a key improvement opportunity, with best-in-class companies achieving significant reductions through cross-training team members, implementing lean principles such as workplace organization, and developing quick changeover techniques.

Performance efficiency is the fraction of equipment uptime that the equipment is processing actual lots at theoretically efficient rates.

  Consequently, it reflects losses incurred by suboptimal operation, specifically the difference between design and actual speeds.

  Idling or minor stoppage and rate losses prevent achieving maximum speed because production is interrupted or slowed respectively by a temporary malfunction, lack of input because of poor raw material or intermediate stream quality, or insufficient personnel.

  This category can be a catchall for unclassified or immeasurable losses.

  In biopharmaceutical manufacturing, performance efficiency can reflect inefficiency from unexpected campaign starts and stops (e.g., in-process assay delays), or from longer than expected step processing times (such as slower than expected depth filtration).  

Another factor is quality, defined as "right the first time it is done."

  Unacceptable quality includes yield losses (leading to scrap) and defects (leading to rework) caused by equipment malfunction and start up losses in which yields are lower during early stages of a new campaign before stabilization.

  In biopharmaceutical manufacturing, quality losses include atypical events such as contamination, impurities, and incorrect documentation that often occur in initial batches for a new product campaign in a multipurpose facility. 

Total productive maintenance (TPM) aims to maximize equipment productivity during its service lifecycle and extend its length of useful service. OEE is a basic building block for TPM because it quantifies both loss types and their durations to appropriately focus on improvement activities.

  TPM analyzes reasons for equipment waste (such as repeated similar repairs and inadequate training) to improve OEE, thus reducing equipment duplication and freeing-up valuable processing space. Its goals are zero breakdowns, speed losses, defects, and accidents.

  It focuses on autonomous maintenance by operators through small group activities to develop ownership, and improving relationships among people, processes, and equipment.

  Equipment reliability, not only its downtime (availability) but also underuse relative to installed capabilities (performance), minimizes compensating purchases of duplicate units of expensive or large footprint equipment.

  Without OEE, organizations unknowingly invest capital, and thus OEE data can support or challenge capital proposals.

Related to total productive maintenance, total preventative maintenance focuses on preventing breakdowns rather than fixing broken equipment, also including operators in maintenance and monitoring activities.

  Strategies exist to reduce losses caused by inadequate spare part stocks, attempting to achieve zero losses with the lowest spare part inventory possibly by eliminating waiting time for critical spares.

Single minute exchange of dies (SMED) aims to reduce equipment downtime consumed by changeovers and set ups associated with switching products.

  It is particularly applicable to biomanufacturing facilities that have multiproduct suites. Downtime is measured as the time from the last good product of type A to first good product of type B.

  Set up reduction helps meet increased customer multiproduct demand because some changeover times can be longer than product cycle times, dramatically reducing suite availability.

  Changeover activities are classified as internal or external based on their ability to be executed during processing of the previous product.

  The next step is to reduce, eliminate, or convert as many internal activities to external, and then progressively shorten remaining internal activity times.

The theory of constraints is a five-step cycle to identify constraints that restrain production systems from achieving high overall operational excellence.

 a system flowchart is developed. Productivity parameters are defined along with metrics to guide data collection. 

 metrics are calculated at the equipment, subsystem, and system levels. 

 bottleneck productivity is evaluated (using 

) and losses identified at upstream and downstream of the bottleneck. 

 the limiting constraint is identified, then simulation is used to assess various scenarios for its removal. 

the entire cycle is repeated to identify and eliminate new constraints. 

This strategy can be applied to develop alternatives to alleviate the current purification bottleneck in biomanufacturing because of the rise of bioreactor product titers.

A generic problem-solving process can be used in biomanufacturing to efficiently remove OEE limitations.

  The simple steps for this process are: (1) recognition that a problem exists that should be solved; (2) allocation of appropriate priority to develop the solution (i.e., identify possible causes and alternative solutions, and then selecting a solution); and (3) solution monitoring to determine its effectiveness.

Armed with flow charts, assembled cross-functional teams review the step and its support functions to identify failures, calculate failure values (i.e., failure type x frequency x loss per failure x values per loss), prioritize losses with the greatest improvement opportunity, and then select appropriate solutions to minimize future losses.

How to optimize facility utilization and improve plant performance.

Application of Overall Equipment Effectiveness to Biopharmaceutical Manufacturing

The sale of interests in discrete product revenue streams has taken hold as an alternative financing source for holders of biopharmaceutical intellectual property (IP). Holders of these IP assets are often either constrained in their reasonable access to capital (e.g., small fast growing pharmaceutical companies) or limited in their interest in managing an IP portfolio, which may be diffuse or require commercialization beyond the development of the basic science involved (e.g., university medical centers). These sale transactions fall broadly into two categories: structured sales of portions of future revenues from a specified compound or biopharmaceutical IP asset over a defined field for a specified period of time (revenue interest transactions) and structured sales of future revenues from an existing out-license, typically to a much larger pharmaceutical company (royalty interest transactions). Although these transactions have similar considerations at their core, such as strength of the underlying IP and assessment of the likelihood of longer-term commercial success, they also present distinct issues from the perspectives of the typical financial investor (the buyer) and the owner of the compound or biopharmaceutical IP asset (the seller).   

In royalty interest transactions, a core consideration is the allocation of rights and responsibilities with respect to the specific out-licensing arrangement. The same issue is substantially less significant for revenue interest transactions because they are modeled on the basis of a non-counterparty specific revenue stream and are documented to contain substantial consent protections relative to future out-licensing and other transfer transactions. Therefore, revenue interest transactions are generally independent of risks associated with obligor or counterparty concentration and are not subject to the pre-existing contractual regime present in a typical royalty interest transaction. Below, we examine the practical and legal considerations for evaluating the out-licensing arrangement in a royalty interest transaction, including the allocation of rights and obligations with regards to the out-licensing counterparty (the licensee). We also discuss mitigating considerations for resolving the often competing interests of the buyer and the seller relative to this core arrangement. 

The essence of a royalty interest transaction is the monetization of a generally well described, yet commercially speculative future cash-flow stream, from an existing out-license with an identified licensee of a specified product. From an analytical perspective, valuing the out-license presents two challenges: (1) assessing the likelihood of successful future commercialization by the licensee and (2) determining the rights of an assignee (whether in whole or in part) as a legal matter under the out-license agreement (especially in relation to the licensee).  

The analysis of the likelihood of successful future commercialization involves a combination of regulatory and IP due diligence to assess the likely success of subject IP in the marketplace. From a legal perspective, the focus is on the rights of the assignee (the buyer) under the out-license, including a review of the out-license to determine the scope of the field covered by the out-license to establish the benchmarking against which the competitive landscape can be measured, and the mechanics for determining the amount payable by the licensee to the licensor. 

The standard out-license usually contains a broadly drafted, often bilateral, prohibition on assignment (e.g., "... neither party shall assign any of its rights or interests under this [a]greement"). This provision is, at first look, very problematic to the buyer of the subject royalty interest. Although the buyer's principal consideration is its analysis of the likely future cash flows from the out-license, it is necessarily concerned with its ability to ensure that its rights to those cash flows are superior to the rights of the seller and the seller's creditors, with respect to that asset.  

The prophylactic measures taken by the buyer include structuring the transaction with the seller to maximize the possibility that the transaction will be treated as a sale rather than as a financing in a seller insolvency proceeding. Usually as a backstop, and less frequently as a primary position, the buyer takes steps to ensure that it enjoys the status of a senior secured creditor with respect to the cash flows. 

In certain cases, usually as a result of either structural impediments or tax and accounting considerations, a royalty interest transaction is structured purely as a secured financing, rather than a sale with a backstopping position as a secured financing. In doing so, the buyer is able to avail itself of the protections afforded by Article 9 of the Uniform Commercial Code (UCC) in dealing with the seemingly problematic anti-assignment provisions of the out-license. The UCC is a set of laws that are enacted in relatively uniform fashion by each of the states for dealing with the rights and obligations of parties to commercial transactions. Article 9 of the UCC deals with the subset of the commercial landscape consisting of secured transactions (dealing with most types of personal property). 

Under the UCC, as a contract arrangement, the out-license is likely characterized as a general intangible. 

 is defined in Section 9–201 of the UCC and is a catch-all category for collateral (i.e., if the collateral is personal property that doesn't meet the definitions of the other types of personal property subject to Article 9, in most cases it defaults to the category of general intangible.) If an analysis of the out-license demonstrates that the licensee's principal obligation is a monetary obligation, it will be classified as a special type of general intangible known as a 

. This determination is relevant because different sections of Article 9 of the UCC address the anti-assignment problem depending on whether a general intangible is or is not a payment intangible. 

The UCC deals with the issue of anti-assignment provisions broadly speaking by permitting the granting of security interests in general intangibles, explicitly including licenses, and other enumerated collateral types and providing that contractual provisions establishing default rights or otherwise prohibiting assignment are ineffective with respect to the granting of a security interest in the subject agreement. This is shown in Sections 9–406 (dealing with payment intangibles) and 9–408 (dealing with other general intangibles) of the UCC.  

These provisions do not, however, entitle the buyer to enforce the out-license. Those rights remain with the seller, where the UCC is concerned. In most out-licenses, the licensee's obligations are not restricted to the payment of money. They involve significant undertakings to commercialize the subject IP, to protect the IP and not transfer or sublicense rights therein, and to use the IP in accordance with applicable laws. If these other obligations are sufficiently broad, the better view is that the out-license is a general intangible and not a payment intangible. However, if the licensee's obligations under the out-license consist principally of a payment obligation, then the out-license would constitute a payment intangible.  

The relevant distinction under the UCC between a general intangible that is a payment intangible and one that is not is that Section 9–406 deals with security interests in payment intangibles and Section 9–408 deals with security interests in general intangibles that are not payment intangibles. These sections operate in a similar fashion. It should be noted that Section 9–408 also deals with sales of as opposed to security interests in payment intangibles. 

To deal with the enforcement rights under the out-license, the buyer in a royalty interest transaction must maintain the continued involvement of the seller because the UCC does not render the anti-assignment provisions void relative to enforcement rights. At a practical level, this is often a highly negotiated issue, particularly in circumstances where all or nearly all of the seller's economic interest in the out-license is intended to be acquired by the buyer.  

If the seller has no meaningful retained economic interest in the out-license, it has little incentive to vigorously enforce its rights as putative licensor against the licensee. This problem is ultimately handled either by aligning the seller's interests with the buyer's interests (e.g., creating a concurrent or tail economic interest for the seller) or by specifically negotiating rights of prosecution in the name of the seller for the buyer with appropriate protections, usually in the form of expense reimbursement and indemnification for the seller. 

As part of an established and growing source of alternative investing, royalty interest transactions draw on multiple analytical and legal disciplines. In dealing with the legal challenge presented by the out-license, the buyer has both legal protections available from the UCC and common structural techniques for maximizing its rights relative to the out-license in relation to the licensee and the seller and its creditors.  

are both partners at McDermott, Will & Emery LLP, Chicago, IL, 312.984.2066, 

Several legal considerations are key to protect the buyer and seller in royalty interest transactions.

Royalty Interest Investing: Addressing the Out-License Assignability Issue

			Healthcare reform is coming. That is good, because our current system is chaotic, inefficient, and most importantly, leaves too many people unprotected. And yet, though I believe strongly in the need for universal coverage, I do worry that any reform will hurt the drug industry's ability to innovate.    

Ian Morrison, however, has a different perspective. A self-described futurist who has studied healthcare systems around the world, Morrison outlined four potential paths for US healthcare reform in his keynote address at the PDA Annual Meeting in April. And although none of the four options is rosy for the industry, some are better than others. 

In two of them, public insurance provides most coverage. In the first of these, which Morrison calls "Sliding toward Australia," we move away from employer-based coverage to a government system of basic care, supplemented by private coverage. However, if the poor economy continues through 2011 and early healthcare reform efforts stumble, Morrison says, we could see a second scenario in which new legislation opens up Medicare to 95% of the population, followed by massive cost cutting. For drug manufacturers, he says, this would be a "nuclear winter with little hope of spring."   

In the other two possibilities, private insurance continues to predominate. The first is what he calls "the Obama boom." This scenario assumes that the stimulus plan works and we see GNP growth by early 2010. The resulting bipartisan healthcare package would be a variation of Massachusetts-style reform that adds a massive investment in healthcare IT, comparative effectiveness programs, and a phased-in mandate for individual coverage along with guarantees that insurance programs cover everyone. There would be no new public plan, and employer-based coverage would still be the norm. 

The last scenario is what he calls "No we can't." The safety net would be increased for the most vulnerable, but there would be no significant coverage expansion. Essentially, this is the status quo. 

So why is the status quo not the best option for the drug industry? The reason, Morrison says, is that it will become increasingly unsustainable. Out-of-pocket costs will continue to rise, and although most big employers will continue to offer health benefits, employees will bear a higher portion of the cost. Many small employers will abandon coverage. The number of uninsured will reach 60 million. As the pool of people able to pay declines, the growing pressure will lead to "ruthless cost management" in the industry to maintain margins. Thus, according to this analysis, the least of four evils in healthcare reform is the Obama administration's plan.  

Assuming that scenario goes forward, I hope policy makers focus on reforming the healthcare 

, rather than making superficial fixes like cutting drug prices. Too often, drug prices become a popular target because people focus on what they see: their out-of-pocket costs for prescriptions, even though drugs comprise about 10% of the overall cost of healthcare. Most people don't see the waste of poorly performing hospitals, the disproportionate expenditure on well-reimbursed medical procedures, or the 25–30% more we spend in healthcare administration compared to countries with a single-payer system.  

All healthcare systems are an ugly compromise, Morrison says. I just hope that in our effort to find a better compromise than the one we have now, we don't decimate pharmaceutical innovation. 

Avoiding healthcare reform is not the best option for the pharmaceutical industry.

The Least of Four Evils

Regulatory compliance remains a critical issue facing the biopharmaceutical industry. Poor and incorrect validation can cost manufacturers millions of dollars in lost time. With increasingly stringent regulations, rising manufacturing costs, and decreasing product pipelines, it is vital for manufacturers to achieve efficient and effective compliance of facilities, processes, and equipment. One area of concern is facility validation. Many new biopharmaceutical facilities fail to go online on time because the validation element of the build project runs over time and over budget.   

The problem has been exacerbated because the industry continues to follow a traditional and complex approach to facility validation, in which validation planning starts during or after the facility design ends. This is too late and leads to problems throughout the build and validation project. This must change if manufacturers are to achieve more efficient regulatory compliance. Furthermore, there is often a divide between process development, facility validation, and ongoing facility compliance management, which further compounds the problem. 

Manufacturers must address the following issues to ensure improved compliance:  

Comprehension—industry knowledge of validation is highly variable; it is often not understood how badly validation can be managed and what effect this can have on a business.

Planning—validation is currently planned too late. Successful validation strategies are planned during basic facility design, initiated before a facility is built, and set the stage for proper lifecycle management.

Resources—manufacturers must understand that validating a facility is both time- and cost-intensive.

One new approach to improve compliance is to plan for validation before the facility is designed and to implement a modular validation platform when building a facility. This involves thinking about validation holistically without simply launching into the development of a detailed and comprehensive validation master plan (VMP) from the outset. Manufacturers currently believe that such master plans must be compiled at an early stage. However, this adversely affects a validation project because the VMP is a large, inflexible document that requires constant revisions and rewriting during the course of the facility build, resulting in delayed go-live dates and product manufacturing.  

A modular program sets out broad intentions and observations in high-level policy and master-plan documents that can be readily adapted as the facility design and construction progresses. This allows specific details to be built into the modular plan as the project evolves and provides more efficient compliance with full traceability back to the initial development and user intentions. 

Moving away from traditional approaches to facility validation doesn't involve reinventing the wheel, but will help manufacturers achieve efficient and well-planned validation, allowing greater regulatory compliance; increased standardization of protocols and documents; and better employee appreciation of the processes involved.  

With rising costs, a changing regulatory environment, and the availability of improved approaches to validation and document management, now is the time for manufacturers to review facility validation procedures and establish effective platforms. Implementing a modular approach will accelerate the time it takes to bring a facility online by eliminating unnecessary validation while ensuring that the work required is performed and documented correctly and accurately.  

 is the validation program director at GE Healthcare Services, Piscataway, NJ, 732.457.8056, 

Why the industry needs to review its traditional approach to facility validation

Efficient Compliance Without Re-inventing the Wheel

In recent years, pharmaceutical companies have focused on core competencies and relied on contract research organizations (CROs) to support their analytical and manufacturing-support requirements.   

In today's economic environment, more and more pharmaceutical companies are using the services offered by CROs. Outsourcing analytical services can reduce overheads by circumventing the need to invest in expensive technology and equipment, thus generating cost savings for the company. The CRO can provide expertise using up-to-date technology supported by an extensive knowledge of the current regulations. Outsourcing also can save time, which is often critical because any delay in production processes, batch releases, or obtaining approvals from regulatory bodies can severely damage a company's prospects. 

It is essential that CROs work in close collaboration with their clients, providing smart solutions to their analytical needs,  establishing and transferring methods quickly, and ensuring that information transfer is efficient, secure, and confidential. 

The key attributes that a CRO should have to support fast turnaround of projects are the following:  

experience and a history of successful method transfer

extensive knowledge of the regulatory requirements 

efficient quality systems with requisite documentation in place

flexible approach to incorporate last-minute changes.

If a CRO has these core capabilities and maintains a good relationship with the client, it will be able to successfully establish manufacturing support and batch release methods. 

This article highlights the importance of the CRO–client relationship through a case study, which demonstrates how partnership and support during the project can result in a timely delivery during late-stage development. 

A CRO was approached with an opportunity to develop, validate, and transfer several analytical methods to support its marketing authorizations. The ultimate intention was to use the validated assays for in-process or manufacturing support testing and batch release. The timelines for completing these projects were very aggressive considering that some of the methods required did not exist earlier, although the customer already had the reagents in place. Table 1 lists some of the problems that may arise during contract analysis, and some of the ways to avoid these problems. 

Table 1.  Key elements of a good CROâclient relationship and how to avoid common problems  

The first task was to set up effective lines of communication. At the start of the project, face-to-face meetings were found to be beneficial. However, telephone and video-conferencing facilities also helped during the initial discussions. The remit of the project was understood and agreed, because knowing exactly what the client wanted was essential to provide the best service. The client was asked to provide as much information as possible upfront about the products, processes, supporting analytical methods, aims, and timelines to avoid any surprises later in the collaboration. 

In addition to the technical issues that were discussed, contracts, confidentiality, and technical agreements were rapidly established to document the project's remit and responsibilities. A single point of contact was assigned at each site to facilitate information exchange. Any subsequent agreed contractual changes (amendments) were processed quickly to prevent delays in the project timelines. 

Transferring a pre-existing method (if not defined by a pharmacopeia) or establishing a new method often requires a technical feasibility study or trial run, which allows the CRO to provide a proof of concept of the intended method. The reagents or methods supplied by the customer can be checked and any supplementary consumables or equipment found to be necessary to produce a robust method, considered fit for purpose, can be sourced. This process allows for an assessment of the typical time constraints for performing the testing. If the initial projected timelines appear unrealistic, contract or protocol amendments can be made at this stage.  

If the outcome of the feasibility assessment is favorable, then the data can be securely transferred to the customer for approval, and results may be formally documented in the form of a feasibility report if required. 

It is essential to build and maintain a good working relationship between the client and contract research organization.

BioPharm International-05-01-2009

When Less is More: Lean Can Help Reduce Costs and Improve Compliance Simultaneously

QbD: Convincing the Skeptics

Application of Overall Equipment Effectiveness to Biopharmaceutical Manufacturing

Royalty Interest Investing: Addressing the Out-License Assignability Issue

The Least of Four Evils

Efficient Compliance Without Re-inventing the Wheel

Establishing a Successful CRO–Client Relationship

Declining Market Demand Intensifies Competition

Monitoring of Biopharmaceutical Processes: Present and Future Approaches

Comparative Effectiveness Research to Shape Biotech Studies