Srinivas S. Dagalur

The healthcare industry lags significantly behind the electronic, chemical, and automotive industries in process quality. Process sigma in healthcare is around 2.0 (achieving success about 85% of the time), while other industries' process sigma is as high as 6 or 7 (achieving success more than 99.9999% of the time). Healthcare companies have relied on inspecting quality into the products at enormous cost, yet defective product still finds its way into the marketplace too frequently. Because newer devices and pharmaceuticals are becoming more complex, it is a mathematical certainty that 2-sigma manufacturing processes will fail. 

The healthcare industry argues that process-improvement efforts are hampered by regulations and that they must spend as much as 50% of each improvement program on validation. These claims are true, but new regulations allow manufacturing processes to be validated according to a science-based mechanistic understanding of process control. Once this validation is accomplished, the requirement for  ongoing validation efforts is greatly reduced. Ongoing process-improvement efforts can proceed with minimal revalidation. 

The US Food and Drug Administration is actively encouraging manufacturers to adopt process analytical technology (PAT) and quality by design (QbD). Both strategies require a process-control management method and a technical infrastructure for ongoing operations. 

Enterprise process control and management (EPCAM) is a strategy for achieving this increase in process understanding. EPCAM is a macromanagement process executed through an integrated information solution and supported by associated systems and data, including machine-process controls through programmable logic controls (PLCs), supervisory control and data-acquisition systems (SCADA), manufacturing execution systems (MES), middleware, statistical process control (SPC), laboratory information management systems (LIMS), adaptive process control (APC), and fault detection and classification (FDC). EPCAM uses Six Sigma as the fundamental macro management process to supervise manufacturing-process control across the entire value chain for any given element, including raw materials, suppliers, and subcontractors. 

EPCAM has largely been overlooked for three major reasons. First, process control is typically executed manually and is primarily focused on stand-alone unit operations. Second, data integration across operations is lacking. Third, the software to draw the relationships between process parameters and product attributes is not widely known or commercially available. Some examples of these issues include the following:  

Large automated equipment trains have their own control systems

Manufacturing is typically split into functional areas such as raw-material preparation, mixing, compression, machining, coating, and sterilizing, with control autonomy in each area

Control remains focused on an operation-by-operation basis versus an end-to-end, product end-state outcome view

Manufacturing uses specialized control systems that addresses specific needs

Process knowledge is kept by the worker and may not be documented or shared among peers

Product test data (percent active, color, tablet hardness, and weight) reside in systems such as LIMS, while process data may be held in an MES or recorded manually.

The requirements of manufacturing in the regulated life-sciences and healthcare environments often necessitate that manufacturing-process improvement take second priority to validation and responding to nonconformances. As a result, process control in many manufacturing operations is not well understood. 

Many companies turn to Six Sigma as the preferred method for process improvement, then apply it problem by problem. Six Sigma is well suited for improving business processes following the methodology of define, measure, analyze, improve, and control (DMAIC). The problem with most DMAIC efforts is the amount of time and resources needed to collect the relevant process data and analyze them with the corresponding product data. 

For example, a plant site of about 350 people adopted the Six Sigma process hierarchy with the intention of continually improving the Sigma of the critical processes and the overall process. The idea was sound, but significant practical problems derailed the implementation. The first problem was that the effort required about 30 full-time employees to track and maintain the data. The second problem was uncertainty about what to do with 10,000 SPC charts after they had been gathered. 

EPCAM solves this process-execution and data-management problem by:  

Establishing DMAIC as the macro process-control management method across the enterprise

Integrating process and product data through DMAIC. The data are collected to enable the correlation of process parameters to product attributes. This technique eliminates the considerable manual effort required by a typical DMAIC project of data collection and analysis.

Providing the adaptive process-control applications that analyze product and process data, correlate the data, and optimize performance. This step provides a mechanistic process understanding.

Providing the automation to run operations based upon the above process understanding in real time.

Identifying process variations early and determining the optimum parameters throughout an entire process chain, as opposed to focusing on a single operation.

Thus, EPCAM allows process control to be executed across the enterprise in an efficient, reliable, and effective manner. 

EPCAM can be achieved in a controlled, phased approach. There are five logical levels or phases in moving from the typical environment to the EPCAM end state. 

The fifth and lowest level is the automation of the batch record (i.e., electronic batch records). The fourth level is MES. The third level is point-to-point process control using PAT. The second level is adaptive process control (APC), which links process control across multiple operations. The first and highest level is FDC, which enables control of processes and the environment. These levels will be explained in more detail in the "EPCAM solution and value" section. Achieving EPCAM can seem like a daunting journey, but the process can be completed in steps, building the organizational capability and trust required along the way. 

The typical manufacturing environment in a life-sciences or healthcare company 

Figure 1 depicts the current and desired states of most manufacturers in the life-science and healthcare industries. 

Traditionally, supply chains in the pharmaceutical industry have not been expected to be efficient. They have merely been expected not to cause problems. In general, the industry's margins have been sufficiently high, and lost sales received more attention than inventory control. Because the industry is regulated, making a significant process change often requires revalidation. Compliance and responding to nonconformances have always been the first priorities from a process perspective. 

As a result, process quality today in healthcare is about 2 sigma, and process capability is around 1. Many processes are less than 1 sigma, and the cost to serve is relatively high. EPCAM provides the opportunity to improve process quality, process capability, and cost to serve. EPCAM goals for the pharmaceutical industry are levels of at least 4 sigma for the manufacturing processes and process-capability (CpK) of critical operations of 2.5 sigma. 

It would be disastrous for product of 2-sigma quality to be released to patients. Recalls would be extensive, adverse events would abound, the industry would lose credibility, and patients would be at increased risk. For this reason, the industry has instituted robust inspection processes that raise product quality to approximately 6 sigma (see Figure 1). Most companies continue to invest in inspection to improve quality even more (see the short red arrow in Figure 1).  

Figure 1: The business case for enterprise process control and management (EPCAM). (AUTHORS) 

The authors believe, however, that the right course is to invest in improving process sigma and process capability (see the long red arrow in Figure 1) while keeping the inspection capability constant. Thus, product quality for the patient would increase to 7 sigma and attain the benefits of lowered cost and reliable supply. The volume under the curve in Figure 1 can be used as a relative indicator of the cost of quality. 

Many developments in the industry indicate that this is the proper course:  

Products are becoming more complex. Supply chains that remain at a low process sigma and low process capability would result in high yield losses, unreliable supply, and increased likelihood that out-of-specification product reaches the patient. Product complexity comes in the form of biologic drugs, drug–device combinations, and time-released products.

FDA is encouraging improved process control and acknowledging that some of its regulations have been obstacles to this goal. The agency is encouraging manufacturers to adopt PAT and decreasing approval times for new products filed with this type of process control.

Mapping the human genome means that the ability to determine drug efficacy based upon genetic makeup will decrease the number of blockbuster drugs. Industry supply chains will need to make more products at lower volumes. Process capabilities must improve for companies to efficiently produce this mix of products.

Because products' complexity is increasing and their side effects are growing more acute, the industry and FDA are becoming increasingly concerned about spikes in dosing. These concerns are inspiring the development of active delivery mechanisms that increase the demands on the supply chain's process capability.

Improving process capability significantly can be a daunting task, but current technologies make this project more feasible and faster to complete. In the past, regulators' conservative approach discouraged innovation, but today they are willing to assist and encourage transformation. This support is based on the belief that increased scientific understanding and applied technologies reduce variation and risk. 

EPCAM integrates information through a combination of open applications, integration software, and adaptive process-control software. Integrated information enables the macro management process to improve manufacturing processes. The following results occur when EPCAM is fully implemented in both manufacturing and product-development environments:  

CpK improves from the typical level of 0.7–1 to > 2

Process sigma improves from roughly 2 to about 4.5

Costs of compliance and nonconformances decrease sharply, and the possibility of recalls is greatly minimized 

The reliability and speed of new product launches are greatly improved

Many EPCAM software components support open standards and are not proprietary. EPCAM works with most installations of commercially available software (MES, ERP, and LIMS). Two proprietary applications, APC and FDC, will be discussed in more detail. Companies want to achieve the level of quality that EPCAM process control failitates, but they are uncertain about how to make the transition from the current environment to the targeted EPCAM end state. To make this change, the authors have developed a phased approach that progresses through five logical levels of control (see Table I). 

The achievement of each level improves quality and control and leads to business benefits such as greater yields and better products. In addition, organizational capability (e.g., process skills, experimentation skills, the number of experienced people) grows with the attainment of each level. When companies reach levels 4 and 5, their organizational capability and process-control skills must keep pace with their technological advancement. It is absolutely critical to build the organization's process-control expertise, discipline, and the culture of control in both the manufacturing, product-development, and information-technology organizations as progress is made. 

Table II: Transformation demands from the current state to the desired state using EPCAM. 

Level 5 is the level of electronic batch records. At this level, the management of manufacturing control is improved by typically linking it to ERP and LIMS electronically. This link guards against mistakes in manual transcription. Conformance to standard operating procedures (SOPs) is increased. Better conformance reduces paperwork errors, which, in turn, ensures that correct manufacturing sequences are followed and reduces manufacturing mistakes. Paperwork is also reduced at this level, and nonconformances resulting from paperwork are significantly reduced. Process capability, however, typically does not improve, and process sigma improves only slightly. This level is a good stage at which to introduce technology to the shop floor, gain experience within operations, and reconcile and improve data. 

MES characterizes Level 4. This level provides automated machine instructions that establish the process parameters in which the equipment operates. MES typically links ERP directly to the shop floor. This link reduces operator and transcription errors. Processes are standardized, and operating conditions are measured and recorded. SCADA regulatory requirements are satisfied. Messages automatically alert operators to out-of-specification operating conditions. Quality and compliance are increased by additional standardization and mistake-proofing. At this level, process capability may increase slightly if the process parameters correlated to product attributes are known. Even if this is not the immediate result, the standardization of MES provides the controlled environment that enables future process improvement. 

Level 3 is marked by point-to-point process control. This level of automated process control allows users to modify product attributes by adjusting process parameters. For example, the amount of active/in.

  in a layer (patch) to be applied to a substrate may be controlled by adjusting the line speed of the coating operation. The thickness of the layer is measured after coating, and the line speed may be increased or decreased to achieve the targeted thickness. This control is an example of PAT that FDA has been encouraging during the past several years. At this level, process capability is increased for the selected operation raising it to more than 1.0 sigma. This measurement means that, most of the time, the product will be made within specification but will vary within the specifications. Quality and compliance increase, thus providing significant business results such as improved yields, reduced waste, increased capacity, and fewer errors. 

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