Role of Process Capability in Monitoring Product Quality
ASTM defines process capability as the natural or inherent behavior of a stable process that is in a state of statistical control, which is achieved when the process exhibits no detectable patterns or trends (ASTM E2281). Statistical tools, such as control charts, are utilized in the determination of process capability, and capability indices are commonly reported. Conceptually, these indices are the ratio of the range of the tolerance defined by its specifications compared to the range occupied by the inherent variability of the process. Process capability is not a regulatory requirement, but it is a supporting tool that helps organizations understand how a particular process is behaving and, therefore, may be used to support product quality.
1 Introduction
ASTM defines process capability as the natural or inherent behavior of a stable process that is in a state of statistical control, which is achieved when the process exhibits no detectable patterns or trends (ASTM E2281
Statistical Process Control (SPC) is more than control charts alone; it is a comprehensive set of tools that can be used to:
- Understand the process
- Understand the causes of variation
- Eliminate the sources of variation
These tools include histograms, control charts, pareto analysis, cause and effect diagrams, check sheets, scatter plots, and stratification, referred to as quality leader Kaoru Ishikawa’s “magnificent seven.”
The relevance of this to the pharmaceutical industry can be seen in the US FDA Guidance for Industry on Process Validation (2011)
- Understand the sources of variation
- Detect the presence and degree of variation
- Understand the impact of variation on the process and, ultimately, on product attributes
- Control variation in a manner commensurate with the risk it represents to the process/product
Statistical process control has been widely utilized across manufacturing industries for decades. The automotive industry has leveraged such analyses since the 1980s, using SPC to prevent nonconforming product, support continuous improvement initiatives, and communicate areas of risk across the supply chain (Kane, 1986
Industry | Application | Example References |
---|---|---|
Automotive |
| Kane, 1986 |
Environment/Pollution |
| Kahraman, 2009 |
Mineral Processing |
| Ipek, 1999 |
Soap Manufacturing |
| Basu, 2014 |
Machining/Precision Tooling |
| Motorcu, 2006 |
Optical Fiber Networks |
| Lin, 2012 |
Analytical Methods |
| Bouabidi, 2012 |
Contact Lens Manufacturing |
| Young, 1999 |
Nuclear |
| Prasad, 1999 |
In the pharmaceutical industry, the code of federal regulations makes numerous references to expectations on process monitoring and control. 21 CFR Part 211.110
Medical device regulations provide similar attention to monitoring/control. 21 CFR Part 820.75
Given the requirements already observed in the federal regulations, as well as the demonstrated utility of the approach across multiple industries, achieving product robustness through process monitoring (with control charts and capability indices) should be encouraged in the pharmaceutical industry. Yu recently made a similar recommendation, highlighting that capability indices can be a powerful tool from product design through commercial manufacturing. Particularly, capability indices are helpful in understanding more about a product or process, linking critical material attributes to Critical Process Parameters (CPPs)/Critical Quality Attributes (CQAs), and establishing a control strategy (Yu, 2015
- A self-audit of process performance for the setting of business priorities
- A means to identify potential risks to a CQA within a process based on monitoring by experts with relevant experience or training
- With harmonized tool(s) and reported consistently across sites/company
- With easy and meaningful metrics to capture and report
- A mechanism to support acceptable, not unwanted behaviors (i.e., a company culture of continuous improvement)
2 Ways to Measure Capability
Compliance and performance of a process can be interpreted from the same data set, but from very different perspectives with different implications. For example, Figure 2.1 shows a series of tablet hardness measurements plotted against their specifications in blue (from 3 to 9 kp) and centered on 8 kp. Because this is plotted against accept/reject specifications, this data can be interpreted from a compliance perspective. This perspective is focused on verifying that a process is meeting clinically relevant specifications, ultimately ensuring no impact to patient safety.
Figure 2.1: Tablet Hardness Data – A Compliance View of Tablet Press Performance Against Specifications
However, if the same data set is reevaluated based on statistical trend limits (7.998 to 8.012 in red) as shown in Figure 2.2, the picture changes. This tablet press is shown to be highly variable.
Figure 2.2: Tablet Hardness Data – A Performance View of Tablet Press Performance Against Control Limits
Capability is both a matter of perspective and purpose, and is dependent upon how it is defined. Figures 2.1 and 2.2 depict the same data; however, the performance model is meant to proactively show potential problems. Manufacturing with a continuous improvement mindset is always actively searching for potential risks. Failure to control a process at the “performance level” may lead to failure at the “compliance level.” Both perspectives are necessary to control and manage a process.
Figure 2.3 shows the range of process variability relative to specifications for a hypothetical example. The compliance view of variability is defined by the specification range, whereas the theoretical process variability is defined by the statistical trend range (often set at +/- 3 s).
Figure 2.3: Performance and Compliance Views of Process Control
Many approaches to measuring process capability exist. Where some focus on nonconformance—or probability of an Out Of Specification (OOS) — others focus on what proportion conforms to specifications. Common and simple measures of process performance are the capability indices, which compares the process variability to the range allowed by specifications.
Early commentary on process capability defined the concept as an evaluation of “the natural or undisturbed performance (of a process) after extraneous influences are eliminated” (Small, 1956
Figure 2.4: Process Capability and Performance Indices
3 How are product robustness and process capability linked?
Product robustness is defined as the certainty and ability to prove that any product, at any time in any place, from any site or allied manufacturer, is of expected quality and available when/where it is intended. As outlined by Bika (Bika, 2015
A robust process demonstrates acceptable quality and performance while tolerating input variability. A key element of this is applying simple statistical tools such as process capability indices, where variation and risk can be detected and actions can be taken. Such tools can be used to monitor performance across a large portfolio in a concise manner and focus attention to areas in need of improvement. Highly variable attributes (or attributes with low capability indices) are more likely to result in product discard.
In January 2011, the FDA issued a Guidance for Industry on “Process Validation: General Principles and Practices”
Such review of key attributes can be accomplished through tracking and trending data in control charts (evaluating a +/- 3 standard deviation range). Confidence intervals can be applied to capability index calculations to reflect the degree of uncertainty with limited batches. Periodic data reviews by technical subject matter experts will allow for proactive assessment of statistical outliers and prevent future quality events/investigations. For new products, data may be limited, underscoring the particular importance of detailed understanding of special cause variation prior to taking any action.
In the framework of SPC, the purpose of control chart monitoring is to identify special causes of variation, rapidly. These are distinguished from common causes of variation, because the type of action required to reduce special causes of variation is totally different from the action required to reduce common cause variation. Special causes of variation are addressed by searching for the cause immediately, before the trail grows cold. Control charts enable rapid identification of special cause variation to support their elimination from the process. When the overall level of common cause variation is unacceptably high, fundamental improvements such as changes to the process design and control strategy are required.
4 Establishing a Monitoring Plan
In order to evaluate sources of variability in a given process, capability indices should be calculated for selected parameters/attributes and a process monitoring plan should be developed. A process monitoring plan is a list of process parameters that are specific, measureable, controllable, and a driver of the CQAs or release attributes. They can include CPPs, In-Process Controls (IPC), quality control test alert or a physical characteristic; however, this list is not exhaustive. They may also be business drivers including cycle time and yield. The objectives of a monitoring plan are to:
- Evaluate the impact of variability in process inputs such as materials, facility and equipment
- Control variability
- Prioritize resources to minimize risk to the patient
Key elements should include:
- Known robustness/performance issues with manufacturing process and analytical methods
- Outputs from Quality Risk Assessments (QRAs)
- Highlight performance issues during development and scale-up campaigns
- Overview of Annual Product Quality Review findings and action plans
- Development and technology transfer history
Additionally, a review of CQAs, CPPs, Critical Material Attributes (CMAs), Key Process Parameters (KPPs), and other Critical to Quality Parameters identified through a risk assessment should be performed. This analysis should include:
- Control charts
- Capability analyses; Cpk, Ppk values below a predetermined value based upon the level of risk a company is able to take on for a particular parameter or attribute should be evaluated and a plan of improvement established
- For new products, data may be limited; therefore, special cause variation should particularly be highlighted so that risks are clear prior to taking action. As this variation may be new to the product/process, detailed understanding is needed.
- Review of stability data trends for Drug Substance (DS) and Drug Product (DP)
- Trend of performance metrics such as:
- Number of batches manufactured versus rejected
- Complaints (use Pareto analysis as appropriate)
- Recalls
- Number of batches falling outside of control limits
- Analytical robustness (variability or bias issues, sampling concerns)
- Review of excipient and DS properties (e.g., flow, specific surface area, particle size, morphology, bulk density)
Monitoring plans should be periodically reevaluated as new data sets are generated and/or process or product trends are observed. For example, annual reevaluation, or an analysis after 30 lots, allows for identification of any new sources of variability or process shifts. New parameters may be identified for future monitoring. Parameters shown to be in a state of control could be eliminated. A risk based approach can be applied to efficiently identify the right parameters for evaluation.
Ultimately, the establishment of a robust process includes a monitoring plan, comprehensive understanding of a product’s history, risk areas, and inputs, and an analysis of control charts as well as capability indices for critical attributes/parameters.
5 Using Process Capability for Continual Improvement as Internal Audits and Compliance Assessments
As outlined in Yu et al., 2014
Lifecycle Stage | Ppk vs. Cpk | Application |
---|---|---|
Product Design | Ppk | Identification of sources of variability, critical parameters/attributes; Use in establishing control strategy |
Process Scale-up and Qualification | Ppk | Same as above + Process Validation Approach |
Commercial Manufacturing | Ppk or Cpk | Same as above + On-Going Continual Improvement |
ICH Q10
The question of whether or not such indices should play a role as a compliance tool has been actively discussed in the ISPE community. The primary stage in a product life cycle where this could take place is during the commercial manufacturing stage. Product specifications have been set on development and clinical data (e.g. efficacy and safety), which is of the utmost importance from a compliance perspective. Per ICH Q10
Continuous improvement is an expectation throughout industry, and is made easier through the use of simple statistical tools such as capability/performance indices, enabling evaluation of performance across multiple products to enable corrective actions to be taken. However, these indices are not the definitive answer as to the state of a company’s control of a particular product or process. As highlighted in Section 3, process robustness (of which capability/performance indices play an essential role in) is just one element of an overall product robustness strategy that encompasses supplier, equipment, and distribution functional areas as well, in addition to key enablers such as people, business processes, and technology.
The goal of developing a robust process is linked to understanding and continual improvement, driven through internal reviews and audits (leveraging tools such as capability indices). The very nature of internal audits is believed to be excluded from the scrutiny of regulatory inspections, as noted in the US FDA’s Compliance Policy Guide (CPG 7151.02)
It is important to note that many specifications in biopharmaceutical manufacturing are derived from actual process data, especially when unit operations are not considered “well characterized.” However, this reliance on process data can be replaced as additional manufacturing, safety, and clinical data becomes available. As specifications are developed, clinical relevance and meeting patient safety/efficacy requirements must remain the highest priority. Process monitoring and continual improvement should be leveraged to ensure a robust process, and clinical data should continue to be utilized to establish specifications.
6 Challenges and Limitations of Capability Indices in Pharmaceutical Manufacturing
Process capability informs as to the level of risk a particular attribute or parameter poses to a process routinely meeting specifications. Other quality metrics to routinely monitor that have also been discussed in the community include:
- Batch Failure Rate
- Right First Time Rate
- Confirmed OOS Rate
Each metric has a place in furthering the objective of establishing a highly capable and robust process. However, each company has a different definition of what the appropriate metric should be given the level of risk they are willing to take for a specific attribute or parameter. Establishing a generic Cpk requirement may not be directly applicable to all products and processes. For example, certain parameters may have specifications based off of compendial requirements or clinical experience. Requiring variation from specification to be within a pre-set number of standard deviations may not be feasible in these instances, and could limit release of product to the market if mandated. Continuous improvement opportunities, however, can try over time to address these areas of risk, which ultimately leads to regulatory compliance. Regardless of the tool used, industry is encouraged to leverage all statistical analyses available to understand risks and proactively remediate. With this approach, drug shortages may continue to be averted. Additionally, harmonization between regulatory bodies to have a global specification for products will reduce significant burden to the industry.
7 Future Directions
Establishing process monitoring plans which incorporate an evaluation of process capability for critical parameters/attributes is an essential part of building a robust process. Process capability indices can be an extremely valuable, simple tool to help identify process improvement opportunities. However, monitoring process capability is just one piece of a company’s overall product robustness effort; therefore, it is not a definitive metric indicative of a product’s state of control.
Capability assessments are recommended as a tool to enhance efficiency and process monitoring. Smaller companies may be limited in the extent of analysis capabilities. However, the means to develop and strengthen such tools, regardless of company size or location, is essential for industry to continue to grow and avert drug shortages. As discussed, process monitoring is an essential part in identifying continuous improvement opportunities and enabling an improvement culture, which ultimately leads to regulatory compliance. Companies should be encouraged to require such programs to ensure robust processes. However, how one achieves this goal may vary and depend on the circumstances of the products/processes manufactured. This is similar to how industry approaches the topic of process validation. Process validation is a requirement, but how a company approaches and prepares can vary. While the prevalence of process monitoring/capability assessments across industry are behind CPV and other forms of monitoring/risk assessment, capability/performance indices are most meaningful as a tool to proactively identify risk of OOS results. Understanding risks enables longer term, proactive improvement, separate from an individual batch release process.
Companies should continue to be encouraged to use statistical tools in appropriate situations, as part of an overall product robustness effort. ISPE’s Quality Metrics Pilot Program
9 Acronyms
CMA | Critical Material Attribute |
CPP | Critical Process Parameter |
CQA | Critical Quality Attribute |
DP | Drug Product |
DS | Drug Substance |
IPC | In-Process Control |
KPP | Key Process Parameter |
OOS | Out Of Specification |
PQLI® | Product Quality Lifecycle Implementation® |
PV | Process Validation |
QRA | Quality Risk Assessment |
SPC | Statistical Process Control |
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Acknowledgements
This Concept Paper was written and reviewed by members of the Process Capability Team and was supported by the Product Quality Lifecycle Implementation (PQLI®) Technical Committee.
Authors
Abizer I. Harianawala, Ariad, USA
Peter G. Millili*, Bristol-Myers Squibb, USA
Julia O’Neill, Tunnell Consulting, USA
Kevin Roberson, EAG Laboratories, USA
*Please send comments to peter.millili@bms.com.