by Stéphanie Peika
(Editor’s note: This is the first half of a two-part article series that focuses on quality risk management in the pharmaceutical industry.)
“Quality by design” is a new term in the pharmaceutical industry. When a company chooses to apply this new system to a quality risk management process that’s linked to an appropriate pharmaceutical quality system, it creates opportunities to enhance science-based and risk-based regulatory and auditing approaches.
Pharmaceutical development is an important part of the product life cycle, and quality by design (QbD) is applied this stage. It requires the development of a design space, which must be audited as part of compliance strategies during development, but also during the product’s life cycle to ensure compliance and to continually evaluate the relevance of the current design space.
In this two-part article, I will discuss definitions and applications of QbD in the pharmaceutical context—as defined by the International Conference for Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH)— look at how QbD is different from the current approach, and outline strategies for implementing effective auditing methods for QbD while remaining within the prescribed standards of ICH guidelines Q8 (pharmaceutical development), Q9 (quality risk management), and Q10 (pharmaceutical quality systems).
QbD as a new paradigm, pharma-style
Pharmaceutical companies and their regulators currently face increasing external requirements, costs, and a growing complexity and scope of risks. Empowerment and flexibility are needed to master this complexity and streamline decision making. It allows proactive disclosure to build trust and understanding, as well as improved communication through sharing best practices and science-based knowledge and helps overworked companies convert data into knowledge.
This paradigm has incremental steps, as shown in table 1.
Table 1: Pharmaceutical QbD: ICH, past and present
|Pharmaceutical Development (ICH Q8)|
|Data transferVariable output||Knowledge transferScience-basedConsistent output|
|Quality Risk Management (ICH Q9)|
|Used, however poorly defined||Opportunity to use structured process thinking|
|Pharmaceutical Quality Systems (ICH Q10)|
|GMP Checklist||Quality systems across product lifecycle|
Pharmaceutical companies have lagged behind other industries in adopting structured risk management into their quality management systems. For example, medical device organizations reference ISO 14971 and ISO 13485 and the food industry uses hazard analysis and critical control points (HACCP). Pharmaceutical organizations’ implementation of quality risk management techniques has been patchy, leaving a lot of room for improvement. At its best, quality risk management should reflect systematic processes for the assessment, control, communication, and review of risks to the quality of a drug product across its life cycle.
QbD is a “systematic approach to development that begins with predefined objectives and emphasizes product and process understanding and process control, based on sound science and quality risk management.” A “systematic approach” to product development can include incorporation of prior knowledge, results of studies using design of experiments, use of quality risk management, and use of knowledge management throughout a product’s life cycle. Such an approach can enhance the quality assurance process and help regulators and auditors better understand a company’s strategy. Product and process understanding can be updated with the knowledge gained over the product’s life cycle.
Each step in the QbD paradigm is directly linked with patient well-being. The QbD product life cycle has many opportunities to improve patient health through the application of ICH principles. Creating the design space required by ICH Q8 and implementing the appropriate pharmaceutical quality systems as defined in ICH Q10, risk management, mitigation, and reduction protects patients’ well-being and health.
The idea behind the ICH Qs discussed here is to manage patient risk based on sound scientific knowledge:
- Knowledge of the product, the process, and the facilities
- Robustness of the quality system
- Application of relevant controls to assess and mitigate risk
The pharmaceutical industry’s adoption of the ICH Q8, Q9, and Q10 standards represents a step into the future, as the standard’s interpretation of development and life cycle management aligns with broad quality applications. Table 2 outlines how this paradigm is evolving with 21st-century quality and risk-management thinking.
Table 2: Pharmaceutical QbD: Past vision becomes present fact
|Old Approach||New Approach||Remarks|
|Broad Concept||Quality decisions divorced from science and risk evaluation.||Quality decisions based on process understanding and risk management (quality by design)||Design space concept introduced to integrate process knowledge with regulatory evaluation|
|Quality||Post-factum sampling and quality testing; process validation||Management of variability; process controls focused on critical attributes – continuous quality verification||Quality by design definition applied; measure critical process parameters to control output product quality|
|Systems||Systems designed to inhibit changes and minimize business risks. Discourages improvement and innovation||Changes managed within company’s quality system; real-time batch release feasible||Regulators and industry place higher reliance / trust / understanding on systems; multidisciplinary evaluation and decision-making|
|Regulatory||Compliance focus: changes require prior approval||Regulatory scrutiny adjusted to level of process understanding; continuous improvement allowed within design space||Requires mechanisms to communicate process understanding data (“inspectable rather than reviewable”)|
Pharmaceutical QbD: The paradigm in action
The mantra of quality professionals is that “Quality cannot be tested into products; it should be built in by design.” For pharmaceutical organizations, the concept of QbD is applied during the product development stage. The aim of pharmaceutical development is to design a quality product and for its manufacturing process to consistently deliver the product’s intended performance. The information and knowledge gained from product-development studies and the resulting manufacturing experience provide scientific understanding to support the establishment of the design space, specifications, and manufacturing controls. This information can be a basis for quality risk management.
Changes in formulation and manufacturing processes during development and life cycle management are great opportunities to gain additional knowledge and further support the definition of the design space. Similarly, inclusion of relevant knowledge gained from experiments giving unexpected results can also be useful.
Companies involved in pharmaceutical product development are responsible for proposing the design space, which is subject to regulatory assessment and approval. Thereafter, working within the design space is not considered as a change. However, scientific understanding facilitates establishment of an expanded design space, which promotes a more flexible design approach.
To realize this flexibility, it’s important to demonstrate an enhanced knowledge of product performance over a range of material attributes, manufacturing process options, and process parameters. This understanding can be gained by application of formal experimental designs, process analytical technology (PAT), and/or prior knowledge. Appropriate use of quality risk management principles can be helpful in prioritizing the additional pharmaceutical development studies to collect such knowledge.
Finally, the design space
The linkage between the process inputs (input variables and process parameters) and the critical quality attributes can be described in the design space.
Selection of variables
The risk assessment and process development experiments can not only lead to an understanding of the linkage and effect of process inputs on product critical quality attributes (CQA); but they also help identify variables and the ranges within which consistent quality can be achieved. These input variables can thus be selected for inclusion in the design space.
An input variable or process parameter need not be included in the design space if it has no effect on delivering CQAs when the input variable or parameter is varied over the full potential range of operation. The control of these variables would be under good manufacturing practices (GMP).
Defining and describing a design space
A design space can be defined in terms of ranges of input variables or parameters or through more complex mathematical relationships. It’s possible to define a design space as a time-dependent function (e.g., temperature and pressure cycle of a lyophilisation cycle), or as a combination of variables such as principal components of a multivariate model. Scaling factors can also be included if the design space is intended to span multiple operational scales. Analysis of historical data can provide the basis for establishing a design space. Regardless of how a design space is developed, it’s expected that operation within the design space will result in a product meeting the defined quality attributes.
Design space vs. proven acceptable ranges
A combination of proven acceptable ranges doesn’t constitute a design space. However, proven acceptable ranges based on univariate experimentation can provide some knowledge about the process.
Design space and edge of failure
Although it can be helpful to know where the edges of failure could be or to determine potential failure modes, it’s not an essential part of establishing a design space.
Risk assessment: QbD and beyond
Risk assessment is a valuable scientific process used in quality risk management that can help identify which material attributes and process parameters have an effect on product CQAs. This risk assessment is typically performed early in a pharmaceutical development process, it can be helpful to repeat the risk assessment as information and greater knowledge become available.
Quality risk management is a systematic process for the assessment, control, communication, and review of risks to the quality of a drug product across its life cycle. Decisions can occur at any point in the process. These decisions might be to return to the previous step and seek further information, to adjust the risk models or even to terminate the risk management process based upon information that supports such a decision. Note: “unacceptable” in the flowchart does not only refer to statutory, legislative or regulatory requirements, but also to the need to revisit the risk assessment process.
Risk assessment tools can be used to identify and rank parameters (e.g., operational, equipment, input material) that could affect product quality based on prior knowledge and initial experimental data. The initial list of potential parameters can be quite extensive, but it will narrow as process understanding increases. The list can be refined further through experimentation to determine the significance of individual variables and potential interactions. Once the significant parameters are identified, they can be further studied through a combination of design of experiments, mathematical models, or studies that lead to mechanistic understanding.
The robustness of the data set in risk assessment is important because it determines the quality of the output. Revealing assumptions and reasonable sources of uncertainty will enhance confidence in this output and/or help identify its limitations. Uncertainty is due to combination of incomplete knowledge about a process and its expected or unexpected variability. Typical sources of uncertainty include gaps in knowledge gaps in pharmaceutical science and process understanding, sources of harm (e.g., failure modes of a process and sources of variability), and probability of detection of problems.
Risk communication is the sharing of information about risk and risk management between the decision makers and others. Parties can communicate at any stage of the risk management process. The output/result of the quality risk management process should be appropriately communicated and documented. Communications might include those among interested parties; e.g., regulators and industry, industry and the patient, or within a company, industry, or regulatory authority, etc. The included information might relate to the existence, nature, form, probability, severity, acceptability, control, treatment, detectability, or other aspects of quality risks. Communication need not be performed for each and every risk acceptance. Between the industry and regulatory authorities, communication concerning quality risk management decisions might be effected through existing channels as specified in regulations and standardized guidance.
Risk management should be an ongoing part of the quality management process. A mechanism to review or monitor events should be implemented. The output/results of the risk management process should be reviewed for new knowledge and experiences. Once a quality risk management process has been initiated, it should continue to be utilized for events that might effect the original quality risk management decision, whether these events are planned (e.g., results of product review, inspections, audits, change control) or unplanned (e.g., root cause from failure investigations, recall). The frequency of any review should be based upon the level of risk. Risk review might include reconsideration of risk acceptance decisions.
Risk management methodology
Quality risk management supports a scientific and practical approach to decision making. It provides documented, transparent, and reproducible methods to accomplish steps of the quality risk management process based on current knowledge about assessing the probability, severity, and sometimes detectability of the risk.
Traditionally, quality risks have been assessed and managed in a variety of informal ways based on compilation of observations, trends, and other information. Such approaches continue to provide useful information that might support topics such as handling of complaints, quality defects, deviations, and allocation of resources.
Additionally, the pharmaceutical industry and regulators can assess and manage risk using recognized risk management tools and/or internal procedures (e.g., standard operating procedures). Below is a list of some of these tools:
- Basic risk management facilitation methods (flowcharts and checksheets)
- Failure mode and effects analysis
- Failure mode, effects, and criticality analysis
- Fault tree analysis
- Hazard analysis and critical control points
- Hazard operability analysis
- Preliminary hazard analysis
- Risk ranking and filtering
- Supporting statistical tools
It might be appropriate to adapt these tools for use in specific areas pertaining to drug product quality. Quality risk management methods and their supporting statistical tools can be used together, which provides flexibility that can facilitate the application of quality risk management principles.
The degree of rigor and formality of quality risk management should reflect available knowledge and align with the complexity and/or criticality of the issue to be addressed.
Integration of quality risk management into industry and regulatory operations
Quality risk management is a process that supports science-based and practical decisions when integrated into quality systems. Appropriate use of quality risk management doesn’t obviate industry’s obligation to comply with regulatory requirements. However, effective quality risk management can facilitate better and more informed decisions, provide regulators with greater assurance of a company’s ability to deal with potential risks, and might affect the extent and level of direct regulatory oversight. In addition, quality risk management can facilitate better use of resources by all parties.
Training of industry and regulatory personnel in quality risk management processes provides for greater understanding of decision-making processes and builds confidence in outcomes. Quality risk management should be integrated into existing operations and documented appropriately. ICH Q8, Q9, and Q10 provide excellent guidance for this integration.
So really, what’s the difference?
The traditional “quality by end-product testing” approach is completely dependent on end-product testing before product release. The variables exist in the product specifications; if they aren’t met, there is very little leeway for correction or improvement.
The QbD approach allows for the introduction of measurables during the process to ensure that the product always meets its specifications. This approach is based on product characteristic and process understanding, along with appropriate risk management efforts to minimize at most the variations during manufacturing.
The second half of this two-part article series appears in the November–December 2010 issue of The Auditor.
About the author
Stéphanie Peika is an ASQ certified quality auditor and a certified manager of quality and operational excellence. She is associate director of quality systems at Paladin Labs Inc., a Montreal-based pharmaceutical company.
Tags: pharmaceutical quality system, QbD, quality by design, risk management.