Control Strategies

In a past post discussing the program level in the document hierarchy, I outlined how program documents serve as critical connective tissue between high-level policies and detailed procedures. Today, I’ll explore three distinct but related approaches to control strategies: the Annex 1 Contamination Control Strategy (CCS), the ICH Q8 Process Control Strategy, and a Technology Platform Control Strategy. Understanding their differences and relationships allows us to establish a comprehensive quality system in pharmaceutical manufacturing, especially as regulatory requirements continue to evolve and emphasize more scientific, risk-based approaches to quality management.

Control strategies have evolved significantly and are increasingly central to pharmaceutical quality management. As I noted in my previous article, program documents create an essential mapping between requirements and execution, demonstrating the design thinking that underpins our quality processes. Control strategies exemplify this concept, providing comprehensive frameworks that ensure consistent product quality through scientific understanding and risk management.

The pharmaceutical industry has gradually shifted from reactive quality testing to proactive quality design. This evolution mirrors the maturation of our document hierarchies, with control strategies occupying that critical program-level space between overarching quality policies and detailed operational procedures. They serve as the blueprint for how quality will be achieved, maintained, and improved throughout a product’s lifecycle.

This evolution has been accelerated by increasing regulatory scrutiny, particularly following numerous drug recalls and contamination events resulting in significant financial losses for pharmaceutical companies.

Annex 1 Contamination Control Strategy: A Facility-Focused Approach

The Annex 1 Contamination Control Strategy represents a comprehensive, facility-focused approach to preventing chemical, physical and microbial contamination in pharmaceutical manufacturing environments. The CCS takes a holistic view of the entire manufacturing facility rather than focusing on individual products or processes.

A properly implemented CCS requires a dedicated cross-functional team representing technical knowledge from production, engineering, maintenance, quality control, microbiology, and quality assurance. This team must systematically identify contamination risks throughout the facility, develop mitigating controls, and establish monitoring systems that provide early detection of potential issues. The CCS must be scientifically formulated and tailored specifically for each manufacturing facility’s unique characteristics and risks.

What distinguishes the Annex 1 CCS is its infrastructural approach to Quality Risk Management. Rather than focusing solely on product attributes or process parameters, it examines how facility design, environmental controls, personnel practices, material flow, and equipment operate collectively to prevent contamination. The CCS process involves continual identification, scientific evaluation, and effective control of potential contamination risks to product quality.

Critical Factors in Developing an Annex 1 CCS

The development of an effective CCS involves several critical considerations. According to industry experts, these include identifying the specific types of contaminants that pose a risk, implementing appropriate detection methods, and comprehensively understanding the potential sources of contamination. Additionally, evaluating the risk of contamination and developing effective strategies to control and minimize such risks are indispensable components of an efficient contamination control system.

When implementing a CCS, facilities should first determine their critical control points. Annex 1 highlights the importance of considering both plant design and processes when developing a CCS. The strategy should incorporate a monitoring and ongoing review system to identify potential lapses in the aseptic environment and contamination points in the facility. This continuous assessment approach ensures that contamination risks are promptly identified and addressed before they impact product quality.

ICH Q8 Process Control Strategy: The Quality by Design Paradigm

While the Annex 1 CCS focuses on facility-wide contamination prevention, the ICH Q8 Process Control Strategy takes a product-centric approach rooted in Quality by Design (QbD) principles. The ICH Q8(R2) guideline introduces control strategy as “a planned set of controls derived from current product and process understanding that ensures process performance and product quality”. This approach emphasizes designing quality into products rather than relying on final testing to detect issues.

The ICH Q8 guideline outlines a set of key principles that form the foundation of an effective process control strategy. At its core is pharmaceutical development, which involves a comprehensive understanding of the product and its manufacturing process, along with identifying critical quality attributes (CQAs) that impact product safety and efficacy. Risk assessment plays a crucial role in prioritizing efforts and resources to address potential issues that could affect product quality.

The development of an ICH Q8 control strategy follows a systematic sequence: defining the Quality Target Product Profile (QTPP), identifying Critical Quality Attributes (CQAs), determining Critical Process Parameters (CPPs) and Critical Material Attributes (CMAs), and establishing appropriate control methods. This scientific framework enables manufacturers to understand how material attributes and process parameters affect product quality, allowing for more informed decision-making and process optimization.

Design Space and Lifecycle Approach

A unique aspect of the ICH Q8 control strategy is the concept of “design space,” which represents a range of process parameters within which the product will consistently meet desired quality attributes. Developing and demonstrating a design space provides flexibility in manufacturing without compromising product quality. This approach allows manufacturers to make adjustments within the established parameters without triggering regulatory review, thus enabling continuous improvement while maintaining compliance.

What makes the ICH Q8 control strategy distinct is its dynamic, lifecycle-oriented nature. The guideline encourages a lifecycle approach to product development and manufacturing, where continuous improvement and monitoring are carried out throughout the product’s lifecycle, from development to post-approval. This approach creates a feedback-feedforward “controls hub” that integrates risk management, knowledge management, and continuous improvement throughout the product lifecycle.

Technology Platform Control Strategies: Leveraging Prior Knowledge

As pharmaceutical development becomes increasingly complex, particularly in emerging fields like cell and gene therapies, technology platform control strategies offer an approach that leverages prior knowledge and standardized processes to accelerate development while maintaining quality standards. Unlike product-specific control strategies, platform strategies establish common processes, parameters, and controls that can be applied across multiple products sharing similar characteristics or manufacturing approaches.

The importance of maintaining state-of-the-art technology platforms has been highlighted in recent regulatory actions. A January 2025 FDA Warning Letter to Sanofi, concerning a facility that had previously won the ISPE’s Facility of the Year award in 2020, emphasized the requirement for “timely technological upgrades to equipment/facility infrastructure”. This regulatory focus underscores that even relatively new facilities must continually evolve their technological capabilities to maintain compliance and product quality.

Developing a Comprehensive Technology Platform Roadmap

A robust technology platform control strategy requires a well-structured technology roadmap that anticipates both regulatory expectations and technological advancements. According to recent industry guidance, this roadmap should include several key components:

At its foundation, regular assessment protocols are essential. Organizations should conduct comprehensive annual evaluations of platform technologies, examining equipment performance metrics, deviations associated with the platform, and emerging industry standards that might necessitate upgrades. These assessments should be integrated with Facility and Utility Systems Effectiveness (FUSE) metrics and evaluated through structured quality governance processes.

The technology roadmap must also incorporate systematic methods for monitoring industry trends. This external vigilance ensures platform technologies remain current with evolving expectations and capabilities.

Risk-based prioritization forms another critical element of the platform roadmap. By utilizing living risk assessments, organizations can identify emerging issues and prioritize platform upgrades based on their potential impact on product quality and patient safety. These assessments should represent the evolution of the original risk management that established the platform, creating a continuous thread of risk evaluation throughout the platform’s lifecycle.

Implementation and Verification of Platform Technologies

Successful implementation of platform technologies requires robust change management procedures. These should include detailed documentation of proposed platform modifications, impact assessments on product quality across the portfolio, appropriate verification activities, and comprehensive training programs. This structured approach ensures that platform changes are implemented systematically with full consideration of their potential implications.

Verification activities for platform technologies must be particularly thorough, given their application across multiple products. The commissioning, qualification, and validation activities should demonstrate not only that platform components meet predetermined specifications but also that they maintain their intended performance across the range of products they support. This verification must consider the variability in product-specific requirements while confirming the platform’s core capabilities.

Continuous monitoring represents the final essential element of platform control strategies. By implementing ongoing verification protocols aligned with Stage 3 of the FDA’s process validation model, organizations can ensure that platform technologies remain in a state of control during routine commercial manufacture. This monitoring should anticipate and prevent issues, detect unplanned deviations, and identify opportunities for platform optimization.

Leveraging Advanced Technologies in Platform Strategies

Modern technology platforms increasingly incorporate advanced capabilities that enhance their flexibility and performance. Single-Use Systems (SUS) reduce cleaning and validation requirements while improving platform adaptability across products. Modern Microbial Methods (MMM) offer advantages over traditional culture-based approaches in monitoring platform performance. Process Analytical Technology (PAT) enables real-time monitoring and control, enhancing product quality and process understanding across the platform. Data analytics and artificial intelligence tools identify trends, predict maintenance needs, and optimize processes across the product portfolio.

The implementation of these advanced technologies within platform strategies creates significant opportunities for standardization, knowledge transfer, and continuous improvement. By establishing common technological foundations that can be applied across multiple products, organizations can accelerate development timelines, reduce validation burdens, and focus resources on understanding the unique aspects of each product while maintaining a robust quality foundation.

How Control Strategies Tie Together Design, Qualification/Validation, and Risk Management

Control strategies serve as the central nexus connecting design, qualification/validation, and risk management in a comprehensive quality framework. This integration is not merely beneficial but essential for ensuring product quality while optimizing resources. A well-structured control strategy creates a coherent narrative from initial concept through on-going production, ensuring that design intentions are preserved through qualification activities and ongoing risk management.

During the design phase, scientific understanding of product and process informs the development of the control strategy. This strategy then guides what must be qualified and validated and to what extent. Rather than validating everything (which adds cost without necessarily improving quality), the control strategy directs validation resources toward aspects most critical to product quality.

The relationship works in both directions—design decisions influence what will require validation, while validation capabilities and constraints may inform design choices. For example, a process designed with robust, well-understood parameters may require less extensive validation than one operating at the edge of its performance envelope. The control strategy documents this relationship, providing scientific justification for validation decisions based on product and process understanding.

Risk management principles are foundational to modern control strategies, informing both design decisions and priorities. A systematic risk assessment approach helps identify which aspects of a process or facility pose the greatest potential impact on product quality and patient safety. The control strategy then incorporates appropriate controls and monitoring systems for these high-risk elements, ensuring that validation efforts are proportionate to risk levels.

The Feedback-Feedforward Mechanism

One of the most powerful aspects of an integrated control strategy is its ability to function as what experts call a feedback-feedforward controls hub. As a product moves through its lifecycle, from development to commercial manufacturing, the control strategy evolves based on accumulated knowledge and experience. Validation results, process monitoring data, and emerging risks all feed back into the control strategy, which in turn drives adjustments to design parameters and validation approaches.

Comparing Control Strategy Approaches: Similarities and Distinctions

While these three control strategy approaches have distinct focuses and applications, they share important commonalities. All three emphasize scientific understanding, risk management, and continuous improvement. They all serve as program-level documents that connect high-level requirements with operational execution. And all three have gained increasing regulatory recognition as pharmaceutical quality management has evolved toward more systematic, science-based approaches.

Aspect	Annex 1 CCS	ICH Q8 Process Control Strategy	Technology Platform Control Strategy
Primary Focus	Facility-wide contamination prevention	Product and process quality	Standardized approach across multiple products
Scope	Microbial, pyrogen, and particulate contamination (a good one will focus on physical, chemical and biologic hazards)	All aspects of product quality	Common technology elements shared across products
Regulatory Foundation	EU GMP Annex 1 (2022 revision)	ICH Q8(R2)	Emerging FDA guidance (Platform Technology Designation)
Implementation Level	Manufacturing facility	Individual product	Technology group or platform
Key Components	Contamination risk identification, detection methods, understanding of contamination sources	QTPP, CQAs, CPPs, CMAs, design space	Standardized technologies, processes, and controls
Risk Management Approach	Infrastructural (facility design, processes, personnel) – great for a HACCP	Product-specific (process parameters, material attributes)	Platform-specific (shared technological elements)
Team Structure	Cross-functional (production, engineering, QC, QA, microbiology)	Product development, manufacturing and quality	Technology development and product adaptation
Lifecycle Considerations	Continuous monitoring and improvement of facility controls	Product lifecycle from development to post-approval	Evolution of platform technology across multiple products
Documentation	Facility-specific CCS with ongoing monitoring records	Product-specific control strategy with design space definition	Platform master file with product-specific adaptations
Flexibility	Low (facility-specific controls)	Medium (within established design space)	High (adaptable across multiple products)
Primary Benefit	Contamination prevention and control	Consistent product quality through scientific understanding	Efficiency and knowledge leverage across product portfolio
Digital Integration	Environmental monitoring systems, facility controls	Process analytical technology, real-time release testing	Platform data management and cross-product analytics

These approaches are not mutually exclusive; rather, they complement each other within a comprehensive quality management system. A manufacturing site producing sterile products needs both an Annex 1 CCS for facility-wide contamination control and ICH Q8 process control strategies for each product. If the site uses common technology platforms across multiple products, platform control strategies would provide additional efficiency and standardization.

Control Strategies Through the Lens of Knowledge Management: Enhancing Quality and Operational Excellence

The pharmaceutical industry’s approach to control strategies has evolved significantly in recent years, with systematic knowledge management emerging as a critical foundation for their effectiveness. Control strategies—whether focused on contamination prevention, process control, or platform technologies—fundamentally depend on how knowledge is created, captured, disseminated, and applied across an organization. Understanding the intersection between control strategies and knowledge management provides powerful insights into building more robust pharmaceutical quality systems and achieving higher levels of operational excellence.

The Knowledge Foundation of Modern Control Strategies

Control strategies represent systematic approaches to ensuring consistent pharmaceutical quality by managing various aspects of production. While these strategies differ in focus and application, they share a common foundation in knowledge—both explicit (documented) and tacit (experiential).

Knowledge Management as the Binding Element

The ICH Q10 Pharmaceutical Quality System model positions knowledge management alongside quality risk management as dual enablers of pharmaceutical quality. This pairing is particularly significant when considering control strategies, as it establishes what might be called a “Risk-Knowledge Infinity Cycle”—a continuous process where increased knowledge leads to decreased uncertainty and therefore decreased risk. Control strategies represent the formal mechanisms through which this cycle is operationalized in pharmaceutical manufacturing.

Effective control strategies require comprehensive knowledge visibility across functional areas and lifecycle phases. Organizations that fail to manage knowledge effectively often experience problems like knowledge silos, repeated issues due to lessons not learned, and difficulty accessing expertise or historical product knowledge—all of which directly impact the effectiveness of control strategies and ultimately product quality.

The Feedback-Feedforward Controls Hub: A Knowledge Integration Framework

As described above, the heart of effective control strategies lies is the “feedback-feedforward controls hub.” This concept represents the integration point where knowledge flows bidirectionally to continuously refine and improve control mechanisms. In this model, control strategies function not as static documents but as dynamic knowledge systems that evolve through continuous learning and application.

The feedback component captures real-time process data, deviations, and outcomes that generate new knowledge about product and process performance. The feedforward component takes this accumulated knowledge and applies it proactively to prevent issues before they occur. This integrated approach creates a self-reinforcing cycle where control strategies become increasingly sophisticated and effective over time.

For example, in an ICH Q8 process control strategy, process monitoring data feeds back into the system, generating new understanding about process variability and performance. This knowledge then feeds forward to inform adjustments to control parameters, risk assessments, and even design space modifications. The hub serves as the central coordination mechanism ensuring these knowledge flows are systematically captured and applied.

Knowledge Flow Within Control Strategy Implementation

Knowledge flows within control strategies typically follow the knowledge management process model described in the ISPE Guide, encompassing knowledge creation, curation, dissemination, and application. For control strategies to function effectively, this flow must be seamless and well-governed.

The systematic management of knowledge within control strategies requires:

Methodical capture of knowledge through various means appropriate to the control strategy context
Proper identification, review, and analysis of this knowledge to generate insights
Effective storage and visibility to ensure accessibility across the organization
Clear pathways for knowledge application, transfer, and growth

When these elements are properly integrated, control strategies benefit from continuous knowledge enrichment, resulting in more refined and effective controls. Conversely, barriers to knowledge flow—such as departmental silos, system incompatibilities, or cultural resistance to knowledge sharing—directly undermine the effectiveness of control strategies.

Annex 1 Contamination Control Strategy Through a Knowledge Management Lens

The Annex 1 Contamination Control Strategy represents a facility-focused approach to preventing microbial, pyrogen, and particulate contamination. When viewed through a knowledge management lens, the CCS becomes more than a compliance document—it emerges as a comprehensive knowledge system integrating multiple knowledge domains.

Effective implementation of an Annex 1 CCS requires managing diverse knowledge types across functional boundaries. This includes explicit knowledge documented in environmental monitoring data, facility design specifications, and cleaning validation reports. Equally important is tacit knowledge held by personnel about contamination risks, interventions, and facility-specific nuances that are rarely fully documented.

The knowledge management challenges specific to contamination control include ensuring comprehensive capture of contamination events, facilitating cross-functional knowledge sharing about contamination risks, and enabling access to historical contamination data and prior knowledge. Organizations that approach CCS development with strong knowledge management practices can create living documents that continuously evolve based on accumulated knowledge rather than static compliance tools.

Knowledge mapping is particularly valuable for CCS implementation, helping to identify critical contamination knowledge sources and potential knowledge gaps. Communities of practice spanning quality, manufacturing, and engineering functions can foster collaboration and tacit knowledge sharing about contamination control. Lessons learned processes ensure that insights from contamination events contribute to continuous improvement of the control strategy.

ICH Q8 Process Control Strategy: Quality by Design and Knowledge Management

The ICH Q8 Process Control Strategy embodies the Quality by Design paradigm, where product and process understanding drives the development of controls that ensure consistent quality. This approach is fundamentally knowledge-driven, making effective knowledge management essential to its success.

The QbD approach begins with applying prior knowledge to establish the Quality Target Product Profile (QTPP) and identify Critical Quality Attributes (CQAs). Experimental studies then generate new knowledge about how material attributes and process parameters affect these quality attributes, leading to the definition of a design space and control strategy. This sequence represents a classic knowledge creation and application cycle that must be systematically managed.

Knowledge management challenges specific to ICH Q8 process control strategies include capturing the scientific rationale behind design choices, maintaining the connectivity between risk assessments and control parameters, and ensuring knowledge flows across development and manufacturing boundaries. Organizations that excel at knowledge management can implement more robust process control strategies by ensuring comprehensive knowledge visibility and application.

Particularly important for process control strategies is the management of decision rationale—the often-tacit knowledge explaining why certain parameters were selected or why specific control approaches were chosen. Explicit documentation of this decision rationale ensures that future changes to the process can be evaluated with full understanding of the original design intent, avoiding unintended consequences.

Technology Platform Control Strategies: Leveraging Knowledge Across Products

Technology platform control strategies represent standardized approaches applied across multiple products sharing similar characteristics or manufacturing technologies. From a knowledge management perspective, these strategies exemplify the power of knowledge reuse and transfer across product boundaries.

The fundamental premise of platform approaches is that knowledge gained from one product can inform the development and control of similar products, creating efficiencies and reducing risks. This depends on robust knowledge management practices that make platform knowledge visible and available across product teams and lifecycle phases.

Knowledge management challenges specific to platform control strategies include ensuring consistent knowledge capture across products, facilitating cross-product learning, and balancing standardization with product-specific requirements. Organizations with mature knowledge management practices can implement more effective platform strategies by creating knowledge repositories, communities of practice, and lessons learned processes that span product boundaries.

Integrating Control Strategies with Design, Qualification/Validation, and Risk Management

Control strategies serve as the central nexus connecting design, qualification/validation, and risk management in a comprehensive quality framework. This integration is not merely beneficial but essential for ensuring product quality while optimizing resources. A well-structured control strategy creates a coherent narrative from initial concept through commercial production, ensuring that design intentions are preserved through qualification activities and ongoing risk management.

The Design-Validation Continuum

Control strategies form a critical bridge between product/process design and validation activities. During the design phase, scientific understanding of the product and process informs the development of the control strategy. This strategy then guides what must be validated and to what extent. Rather than validating everything (which adds cost without necessarily improving quality), the control strategy directs validation resources toward aspects most critical to product quality.

Risk-Based Prioritization

Risk management principles are foundational to modern control strategies, informing both design decisions and validation priorities. A systematic risk assessment approach helps identify which aspects of a process or facility pose the greatest potential impact on product quality and patient safety. The control strategy then incorporates appropriate controls and monitoring systems for these high-risk elements, ensuring that validation efforts are proportionate to risk levels.

The Feedback-Feedforward Mechanism

The feedback-feedforward controls hub represents a sophisticated integration of two fundamental control approaches, creating a central mechanism that leverages both reactive and proactive control strategies to optimize process performance. This concept emerges as a crucial element in modern control systems, particularly in pharmaceutical manufacturing, chemical processing, and advanced mechanical systems.

To fully grasp the concept of a feedback-feedforward controls hub, we must first distinguish between its two primary components. Feedback control works on the principle of information from the outlet of a process being “fed back” to the input for corrective action. This creates a loop structure where the system reacts to deviations after they occur. Fundamentally reactive in nature, feedback control takes action only after detecting a deviation between the process variable and setpoint.

In contrast, feedforward control operates on the principle of preemptive action. It monitors load variables (disturbances) that affect a process and takes corrective action before these disturbances can impact the process variable. Rather than waiting for errors to manifest, feedforward control uses data from load sensors to predict when an upset is about to occur, then feeds that information forward to the final control element to counteract the load change proactively.

The feedback-feedforward controls hub serves as a central coordination point where these two control strategies converge and complement each other. As a product moves through its lifecycle, from development to commercial manufacturing, this control hub evolves based on accumulated knowledge and experience. Validation results, process monitoring data, and emerging risks all feed back into the control strategy, which in turn drives adjustments to design parameters and validation approaches.

Knowledge Management Maturity in Control Strategy Implementation

The effectiveness of control strategies is directly linked to an organization’s knowledge management maturity. Organizations with higher knowledge management maturity typically implement more robust, science-based control strategies that evolve effectively over time. Conversely, organizations with lower maturity often struggle with static control strategies that fail to incorporate learning and experience.

Common knowledge management gaps affecting control strategies include:

Inadequate mechanisms for capturing tacit knowledge from subject matter experts
Poor visibility of knowledge across organizational and lifecycle boundaries
Ineffective lessons learned processes that fail to incorporate insights into control strategies
Limited knowledge sharing between sites implementing similar control strategies
Difficulty accessing historical knowledge that informed original control strategy design

Addressing these gaps through systematic knowledge management practices can significantly enhance control strategy effectiveness, leading to more robust processes, fewer deviations, and more efficient responses to change.

The examination of control strategies through a knowledge management lens reveals their fundamentally knowledge-dependent nature. Whether focused on contamination control, process parameters, or platform technologies, control strategies represent the formal mechanisms through which organizational knowledge is applied to ensure consistent pharmaceutical quality.

Organizations seeking to enhance their control strategy effectiveness should consider several key knowledge management principles:

Recognize both explicit and tacit knowledge as essential components of effective control strategies
Ensure knowledge flows seamlessly across functional boundaries and lifecycle phases
Address all four pillars of knowledge management—people, process, technology, and governance
Implement systematic methods for capturing lessons and insights that can enhance control strategies
Foster a knowledge-sharing culture that supports continuous learning and improvement

By integrating these principles into control strategy development and implementation, organizations can create more robust, science-based approaches that continuously evolve based on accumulated knowledge and experience. This not only enhances regulatory compliance but also improves operational efficiency and product quality, ultimately benefiting patients through more consistent, high-quality pharmaceutical products.

The feedback-feedforward controls hub concept represents a particularly powerful framework for thinking about control strategies, emphasizing the dynamic, knowledge-driven nature of effective controls. By systematically capturing insights from process performance and proactively applying this knowledge to prevent issues, organizations can create truly learning control systems that become increasingly effective over time.

Conclusion: The Central Role of Control Strategies in Pharmaceutical Quality Management

Control strategies—whether focused on contamination prevention, process control, or technology platforms—serve as the intellectual foundation connecting high-level quality policies with detailed operational procedures. They embody scientific understanding, risk management decisions, and continuous improvement mechanisms in a coherent framework that ensures consistent product quality.

Regulatory Needs and Control Strategies

Regulatory guidelines like ICH Q8 and Annex 1 CCS underscore the importance of control strategies in ensuring product quality and compliance. ICH Q8 emphasizes a Quality by Design (QbD) approach, where product and process understanding drives the development of controls. Annex 1 CCS focuses on facility-wide contamination prevention, highlighting the need for comprehensive risk management and control systems. These regulatory expectations necessitate robust control strategies that integrate scientific knowledge with operational practices.

Knowledge Management: The Backbone of Effective Control Strategies

Knowledge management (KM) plays a pivotal role in the effectiveness of control strategies. By systematically acquiring, analyzing, storing, and disseminating information related to products and processes, organizations can ensure that the right knowledge is available at the right time. This enables informed decision-making, reduces uncertainty, and ultimately decreases risk.

Risk Management and Control Strategies

Risk management is inextricably linked with control strategies. By identifying and mitigating risks, organizations can maintain a state of control and facilitate continual improvement. Control strategies must be designed to incorporate risk assessments and management processes, ensuring that they are proactive and adaptive.

The Interconnectedness of Control Strategies

Control strategies are not isolated entities but are interconnected with design, qualification/validation, and risk management processes. They form a feedback-feedforward controls hub that evolves over a product’s lifecycle, incorporating new insights and adjustments based on accumulated knowledge and experience. This dynamic approach ensures that control strategies remain effective and relevant, supporting both regulatory compliance and operational excellence.

Why Control Strategies Are Key

Control strategies are essential for several reasons:

Regulatory Compliance: They ensure adherence to regulatory guidelines and standards, such as ICH Q8 and Annex 1 CCS.
Quality Assurance: By integrating scientific understanding and risk management, control strategies guarantee consistent product quality.
Operational Efficiency: Effective control strategies streamline processes, reduce waste, and enhance productivity.
Knowledge Management: They facilitate the systematic management of knowledge, ensuring that insights are captured and applied across the organization.
Risk Mitigation: Control strategies proactively identify and mitigate risks, protecting both product quality and patient safety.

Control strategies represent the central mechanism through which pharmaceutical companies ensure quality, manage risk, and leverage knowledge. As the industry continues to evolve with new technologies and regulatory expectations, the importance of robust, science-based control strategies will only grow. By integrating knowledge management, risk management, and regulatory compliance, organizations can develop comprehensive quality systems that protect patients, satisfy regulators, and drive operational excellence.

Best Practices for Managing the Life-Cycle of Single-Use Systems

Single-use systems (SUS) have become increasingly prevalent in biopharmaceutical manufacturing due to their flexibility, reduced contamination risk, and cost-effectiveness. The thing is, management of the life-cycle of single-use systems becomes critical and is an area organizations can truly screw up by cutting corners. To do it right requires careful collaboration between all stakeholders in the supply chain, from raw material suppliers to end users.

Design and Development

Apply Quality by Design (QbD) principles from the outset by focusing on process understanding and the design space to create controlled and consistent manufacturing processes that result in high-quality, efficacious products. This approach should be applied to SUS design.

ASTM E3051 “Standard guide for specification, design, verification, and application of SUS in pharmaceutical and biopharmaceutical manufacturing” provides an excellent framework for the design process.

Make sure to conduct thorough risk assessments, considering potential failure modes and effects throughout the SUS life-cycle.

Engage end-users early to understand their specific requirements and process constraints. A real mistake in organizations is not involving the end-users early enough. From the molecule steward to manufacturing these users are critical.

Raw Material and Component Selection

Carefully evaluate and qualify raw materials and components. Work closely with suppliers to understand material properties, extractables/leachables profiles, and manufacturing processes.

Develop comprehensive specifications for critical materials and components. ASTM E3244 is handy place to look for guidance on raw material qualification for SUS.

Manage the Supplier through Manufacturing and Assembly

Implementing robust supplier qualification and auditing programs and establish change control agreements with suppliers to be notified of any changes that could impact SUS performance or quality. It is important the supplier have a robust quality management system and that they apply Good Manufacturing Practices (GMP) through their facilities. Ensure they have in place appropriate controls to

Validate sterilization processes
Conduct routine bioburden and endotoxin testing
Design packaging to protect SUS during transportation and storage. Shipping methods need to protect against physical damage and temperature excursions
Establish appropriate storage conditions and shelf-life based on stability studies
Provide appropriate labeling and traceability
Have appropriate inventory controls. Ideally select suppliers who understand the importance of working with you for collaborative planning, forecasting and replenishment (CPFR)

Testing and Qualification

Develop a comprehensive testing strategy, including integrity testing and conduct extractables and leachables studies following industry guidelines. Evaluate the suppliers shipping and transportation studies to evaluate SUS robustness and determine if you need additional studies.

Implementation and Use

End users should have appropriate and comprehensive documentation and training to end users on proper handling, installation, and use of SUS. These procedures should include how to perform pre-use integrity testing at the point of use as well as how to perform thorough in-process and final inspections.

Consider implementing automated visual inspection systems and other appropriate monitoring.

Implement appropriate environmental monitoring programs in SUS manufacturing areas. While the dream of manufacturing outdoors is a good one, chances are we aren’t even close yet. Don’t short this layer of control.

Continuous Improvement

Ensure you have appropriate mechanisms in place to gather data on SUS performance and any issues encountered during use. Share relevant information across the supply chain to drive improvements.

Conduct periodic audits of suppliers and manufacturing facilities.

Stay updated on evolving regulatory guidance and industry best practices. There is still a lot changing in this space.

Multi-Criteria Decision-Making to Drive Risk Control

To be honest, too often, we perform a risk assessment not to make decisions but to justify an already existing risk assessment. The risk assessment may help define a few additional action items and determine how rigorous to be about a few things. It actually didn’t make much of an impact on the already-decided path forward. This is some pretty bad risk management and decision-making.

For highly important decisions with high uncertainty or complexity, it is useful to consider the options/alternatives that exist and assess the benefits and risks of each before deciding on a path forward. Thoroughly identifying options/alternatives and assessing the benefits and risks of each can help the decision-making process and ultimately reduce risk.

An effective, highly structured decision-making process can help answer the question, ‘How can we compare the consequences of the various options before deciding?

The most challenging risk decisions are characterized by having several different, important things to consider in an environment where there are often multiple stakeholders and, often, multiple decision-makers.

In Multi-Criteria Decision-Making (MCDM), the primary objective is the structured consideration of the available alternatives (options) for achieving the objectives in order to make the most informed decision, leading to the best outcome.

In a Quality Risk Management context, the decision-making concerns making informed decisions in the face of uncertainty about risks related to the quality (and/or availability) of medicines.

Key Concepts of MCDM

Conflicting Criteria: MCDM deals with situations where criteria conflict. For example, when purchasing a car, one might need to balance cost, comfort, safety, and fuel economy, which often do not align perfectly.
Explicit Evaluation: Unlike intuitive decision-making, MCDM involves a structured approach to explicitly evaluate multiple criteria, which is crucial when the stakes are high, such as deciding whether to build additional manufacturing capacity for a product under development.
Types of Problems:

Multiple-Criteria Evaluation Problems: These involve a finite number of alternatives known at the beginning. The goal is to find the best alternative or a set of good alternatives based on their performance across multiple criteria.
Multiple-Criteria Design Problems: In these problems, alternatives are not explicitly known and must be found by solving a mathematical model. The number of alternatives can be very large, often exponentially.

Preference Information: The methods used in MCDM often require preference information from decision-makers (DMs) to differentiate between solutions. This can be done at various stages of the decision-making process, such as prior articulation of preferences, which transforms the problem into a single-criterion problem.

MCDM focuses on risk and uncertainty by explicitly weighing criteria and trade-offs between them. Multi-criteria decision-making (MCDM) differs from traditional decision-making methods in several key ways:

Explicit Consideration of Multiple Criteria: Traditional decision-making often focuses on a single criterion like cost or profit. MCDM explicitly considers multiple criteria simultaneously, which may be conflicting, such as cost, quality, safety, and environmental impact[1]. This allows for a more comprehensive evaluation of alternatives.
Structured Approach: MCDM provides a structured framework for evaluating alternatives against multiple criteria rather than relying solely on intuition or experience. It involves techniques like weighting criteria, scoring alternatives, and aggregating scores to rank or choose the best option.
Transparency and Consistency: MCDM methods aim to make decision-making more transparent, consistent, and less susceptible to individual biases. The criteria, weights, and evaluation process are explicitly defined, allowing for better justification and reproducibility of decisions.
Quantitative Analysis: Many MCDM methods employ quantitative techniques, such as mathematical models, optimization algorithms, and decision support systems. This enables a more rigorous and analytical approach compared to traditional qualitative methods.
Handling Complexity: MCDM is particularly useful for complex decision problems involving many alternatives, conflicting objectives, and multiple stakeholders. Traditional methods may struggle to handle such complexity effectively.
Stakeholder Involvement: Some MCDM methods, like the Analytic Hierarchy Process (AHP), facilitate the involvement of multiple stakeholders and the incorporation of their preferences and judgments. This can lead to more inclusive and accepted decisions.
Trade-off Analysis: MCDM techniques often involve analyzing trade-offs between criteria, helping decision-makers understand the implications of prioritizing certain criteria over others. This can lead to more informed and balanced decisions.

While traditional decision-making methods rely heavily on experience, intuition, and qualitative assessments, MCDM provides a more structured, analytical, and comprehensive approach, particularly in complex situations with conflicting criteria.

Multi-Criteria Decision-Making (MCDM) is typically performed following these steps:

Define the Decision Problem: Clearly state the problem or decision to be made, identify the stakeholders involved, and determine the desired outcome or objective.
Establish Criteria: Identify the relevant criteria that will be used to evaluate the alternatives. These criteria should be measurable, independent, and aligned with the objectives. Involve stakeholders in selecting and validating the criteria.
Generate Alternatives: Develop a comprehensive list of potential alternatives or options that could solve the problem. Use techniques like brainstorming, benchmarking, or scenario analysis to generate diverse alternatives.
Gather Performance Data: Assess how each alternative performs against each criterion. This may involve quantitative data, expert judgments, or qualitative assessments.
Assign Criteria Weights: By assigning weights, determine each criterion’s relative importance or priority. This can be done through methods like pairwise comparisons, swing weighting, or direct rating. Stakeholder input is crucial here.
Apply MCDM Method: Choose an appropriate MCDM technique based on the problem’s nature and the available data. Some popular methods include: Analytic Hierarchy Process (AHP); Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS); ELimination and Choice Expressing REality (ELECTRE); Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE); and, Multi-Attribute Utility Theory (MAUT).
Evaluate and Rank Alternatives: Apply the chosen MCDM method to evaluate and rank the alternatives based on their performance against the weighted criteria. This may involve mathematical models, software tools, or decision support systems.
Sensitivity Analysis: Perform sensitivity analysis to assess the robustness of the results and understand how changes in criteria weights or performance scores might affect the ranking or choice of alternatives.
Make the Decision: Based on the MCDM analysis, select the most preferred alternative or develop an action plan based on the ranking of alternatives. Involve stakeholders in the final decision-making process.
Monitor and Review: Implement the chosen alternative and monitor its performance. Review the decision periodically, and if necessary, repeat the MCDM process to adapt to changing circumstances or new information.

MCDM is an iterative process; stakeholder involvement, transparency, and clear communication are crucial. Additionally, the specific steps and techniques may vary depending on the problem’s complexity, the data’s availability, and the decision-maker’s preferences.

MCDM Technique	Description	Application	Key Features
Analytic Hierarchy Process (AHP)	A structured technique for organizing and analyzing complex decisions, using mathematics and psychology.	Widely used in business, government, and healthcare for prioritizing and decision-making.	Pairwise comparisons, consistency checks, and hierarchical structuring of criteria and alternatives.
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)	Based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution and the longest geometric distance from the negative ideal solution.	Frequently used in engineering, management, and human resource management for ranking and selection problems.	Compensatory aggregation, normalization of criteria, and calculation of geometric distances.
Elimination and Choice Expressing Reality (ELECTRE)	An outranking method that compares alternatives by considering both qualitative and quantitative criteria. It uses a pairwise comparison approach to eliminate less favorable alternatives.	Commonly used in project selection, resource allocation, and environmental management.	Use of concordance and discordance indices, handling of both qualitative and quantitative data, and ability to deal with incomplete rankings.
Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE)	An outranking method that uses preference functions to compare alternatives based on multiple criteria. It provides a complete ranking of alternatives.	Applied in various fields such as logistics, finance, and environmental management.	Preference functions, visual interactive modules (GAIA), and sensitivity analysis.
Multi-Attribute Utility Theory (MAUT)	Involves converting multiple criteria into a single utility function, which is then used to evaluate and rank alternatives. It takes into account the decision-maker’s risk preferences and uncertainties.	Used in complex decision-making scenarios involving risk and uncertainty, such as policy analysis and strategic planning.	Utility functions, probabilistic weights, and handling of uncertainty.

Popular MCDM Techniques

ASTM E2500 Approach to Validation

ASTM E2500, the Standard Guide for Specification, Design, and Verification of Pharmaceutical and Biopharmaceutical Manufacturing Systems and Equipment, is intended to “satisfy international regulatory expectations in ensuring that manufacturing systems and equipment are fit for the intended use and to satisfy requirements for design, installation, operation, and performance.”

The ASTM E2500 approach is a comprehensive framework for specification setting, design, and verification of pharmaceutical and biopharmaceutical manufacturing systems and equipment. It emphasizes a risk- and science-based methodology to ensure that systems are fit for their intended use, ultimately aiming to enhance product quality and patient safety.

Despite its 17-year history, it is fair to say it is not the best-implemented standard. There are still many unrealized opportunities and some major challenges. I don’t think a single organization I’ve been in has fully aligned, and ASTM E2500 can feel aspirational.

Key Principles

Risk Management: The approach integrates risk management principles from ICH Q8, Q9, and Q10, focusing on identifying and mitigating risks to product quality and patient safety throughout the lifecycle of the manufacturing system.
Good Engineering Practices (GEP): It incorporates GEP to ensure systems are correctly designed, installed, and operated.
Flexibility and Efficiency: It strives for a more flexible and efficient organization of verification activities that can be adapted to each project’s specific context.

Know your Process

Regulatory agencies expect drugmakers to persuade them that we know our processes and that our facilities, equipment, systems, utilities, and procedures have been established based on concrete data and a thorough risk assessment. The ASTM E2500 standard provides a means of demonstrating that all of these factors have been validated in consideration of carefully evaluated risks.

What the Standard Calls for

Four Main Steps

Requirements: Define the system’s needs and critical aspects. Subject Matter Experts (SMEs) play a crucial role in this phase by defining needs, identifying critical aspects, and developing the verification strategy.
Specification & Design: Develop detailed specifications and design the system to meet the requirements. This step involves thorough design reviews and risk assessments to ensure the system functions as intended.
Verification: Conduct verification activities to confirm that the system meets all specified requirements. This step replaces the traditional FAT/SAT/IQ/OQ/PQ sequence with a more streamlined verification process that can be tailored to the project’s needs.
Acceptance & Release: Finalize the verification process and release the system for operational use. This step includes the final review and approval of all verification activities and documentation.

Four Cross-Functional Processes

Good Engineering Practices (GEP): Ensure all engineering activities adhere to industry standards and best practices.
Quality Risk Management: Continuously assess and manage risks to product quality and patient safety throughout the project.
Design Review: Regularly reviews the system design to ensure it meets all requirements and addresses identified risks.
Change Management: Implement a structured process for managing system changes to ensure that all modifications are appropriately evaluated and documented.

Applications and Benefits

Applicability: The ASTM E2500 approach can be applied to new and existing manufacturing systems, including laboratory, information, and medical device manufacturing systems.
Lifecycle Coverage: It applies throughout the manufacturing system’s lifecycle, from concept to retirement.
Regulatory Compliance: The approach is designed to conform with FDA, EU, and other international regulations, ensuring that systems are qualified and meet all regulatory expectations.
Efficiency and Cost Management: By focusing on critical aspects and leveraging risk management tools, the ASTM E2500 approach can streamline project execution, reduce time to market, and optimize resource utilization.

The ASTM E2500 approach provides a structured, risk-based framework for specifying, designing, and verifying pharmaceutical and biopharmaceutical manufacturing systems. It emphasizes flexibility, efficiency, and regulatory compliance, making it a valuable tool for ensuring product quality and patient safety.

What Makes it Different?

	ASTM E2500	The more traditional approach
Testing Approach	It emphasizes a risk-based approach, focusing on identifying and managing risks to product quality and patient safety throughout the manufacturing system’s lifecycle. This approach allows for flexibility in organizing verification activities based on the specific context and critical aspects of the system.	Typically follows a prescriptive sequence of tests (FAT, SAT, IQ, OQ, PQ) as outlined in guidelines like EU GMP Annex 15. This method is more rigid and less adaptable to the specific needs and risks of each project.
Verification vs Qualification	The term “verification” encompasses all testing activities, which can be organized more freely and rationally to optimize efficiency. Verification activities are tailored to the project’s needs and focus on critical aspects.	Follows a structured qualification process (Installation Qualification, Operational Qualification, Performance Qualification) with predefined steps and documentation requirements.
Role of Subject Matter Experts	SMEs play a crucial role from the start of the project, contributing to the definition of needs, identification of critical aspects, system design review, and development of the verification strategy. They are involved throughout the project lifecycle.	SMEs are typically involved at specific points in the project lifecycle, primarily during the qualification phases, and may not have as continuous a role as in the ASTM E2500 approach.
Integration of Good Engineering Practices	Offers greater flexibility in organizing verification activities, allowing for a more efficient and streamlined process. This can lead to reduced time to market and optimized resource utilization.	While GEP is also important, the focus is more on the qualification steps rather than integrating GEP throughout the entire project lifecycle.
Change Management	It emphasizes early and continuous change management, starting from the supplier’s site, to avoid test duplication and ensure that changes are properly evaluated and documented.	It emphasizes early and continuous change management, starting from the supplier’s site, to avoid test duplication and ensure that changes are properly evaluated and documented.
Documentation	Documentation is focused on risk management and verification activities, ensuring compliance with international regulations (FDA, EU, ICH Q8, Q9, Q10). The approach is designed to meet regulatory expectations while allowing for flexibility in documentation.	quires extensive documentation for each qualification step, which can be more cumbersome and less adaptable to specific project needs.

Opinion

I’m watching to see what the upcoming update to Annex 15 will do to address the difficulties some see between an ATSM E2500 approach and the European regulations. I also hope we will see an update to ISPE Baseline® Guide Volume 5: Commissioning and Qualification to align an approach.

ISPE Baseline® Guide Volume 5	ATSM E2500
Design inputs Impact assessment Design Qualification Commissioning Multiple trial runs to get things right IQ, OQ, PQ, and acceptance criteria GEP Scope and QA Scope overlapped Focused on Documentation Deliverables Change Management	Design inputs Design Review Risk Mitigation Critical Control Parameters define Acceptance Criteria Verification Testing Performance Testing GEP Scope and QA Scope have a clear boundary Process, Product Quality and Patient Safety Quality by Design, Design Space, and Continuous Improvement

To be honest I don’t think ATSM E2500, ISPE Guide 5, or anything else has the balance just right. And your program ends up being a triangulation between these and the regulations. And don’t even bring in trying to align GAMP5 or USP <1058> or…or…or…

And yes, I do consider this part of my 3-year plan. I look forward to the challenges of a culture shift, increased SME involvement, formalization of GEPs (and teaching engineers how to write), effective change management, timely risk assessments, and comprehensive implementation planning.

Q13 and Q14 path forward

Final concept papers have been published for the next two ICH quality guidelines. In both cases we can hope to see drafts in the first half of 2020. Both guidelines are intended to supplement the existing documents ICH Q8 – ICH Q12, reinforcing the principles of a risk based quality by design (QbD).

ICH Q13: Continuous Manufacturing of Drug Substances and Drug Products

Final concept paper and business plan. This new quality guideline will:

capture key technical and regulatory considerations including certain CGMP elements specific to continuous manufacturing
allow drug manufacturers to employ flexible approaches to develop, implement, or integrate continuous manufacturing for the manufacture of small molecules and therapeutic proteins for new and existing products
provide guidance to industry and regulatory agencies regarding regulatory expectations on the development, implementation, and assessment of continuous manufacturing technologies.

ICH Q2/Q14: Analytical Procedure Development

Concept paper and business plan. Q14 will bring the QbD principles to analytical development.

In the course of the preparation of this new guideline, ICH Q2 (Validation of Analytical Procedures) will also be revised. It will be adapted to the state of the art to include modern analytical methods in the future..

It’s stated that the Expert Working Group (EWG) will evaluate combining Q2 and Q14 into one document. Here’s hoping.