Living Risk in the Validation Lifecycle

Risk management plays a pivotal role in validation by enabling a risk-based approach to defining validation strategies, ensuring regulatory compliance, mitigating product quality and safety risks, facilitating continuous improvement, and promoting cross-functional collaboration. Integrating risk management principles into the validation lifecycle is essential for maintaining control and consistently producing high-quality products in regulated industries such as biotech and medical devices.

We will conduct various risk assessments in our process lifecycle—many ad hoc (static) and a few living (dynamic). Understanding how they fit together in a larger activity set is crucial.

In the Facility, Utilities, Systems, and Equipment (FUSE) space, we are taking the process understanding, translating it into a design, and then performing Design Qualification (DQ) to verify that the critical aspects (CAs) and critical design elements (CDEs) necessary to control risks identified during the quality risk assessment (QRA) are present in the design. This helps mitigate risks to product quality and patient safety. To do this, we need to properly understand the process. Unfortunately, we often start with design before understanding the process and then need to go back and perform rework. Too often I see a dFMEA ignored or as an input to the pFMEA instead of working together in a full risk management cycle.

The Preliminary Hazard Analysis (PHA) supports a pFMEA, which supports a dFMEA, which supports the pFMEA (which also benefits at this stage from a HAACP). Tools fit together to provide the approach. Tools do not become the approach.

Design and Process FMEAs

DFMEA (Design Failure Mode and Effects Analysis) and PFMEA (Process Failure Mode and Effects Analysis) are both methodologies used within the broader FMEA framework to identify and mitigate potential failures. Still, they focus on different aspects of development and manufacturing.

	DFMEA	PFMEA
Scope and Focus	Primarily scrutinizes design to preempt flaws.	Focuses on processes to ensure effectiveness, efficiency and reliability.
Stakeholder Involvement	Engages design-oriented teams like engineering, quality engineers, and reliability engineers.	Involves operation-centric personnel such as manufacturing, quality control, quality operations, and process engineers.
Inputs and Outputs	Relies on design requirements, product specs, and component interactions to craft a robust product.	Utilizes process steps, equipment capabilities, and parameters to design a stable operational process.
Stages in lifecycle	Conducted early in development, concurrent with the design phase, it aids in early issue detection and minimizes design impact.	Executed in production planning post-finalized design, ensuring optimized operations prior to full-scale production.
Updated When	Executed in production planning post-finalized design, ensuring optimized operations before full-scale production.	Process changes and under annual review.

dFMEA and pFMEA

Risk Analysis in the Design Phase

The design qualification phase is especially suitable for determining risks for products and patients stemming from the equipment or machine. These risks should be identified during the design qualification and reflected by appropriate measures in the draft design so that the operator can effectively eliminate, adequately control, and monitor or observe them. To identify design defects (mechanical) or in the creation of systems (electronics) on time and to eliminate them at a low cost, it is advisable to perform the following risk analysis activities for systems, equipment, or processes:

Categorize the GMP criticality and identify the critical quality attributes and process parameters;
Categorize the requirements regarding the patient impact and product impact (for example, in the form of a trace matrix);
Identify critical functions and system elements (e.g., the definition of a calibration concept and preventive maintenance);
Investigate functions for defect recognition. This includes checking alarms and fault indications, operator error, etc. The result of this risk analysis may be the definition of further maintenance activities, a different assessment of a measurement point, or the identification of topics to include in the operating manuals or procedures.

Additional risk analyses for verifying the design may include usability studies using equipment mock-ups or preliminary production trials (engineering studies) regarding selected topics to prove the feasibility of specific design aspects (e.g., interaction between machine and materials).

Too often, we misunderstand risk assessments and start doing them at the most granular level. This approach allows us to right-size our risk assessments and holistically look at the entire lifecycle.

Challenges in Validation

I often get asked why I moved from a broader senior role in Quality Management to a particular but deep role in Quality Engineering and Validation. There are many answers, but the biggest is that validation is poised for some exciting shifts due to navigating a complex validation landscape characterized by rapid technological advancements, evolving regulatory standards, and the development of novel therapies. Addressing these challenges requires innovation, collaboration, and a proactive approach to risk management and data integration. Topics near and dear to me.

Today’s Challenges in Biotech Validation

1. Rapid Technological Advancements

The biotech industry is experiencing rapid technological advancements such as AI, machine learning, and automation. Integrating these technologies into validation processes can be challenging due to the need for new validation frameworks and methodologies.

2. Regulatory Compliance

Maintaining compliance with evolving regulatory standards is a significant challenge. Regulatory bodies like the FDA continuously update guidelines for technological advancements.

3. Complexity of New Therapies

Developing novel therapies, such as cell and gene therapies, introduces additional complexity to the validation process. These therapies often require redesigned facilities and equipment to accommodate their sensitive and sterile nature. Ensuring sterility and product quality at each process stage is crucial but challenging.

4. Data Management and Integration

Managing and integrating vast amounts of data has become challenging with the increasing use of digital tools and platforms. Effective data management is essential for predictive modeling and risk management in validation processes. Organizations must adopt robust data analytics and machine learning tools to handle this data efficiently.

5. Collaboration and Knowledge Sharing

Validation processes often require collaboration among various stakeholders, including validation teams, developers, and regulatory bodies. Ensuring real-time communication and data sharing can be challenging but is essential for streamlining validation efforts and aligning goals.

6. Resource Constraints

Smaller biotech companies, in particular, face resource constraints regarding funding, personnel, and expertise. These constraints can hinder their ability to implement advanced validation techniques and maintain compliance with regulatory standards.

7. Risk Management

Adopting a risk-based approach to validation is essential but challenging. Companies must identify and mitigate risks throughout the product lifecycle, which requires a thorough understanding of potential risks and effective risk management strategies.

Let’s Avoid the Term Validation 4.0

Let’s avoid the 4.0 term. We are constantly evolving, and adding a current ‘buzziness’ to it does no one any favors. We are shifting from traditional, paper-heavy validation methods to a more dynamic, data-driven, and digitalized process. Yes, we are leveraging modern technologies such as automation, data analytics, artificial intelligence (AI), and the Internet of Things (IoT) to enhance validation processes’ efficiency, flexibility, and reliability. But we don’t need buzziness, we just need to give it some thought, experiment, and refine.

Component Manufacturers Validation Requirements

I recently got asked what a medical device component manufacturer’s validation requirements are. Here is my answer.

Component manufacturers play a crucial role in the medical device industry by producing various parts and components for proper functioning and assembly. Here are some key expectations and responsibilities of component manufacturers in the medical device sector:

Quality and Precision Manufacturing: Medical device components often require high precision, accuracy, and quality to ensure patient safety and device efficacy. To meet these demanding standards, component manufacturers must adhere to stringent quality control measures, utilize advanced manufacturing techniques, and maintain strict tolerances.
Regulatory Compliance: The medical device industry is heavily regulated, and component manufacturers must comply with relevant regulations and standards set by governing bodies like the FDA, ISO, and others. This includes maintaining proper documentation, implementing quality management systems, and ensuring traceability of materials and processes.
Material Selection and Biocompatibility: Many medical device components come into direct contact with the human body or bodily fluids. Consequently, component manufacturers must carefully select biocompatible, non-toxic, and suitable materials for the intended application. They must also ensure proper sterilization and packaging to maintain sterility.
Design and Engineering Support: Some component manufacturers offer design and engineering services in addition to manufacturing to assist medical device companies in developing new components or optimizing existing ones. This collaboration helps ensure that components meet specific performance, functional, and regulatory requirements.
Supply Chain Management: Component manufacturers must have robust supply chain management systems to ensure the timely delivery of components to medical device manufacturers. This includes maintaining adequate inventory levels, managing logistics, and minimizing disruptions in the supply chain.

Yes, component manufacturers in the medical device industry are expected to validate their manufacturing processes to ensure the components they produce meet specified requirements and perform as intended.

Regulatory bodies like the FDA require that components critical to the safety and performance of medical devices be produced through validated processes. This helps ensure that components consistently meet quality standards.
Component manufacturers must perform Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ) on their manufacturing equipment and processes.
Validation requirements apply to finished components and raw materials, sub-components received from suppliers, and any processes involved in producing the component. Traceability of validation activities throughout the supply chain is essential.
The level of validation required depends on the component’s criticality and risk to the final medical device. More stringent validation is expected for higher-risk components that directly contact the patient or are essential for device safety and efficacy.
The component manufacturer must maintain validation documentation such as protocols, test reports, and traceability matrices and provide it to the medical device company upon request for review and auditing purposes.

The State of the Analytical Lifecycle

There have been a lot of changes in the way pharma thinks of analytical lifecycles in the last few years. With changes in technology, new product modalities, ICH Q2(R2) and ICH Q14 being released in November 2023, and USP <1220> in 2022, it is fair to say we are all catching up with our analytical lifecycle programs.

Let’s discuss what I think are the four pivotal documents that provide direction.

ICH Q2(R2) and ICH Q14

ICH Q2(R2) and ICH Q14 are complementary guidelines that provide a comprehensive framework for the development, validation, and lifecycle management of analytical procedures used in the pharmaceutical industry.

ICH Q14 describes the scientific principles and risk-based approaches for developing and maintaining suitable analytical procedures throughout their lifecycle. It outlines the key elements and considerations for analytical procedure development, including:

Defining an Analytical Target Profile (ATP)
Knowledge management and risk assessment
Evaluating robustness and parameter ranges
Establishing an Analytical Procedure Control Strategy
Lifecycle management and post-approval changes
Multivariate analytical procedures
Real-time release testing

On the other hand, ICH Q2(R2) provides specific guidance on validating analytical procedures to demonstrate their suitability for the intended use. It covers various validation tests, methodologies, and evaluation criteria, such as:

Specificity/selectivity
Working range
Accuracy and precision
Robustness
Stability-indicating properties
Multivariate analytical procedures

In summary, ICH Q14 establishes the overarching principles and approaches for analytical procedure development. At the same time, ICH Q2(R2) focuses on the validation aspects to ensure the analytical procedures are fit for purpose and meet quality requirements throughout their lifecycle. The two guidelines are intended to be applied together, with ICH Q14 providing the framework for development and ICH Q2(R2) specifying the validation requirements.

USP <1220> Analytical Procedure Lifecycle and USP <1058> Analytical Instrument Qualification

USP <1220> Analytical Procedure Lifecycle and USP <1058> Analytical Instrument Qualification are closely connected and complementary guidelines that provide a comprehensive framework for ensuring data integrity and quality in analytical procedures throughout their lifecycle.

The key connections between USP <1220> and USP <1058> are:

USP <1220> establishes the principles and requirements for managing the entire lifecycle of analytical procedures, from procedure design and development to retirement. It emphasizes the importance of defining an Analytical Target Profile (ATP) and implementing an Analytical Procedure Control Strategy.
USP <1058> focuses explicitly on the qualification of analytical instruments that execute analytical procedures. It outlines the requirements for ensuring instruments are suitable for their intended use through proper qualification (Design, Installation, Operational, and Performance Qualification).
The instrument qualification activities described in USP <1058> are critical to the overall Analytical Procedure Control Strategy outlined in USP <1220>. Proper instrument qualification as per <1058> helps ensure the quality and integrity of data generated by analytical procedures throughout their lifecycle.
Both guidelines stress the importance of defining user requirements (ATP in <1220> and User Requirements Specification in <1058>) as the basis for procedure development and instrument qualification activities.
USP <1220> requires ongoing monitoring and periodic requalification of analytical procedures, which includes re-evaluating the suitability of the analytical instruments used, as described in the Performance Qualification section of <1058>.

USP <1220> provides the overarching framework for holistically managing analytical procedures. USP <1058> focuses on ensuring the instruments used to execute those procedures are properly qualified and suitable for their intended use. The two guidelines work together to maintain data integrity and quality across the entire analytical lifecycle.

Complementary Approaches

USP <1220> Analytical Procedure Lifecycle is closely related to and complements the ICH Q2(R2) and ICH Q14 guidelines.

USP <1220> aligns with the principles outlined in ICH Q14 for managing the entire lifecycle of analytical procedures, from design and development to retirement. Both emphasize defining an Analytical Target Profile and implementing an Analytical Procedure Control Strategy.
The validation activities described in ICH Q2(R2), such as evaluating specificity, accuracy, precision, and robustness, are critical components of the Analytical Procedure Control Strategy required by USP <1220>.
USP <1220> requires ongoing monitoring and periodic requalification of analytical procedures, which aligns with the lifecycle management approach promoted in ICH Q14 and the validation during the lifecycle section in Q2(R2).
All these guidelines stress the importance of knowledge management, risk management, and a science/risk-based approach throughout the analytical procedure lifecycle.
The instrument qualification requirements outlined in USP <1058> are an integral part of the overall Analytical Procedure Control Strategy described in USP <1220>, ensuring instruments are suitable as per ICH Q2(R2) validation principles.

In essence, USP <1220> provides a comprehensive framework for analytical procedure lifecycle management that incorporates and operationalizes the scientific principles and validation activities detailed in the ICH Q14 and Q2(R2) guidelines, while USP <1058> provides the roadmap for instrument qualification. These four documents establish harmonized best practices for analytical procedures from development through retirement.

Commissioning, Qualification and Validation

Commissioning, qualification, and validation are three distinct but interrelated processes in the pharmaceutical and biotechnology industries that ensure facilities, equipment, systems, and processes meet regulatory requirements and produce products of the desired quality. Here are the key differences:

Commissioning

Commissioning is a systematic process of ensuring that equipment, systems, and facilities are designed, installed, and functioning according to operational and engineering requirements.
It involves design reviews, installation verification, functional testing, and handover to operations.
Commissioning primarily focuses on satisfying engineering requirements and does not have direct regulatory requirements.

Qualification

Qualification is a regulated and documented process that demonstrates that equipment, systems, and facilities are installed correctly and operate as intended for their specific use.
It applies only to equipment, systems, and utilities that directly or indirectly impact product quality and patient safety.
Qualification activities include Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ).
Qualification is focused on by regulatory authorities like the FDA and EMA to ensure compliance.

Validation

Validation is a broader concept establishing documented evidence that a process consistently produces a product that meets its predetermined specifications and quality attributes.
It encompasses the entire process lifecycle, including process design, qualification of equipment/systems, and continued process verification.
Validation ensures that the equipment and systems are qualified and the entire process is controlled to produce the desired final product.

In summary, commissioning verifies engineering requirements, qualification demonstrates suitability for intended use, and validation provides a high degree of assurance that the process will consistently produce a quality product. These activities are interconnected, with commissioning often leveraged during qualification and qualification being a subset of the overall validation process.

FDA’s Framework for Process Validation

The FDA’s Process Validation Guidance is a core document outlining a lifecycle approach with outlines a lifecycle approach with three main stages:

Stage 1: Process Design

Establish a process design based on knowledge gained through development and scale-up activities.
Identify critical quality attributes (CQAs) and critical process parameters (CPPs) using risk assessment and multivariate studies like Design of Experiments (DoE).
Develop a control strategy to ensure CQAs are met.

Stage 2: Process Qualification

Evaluate the process design through facility, utility, and equipment qualification.
Conduct performance qualification (PQ) by running production batches to confirm the process design has reproducible commercial manufacturing.
Establish scientific evidence that the process meets all defined requirements and product specifications.

Stage 3: Continued Process Verification

Maintain the validated status and monitor performance to ensure a state of control.
Identify sources of variation and implement process improvements through an ongoing program.
Conduct product quality reviews periodically to evaluate process performance.

The guidance emphasizes using a science and risk-based approach throughout the lifecycle, leveraging process understanding and knowledge gained from development through commercial production. Effective process validation requires good planning, documented evidence, and a robust quality system.