Assessing the Quality of Our Risk Management Activities

Twenty years on, risk management in the pharmaceutical world continues to be challenging. Ensure that risk assessments are systematic, structured, and based on scientific knowledge. A large part of the ICH Q9(R1) revision was written to address continued struggles with subjectivity, formality, and decision-making. And quite frankly, it’s clear to me that we, as an industry, are still working to absorb those messages these last two years.

A big challenge is that we struggle to measure the effectiveness of our risk assessments. Quite frankly, this is a great place for a rubric.

Luckily, we have a good tool out there to adopt: the Risk Analysis Quality Test (RAQT1.0), developed by the Society for Risk Analysis (SRA). This comprehensive framework is designed to evaluate and improve the quality of risk assessments. We can apply this tool to meet the requirements of the International Conference on Harmonisation (ICH) Q9, which outlines quality risk management principles for the pharmaceutical industry. From that, we can drive continued improvement in our risk management activities.

Components of RAQT1.0

The Risk Analysis Quality Test consists of 76 questions organized into 15 categories:

Framing the Analysis and Its Interface with Decision Making
Capturing the Risk Generating Process (RGP)
Communication
Stakeholder Involvement
Assumptions and Scope Boundary Issues
Proactive Creation of Alternative Courses of Action
Basis of Knowledge
Data Limitations
Analysis Limitations
Uncertainty
Consideration of Alternative Analysis Approaches
Robustness and Resilience of Action Strategies
Model and Analysis Validation and Documentation
Reporting
Budget and Schedule Adequacy

Application to ICH Q9 Requirements

ICH Q9 emphasizes the importance of a systematic and structured risk assessment process. The RAQT can be used to ensure that risk assessments are thorough and meet quality standards. For example, Category G (Basis of Knowledge) and Category H (Data Limitations) help in evaluating the scientific basis and data quality of the risk assessment, aligning with ICH Q9’s requirement for using available knowledge and data.

The RAQT’s Category B (Capturing the Risk Generating Process) and Category C (Communication) can help in identifying and communicating risks effectively. This aligns with ICH Q9’s requirement to identify potential risks based on scientific knowledge and understanding of the process.

Categories such as Category I (Analysis Limitations) and Category J (Uncertainty) in the RAQT help in analyzing the risks and addressing uncertainties, which is a key aspect of ICH Q9. These categories ensure that the analysis is robust and considers all relevant factors.

The RAQT’s Category A (Framing the Analysis and Its Interface with Decision Making) and Category F (Proactive Creation of Alternative Courses of Action) are crucial for evaluating risks and developing mitigation strategies. This aligns with ICH Q9’s requirement to evaluate risks and determine the need for risk reduction.

Categories like Category L (Robustness and Resilience of Action Strategies) and Category M (Model and Analysis Validation and Documentation) in the RAQT help in ensuring that the risk control measures are robust and well-documented. This is consistent with ICH Q9’s emphasis on implementing and reviewing controls.

Category D (Stakeholder Involvement) of the RAQT ensures that stakeholders are engaged in the risk management process, which is a requirement under ICH Q9 for effective communication and collaboration.

The RAQT can be applied both retrospectively and prospectively, allowing for the evaluation of past risk assessments and the planning of future ones. This aligns with ICH Q9’s requirement for periodic review and continuous improvement of the risk management process.

Creating a Rubric

To make this actionable we need a tool, a rubric, to allow folks to evaluate what goods look like. I would insert this tool into the quality oversite of risk management.

Category A: Framing the Analysis and Its Interface With Decision Making

Criteria	Excellent (4)	Good (3)	Fair (2)	Poor (1)
Problem Definition	Clearly and comprehensively defines the problem, including all relevant aspects and stakeholders	Adequately defines the problem with most relevant aspects considered	Partially defines the problem with some key aspects missing	Poorly defines the problem or misses critical aspects
Analytical Approach	Selects and justifies an optimal analytical approach, demonstrating deep understanding of methodologies	Chooses an appropriate analytical approach with reasonable justification	Selects a somewhat relevant approach with limited justification	Chooses an inappropriate approach or provides no justification
Data Collection and Management	Thoroughly identifies all necessary data sources and outlines a comprehensive data management plan	Identifies most relevant data sources and provides a adequate data management plan	Identifies some relevant data sources and offers a basic data management plan	Fails to identify key data sources or lacks a coherent data management plan
Stakeholder Identification	Comprehensively identifies all relevant stakeholders and their interests	Identifies most key stakeholders and their primary interests	Identifies some stakeholders but misses important ones or their interests	Fails to identify major stakeholders or their interests
Decision-Making Context	Provides a thorough analysis of the decision-making context, including constraints and opportunities	Adequately describes the decision-making context with most key factors considered	Partially describes the decision-making context, missing some important factors	Poorly describes or misunderstands the decision-making context
Alignment with Organizational Goals	Demonstrates perfect alignment between the analysis and broader organizational objectives	Shows good alignment with organizational goals, with minor gaps	Partially aligns with organizational goals, with significant gaps	Fails to align with or contradicts organizational goals
Communication Strategy	Develops a comprehensive strategy for communicating results to all relevant decision-makers	Outlines a good communication strategy covering most key decision-makers	Provides a basic communication plan with some gaps	Lacks a clear strategy for communicating results to decision-makers

This rubric provides a framework for assessing the quality of work in framing an analysis and its interface with decision-making. It covers key aspects such as problem definition, analytical approach, data management, stakeholder consideration, decision-making context, alignment with organizational goals, and communication strategy. Each criterion is evaluated on a scale from 1 (Poor) to 4 (Excellent), allowing for nuanced assessment of performance in each area.

To use this rubric effectively:

Adjust the criteria and descriptions as needed to fit your specific context or requirements.
Ensure that the expectations for each level (Excellent, Good, Fair, Poor) are clear and distinguishable.

My next steps will be to add specific examples or indicators for each level to provide more guidance to both assessors and those being assessed.

I also may, depending on internal needs, want to assign different weights to each criterion based on their relative importance in your specific context. In this case I think each ends up being pretty similar.

I would then go and add the other sections. For example, here is category B with some possible weighting.

Category B: Capturing the Risk Generating Process (RGP)

Component	Weight Factor	Excellent	Satisfactory	Needs Improvement	Poor
B1. Comprehensiveness	4	The analysis includes: i) A structured taxonomy of hazards/events demonstrating comprehensiveness ii) Each scenario spelled out with causes and types of change iii) Explicit addressing of potential “Black Swan” events iv) Clear description of implications of such events for risk management	The analysis includes 3 out of 4 elements from the Excellent criteria, with minor gaps that do not significantly impact understanding	The analysis includes only 2 out of 4 elements from the Excellent criteria, or has significant gaps in comprehensiveness	The analysis includes 1 or fewer elements from the Excellent criteria, severely lacking in comprehensiveness
B2. Basic Structure of RGP	2	Clearly identifies and accounts for the basic structure of the RGP (e.g. linear, chaotic, complex adaptive) AND Uses appropriate mathematical structures (e.g. linear, quadratic, exponential) that match the RGP structure	Identifies the basic structure of the RGP BUT does not fully align mathematical structures with the RGP	Attempts to identify the RGP structure but does so incorrectly or incompletely OR Uses mathematical structures that do not align with the RGP	Does not identify or account for the basic structure of the RGP
B3. Complexity of RGP	3	Lists all important causal and associative links in the RGP AND Demonstrates how each link is accounted for in the analysis	Lists most important causal and associative links in the RGP AND Demonstrates how most links are accounted for in the analysis	Lists some causal and associative links but misses key elements OR Does not adequately demonstrate how links are accounted for in the analysis	Does not list causal and associative links or account for them in the analysis
B4. Early Warning Detection	3	Includes a clear process for detecting early warnings of potential surprising risk aspects, beyond just concrete events	Includes a process for detecting early warnings, but it may be limited in scope or not fully developed	Mentions the need for early warning detection but does not provide a clear process	Does not address early warning detection
B5. System Changes	2	Fully considers the possibility of system changes AND Establishes adequate mechanisms to detect those changes	Considers the possibility of system changes BUT mechanisms to detect changes are not fully developed	Mentions the possibility of system changes but does not adequately consider or establish detection mechanisms	Does not consider or address the possibility of system changes

I definitely need to go back and add more around structure requirements. The SRA RAQT tool needs some more interpretation here.

Category C: Risk Communication

Component	Weight Factor	Excellent	Satisfactory	Needs Improvement	Poor
C1. Integration of Communication into Risk Analysis	3	Communication is fully integrated into the risk analysis following established norms). All aspects of the methodology are clearly addressed including context establishment, risk assessment (identification, analysis, evaluation), and risk treatment. There is clear evidence of pre-assessment, management, appraisal, characterization and evaluation. Knowledge about the risk is thoroughly categorized.	Communication is integrated into the risk analysis following most aspects of established norms. Most key elements of methodologies like ISO 31000 or IRGC are addressed, but some minor aspects may be missing or unclear. Knowledge about the risk is categorized, but may lack some detail.	Communication is partially integrated into the risk analysis, but significant aspects of established norms are missing. Only some elements of methodologies like ISO 31000 or IRGC are addressed. Knowledge categorization about the risk is incomplete or unclear.	There is little to no evidence of communication being integrated into the risk analysis following established norms. Methodologies like ISO 31000 or IRGC are not followed. Knowledge about the risk is not categorized.
C2. Adequacy of Risk Communication	3	All considerations for effective risk communication have been applied to ensure adequacy between analysts and decision makers, analysts and other stakeholders, and decision makers and stakeholders. There is clear evidence that all parties agree the communication is adequate.	Most considerations for effective risk communication have been applied. Communication appears adequate between most parties, but there may be minor gaps or areas where agreement on adequacy is not explicitly stated.	Some considerations for effective risk communication have been applied, but there are significant gaps. Communication adequacy is questionable between one or more sets of parties. There is limited evidence of agreement on communication adequacy.	Few to no considerations for effective risk communication have been applied. There is no evidence of adequate communication between analysts, decision makers, and stakeholders. There is no indication of agreement on communication adequacy.

Category D: Stakeholder Involvement

Criteria	Weight	Excellent (4)	Satisfactory (3)	Needs Improvement (2)	Poor (1)
Stakeholder Identification	4	All relevant stakeholders are systematically and comprehensively identified	Most relevant stakeholders are identified, with minor omissions	Some relevant stakeholders are identified, but significant groups are missed	Few or no relevant stakeholders are identified
Stakeholder Consultation	3	All identified stakeholders are thoroughly consulted, with their perceptions and concerns fully considered	Most identified stakeholders are consulted, with their main concerns considered	Some stakeholders are consulted, but consultation is limited in scope or depth	Few or no stakeholders are consulted
Stakeholder Engagement	3	Stakeholders are actively engaged throughout the entire risk management process, including problem framing, decision-making, and implementation	Stakeholders are engaged in most key stages of the risk management process	Stakeholders are engaged in some aspects of the risk management process, but engagement is inconsistent	Stakeholders are minimally engaged or not engaged at all in the risk management process
Effectiveness of Involvement	2	All stakeholders would agree that they were effectively consulted and engaged	Most stakeholders would agree that they were adequately consulted and engaged	Some stakeholders may feel their involvement was insufficient or ineffective	Most stakeholders would likely feel their involvement was inadequate or ineffective

Category E: Assumptions and Scope Boundary Issues

Criterion	Weight	Excellent (4)	Satisfactory (3)	Needs Improvement (2)	Poor (1)
E1. Important assumptions and implications listed	4	All important assumptions and their implications for risk management are systematically listed in clear language understandable to decision makers. Comprehensive and well-organized.	Most important assumptions and implications are listed in language generally clear to decision makers. Some minor omissions or lack of clarity.	Some important assumptions and implications are listed, but significant gaps exist. Language is not always clear to decision makers.	Few or no important assumptions and implications are listed. Language is unclear or incomprehensible to decision makers.
E2. Risks of assumption deviations evaluated	3	Risks of all significant assumptions deviating from the actual Risk Generating Process are thoroughly evaluated. Consequences and implications are clearly communicated to decision makers.	Most risks of significant assumption deviations are evaluated. Consequences and implications are generally communicated to decision makers, with minor gaps.	Some risks of assumption deviations are evaluated, but significant gaps exist. Communication to decision makers is incomplete or unclear.	Few or no risks of assumption deviations are evaluated. Little to no communication of consequences and implications to decision makers.
E3. Scope boundary issues and implications listed	3	All important scope boundary issues and their implications for risk management are systematically listed in clear language understandable to decision makers. Comprehensive and well-organized.	Most important scope boundary issues and implications are listed in language generally clear to decision makers. Some minor omissions or lack of clarity.	Some important scope boundary issues and implications are listed, but significant gaps exist. Language is not always clear to decision makers.	Few or no important scope boundary issues and implications are listed. Language is unclear or incomprehensible to decision makers.

Category F: Proactive Creation of Alternative Courses of Action

Criteria	Weight	Excellent (4)	Satisfactory (3)	Needs Improvement (2)	Poor (1)
Systematic generation of alternatives	4	A comprehensive and structured process is used to systematically generate a wide range of alternative courses of action, going well beyond initially considered options	A deliberate process is used to generate multiple alternative courses of action beyond those initially considered	Some effort is made to generate alternatives, but the process is not systematic or comprehensive	Little to no effort is made to generate alternatives beyond those initially considered
Goal-focused creation	3	All generated alternatives are clearly aligned with and directly address the stated goals of the analysis	Most generated alternatives align with the stated goals of the analysis	Some generated alternatives align with the goals, but others seem tangential or unrelated	Generated alternatives (if any) do not align with or address the stated goals
Consideration of robust/resilient options	3	Multiple robust and resilient alternatives are developed to address various uncertainty scenarios	At least one robust or resilient alternative is developed to address uncertainty	Robustness and resilience are considered, but not fully incorporated into alternatives	Robustness and resilience are not considered in alternative generation
Examination of unintended consequences	2	Thorough examination of potential unintended consequences for each alternative, including action-reaction spirals	Some examination of potential unintended consequences for most alternatives	Limited examination of unintended consequences for some alternatives	No consideration of potential unintended consequences
Documentation of alternative creation process	1	The process of alternative generation is fully documented, including rationale for each alternative	The process of alternative generation is mostly documented	The process of alternative generation is partially documented	The process of alternative generation is not documented

Category G: Basis of Knowledge

Criterion	Weight	Excellent (4)	Satisfactory (3)	Needs Improvement (2)	Poor (1)
G1. Characterization of knowledge basis	4	All inputs are clearly characterized (empirical, expert elicitation, testing, modeling, etc.). Distinctions between broadly accepted and novel analyses are explicitly stated.	Most inputs are characterized, with some minor omissions. Distinctions between accepted and novel analyses are mostly clear.	Some inputs are characterized, but significant gaps exist. Limited distinction between accepted and novel analyses.	Little to no characterization of knowledge basis. No distinction between accepted and novel analyses.
G2. Strength of knowledge adequacy	3	Strength of knowledge is thoroughly characterized in terms of its adequacy to support risk management decisions. Limitations are clearly articulated.	Strength of knowledge is mostly characterized, with some minor gaps in relating to decision support adequacy.	Limited characterization of knowledge strength. Unclear how it relates to decision support adequacy.	No characterization of knowledge strength or its adequacy for decision support.
G3. Communication of knowledge limitations	4	All knowledge limitations and their implications for risk management are clearly communicated to decision makers in understandable language.	Most knowledge limitations and implications are communicated, with minor clarity issues.	Some knowledge limitations are communicated, but significant gaps exist in clarity or completeness.	Knowledge limitations are not communicated or are presented in a way decision makers cannot understand.
G4. Consideration of surprises and unforeseen events	3	Thorough consideration of potential surprises and unforeseen events (Black Swans). Their importance is clearly articulated.	Consideration of surprises and unforeseen events is present, with some minor gaps in articulating their importance.	Limited consideration of surprises and unforeseen events. Their importance is not clearly articulated.	No consideration of surprises or unforeseen events.
G5. Conflicting expert opinions	2	All conflicting expert opinions are systematically considered and reported to decision makers as a source of uncertainty.	Most conflicting expert opinions are considered and reported, with minor omissions.	Some conflicting expert opinions are considered, but significant gaps exist in reporting or consideration.	Conflicting expert opinions are not considered or reported.
G6. Consideration of unconsidered knowledge	2	Explicit measures are implemented to check for knowledge outside the analysis group (e.g., independent review).	Some measures are in place to check for outside knowledge, but they may not be comprehensive.	Limited consideration of knowledge outside the analysis group. No formal measures in place.	No consideration of knowledge outside the analysis group.
G7. Consideration of disregarded low-probability events	1	Explicit measures are implemented to check for events disregarded due to low probabilities based on critical assumptions.	Some consideration of low-probability events, but measures may not be comprehensive.	Limited consideration of low-probability events. No formal measures in place.	No consideration of events disregarded due to low probabilities.

This rubric, once done, is a tool to guide assessment and provide feedback. It should be flexible enough to accommodate unique aspects of individual work while maintaining consistent standards across evaluations. I’d embed it in the quality approval step.

Requirements for Knowledge Management

I was recently reviewing the updated Q9(R1) Annex 1- Q8/Q9/Q10 Questions & Answers (R5) related to ICH Q9(R1) Quality Risk Management (QRM) that were approved on 30 October 2024 and what they say about knowledge management. While there are some fun new questions asked, I particularly like “Do regulatory agencies expect to see a formal knowledge management approach during inspections?”

To which the answer was: “No. There is no regulatory requirement for a formal knowledge management system. However. it is expected that knowledge from different processes and
systems is appropriately utilised. Note: ‘formal’ in this context means a structured approach using a recognised methodology or (IT-) tool, executing and documenting something in a transparent and detailed manner.”

What does appropriately utilized mean? What is the standard for determining it? The agencies are quite willing to leave that to you to figure out.

As usual I think it is valuable to agree upon a few core assumptions for what appropriate utilization of knowledge management might look like.

Accessibility and Sharing

Knowledge should be easily accessible to those who need it within the organization. This means:

Implementing centralized knowledge repositories or databases
Ensuring information is structured and organized for easy retrieval
Fostering a culture of knowledge sharing among employees

Relevance and Accuracy

Appropriately utilized knowledge is:

Up-to-date and accurate
Relevant to the specific needs of the organization and its employees
Regularly reviewed and updated to maintain its value

Integration into Processes

Knowledge should be integrated into the organization’s workflows and decision-making processes:

Incorporated into standard operating procedures
Used to inform strategic planning and problem-solving
Applied to improve efficiency and productivity

Measurable Impact

Appropriate utilization of knowledge should result in tangible benefits:

Improved decision-making
Increased productivity and efficiency
Enhanced innovation and problem-solving capabilities
Reduced duplication of efforts

Continuous Improvement

Appropriate utilization of knowledge includes a commitment to ongoing improvement:

Regular assessment of knowledge management processes
Gathering feedback from users
Adapting strategies based on changing organizational needs

Viral Risk Management

While rare, viral contamination events can have severe consequences, potentially impacting product quality, patient safety, and company reputation. And while a consent decree is a good way to grow your skills, I tend to prefer to avoid causing one to happen.

Luckily, regulatory bodies have provided comprehensive guidelines, with ICH Q5A(R2) being a cornerstone document. Let’s explore the best practices for viral risk management in biotech, drawing from ICH Q5A and other relevant guidances.

The Three Pillars of Viral Safety

ICH Q5A outlines three complementary approaches to control potential viral contamination:

Selection and testing of cell lines and raw materials
Assessment of viral clearance capacity in production processes
Testing of the product at appropriate stages for contaminating viruses

These pillars form the foundation of a robust viral safety strategy.

Cell Line and Raw Material Control

Thoroughly document the origin and history of cell lines
Implement comprehensive testing programs for cell banks, including master and working cell banks
Carefully assess and control animal-derived raw materials
Consider using chemically-defined or animal-free raw materials where possible
Implement stringent change control and quality agreements with raw material suppliers

Viral Clearance Capacity

Design manufacturing processes with multiple orthogonal viral clearance steps
Validate the effectiveness of viral clearance steps using model viruses
Aim for a cumulative viral reduction factor of at least 4 log10 per the USP guidelines
Consider both dedicated viral inactivation steps (e.g., low pH treatment) and removal steps (e.g., nanofiltration)
For continuous manufacturing, assess the impact of process dynamics on viral clearance

In-Process and Final Product Testing

Develop a comprehensive testing strategy for in-process materials and final product
Utilize state-of-the-art detection methods, including PCR and next-generation sequencing (NGS)
Consider replacing traditional in vivo assays with molecular methods where appropriate
Implement a testing program that covers a broad spectrum of potential viral contaminants

Risk-Based Approach

The revised ICH Q5A(R2) emphasizes a risk-based approach to viral safety. This involves:

Conducting thorough risk assessments of the entire manufacturing process
Identifying critical control points for viral contamination
Implementing appropriate mitigation strategies based on risk levels
Continuously monitoring and updating the risk assessment as new information becomes available

Prior knowledge, including “in-house” experience, plays a crucial role in viral risk assessment and management for biopharmaceutical manufacturing. Here’s how it can be effectively utilized:

Leveraging Historical Data

Review past viral contamination events or near-misses within the organization
Analyze trends in raw material quality and supplier performance
Evaluate the effectiveness of previous risk mitigation strategies

Process Design and Optimization

Apply lessons learned from previous manufacturing campaigns to improve process robustness
Use historical data to identify critical control points for viral contamination
Optimize viral clearance steps based on past validation studies

Cell Line Susceptibility

Use accumulated data on cell line susceptibility to various viruses to inform risk assessments
Apply knowledge of cell line behavior under different conditions to enhance contamination detection

Risk Assessment Approach

The risk assessment process should take a holistic approach, focusing on:

Raw material sourcing and testing
- Identifying high-risk materials, especially animal-derived components
- Assessing chemically-undefined components like hydrolysates and peptones
- Evaluating materials produced or stored in non-controlled environments
Cell substrate selection and characterization
- Documenting the derivation and source history of the cell line
- Testing cell banks extensively for adventitious agents
- Assessing the cell line’s susceptibility to various viruses
Process design for viral clearance
- Designing manufacturing processes with multiple orthogonal viral clearance steps
Facility design and operations
- Implementing robust cleaning and sanitization procedures
- Ensuring proper facility layout and air handling systems to prevent contamination spread
Personnel training and practices
- Training on proper gowning procedures and personal protective equipment (PPE) usage
- Policies on illness reporting and exclusion of sick employees from critical areas

Preparedness and Response

While prevention is key, being prepared for a potential contamination event is crucial:

Develop a comprehensive viral contamination response plan[6]
Regularly practice and update the response plan through mock drills
Establish clear communication channels and decision-making processes
Prepare strategies for containment, decontamination, and facility restart

Continuous Improvement

Viral risk management is an ongoing process:

Stay updated on emerging technologies and regulatory guidance
Participate in industry forums and share best practices
Invest in employee training and awareness programs
Continuously evaluate and improve viral safety strategies

By implementing these best practices and adhering to regulatory guidances like ICH Q5A, we can strive to significantly mitigate the risk of viral contamination. While no approach can guarantee absolute safety, a comprehensive, risk-based strategy that leverages cutting-edge technologies and emphasizes preparedness will go a long way in protecting patients, products, and the industry as a whole.

Process Mapping to Process Modeling – The Next Step

In the last two posts (here and here) I’ve been talking about how process mapping is a valuable set of techniques to create a visual representation of the processes within an organization. Fundamental tools, every quality professional should be fluent in them.

The next level of maturity is process modeling which involves creating a digital representation of a process that can be analyzed, simulated, and optimized. Way more comprehensive, and frankly, very very hard to do and maintain.

Process Map	Process Model	Why is this Important?
Notation ambiguous	Standardized notation convention	Standardized notation conventions for process modeling, such as Business Process Model and Notation (BPMN), drive clarity, consistency, communication and process improvements.
Precision usually lacking	As precise as needed	Precision drives model accuracy and effectiveness. Too often process maps are all over the place.
Icons (representing process components made up or loosely defined	Icons are objectively defined and standardized	The use of common modeling conventions ensures that all process creators represent models consistently, regardless of who in the organization created them.
Relationship of icons portrayed visually	Icon relationships definite and explained in annotations, process model glossary, and process narratives	Reducing ambiguity, improving standardization and easing knowledge transfer are the whole goal here. And frankly, the average process map can fall really short.
Limited to portrayal of simple ideas	Can depict appropriate complexity	We need to strive to represent complex workflows in a visually comprehensible manner, striking a balance between detail and clarity. The ability to have scalable detail cannot be undersold.
One-time snapshot	Can grow, evolve, mature	How many times have you sat down to a project and started fresh with a process map? Enough said.
May be created with simple drawing tools	Created with a tool appropriate to the need	The right tool for the right job
Difficult to use for the simplest manual simulations	May provide manual or automated process simulation	In w world of more and more automation, being able to do a good process simulation is critical.
Difficult to link with related diagram or map	Vertical and horizontal linking, showing relationships among processes and different process levels	Processes don’t stand along, they are interconnected in a variety of ways. Being able to move up and down in detail and across the process family is great for diagnosing problems.
Uses simple file storage with no inherent relationships	Uses a repository of related models within a BPM system	It is fairly common to do process maps and keep them separate, maybe in an SOP, but more often in a dozen different, unconnected places, making it difficult to put your hands on it. Process modeling maturity moves us towards a library approach, with drives knowledge management.
Appropriate for quick capture of ideas	Appropriate for any level of process capture, analysis and design	Processes are living and breathing, our tools should take that into account.

This is all about moving to a process repository and away from a document mindset. I think it is a great shame that the eQMS players don’t consider this part of their core mission. This is because most quality units don’t see this as part of their core mission. We as quality leaders should be seeing process management as critical for future success. This is all about profound knowledge and utilizing it to drive true improvements.

Validating Manufacturing Process Closure for Biotech Utilizing Single-Use Systems (SUS)

Maintaining process closure is crucial for ensuring product quality and safety in biotechnology manufacturing, especially when using single-use systems (SUS). This approach is an integral part of the contamination control strategy (CCS). To validate process closure in SUS-based biotech manufacturing, a comprehensive method is necessary, incorporating:

Risk assessment
Thorough testing
Ongoing monitoring

By employing risk analysis tools such as Hazard Analysis and Critical Control Points (HACCP) and Failure Mode and Effects Analysis (FMEA), manufacturers can identify potential weaknesses in their processes. Additionally, addressing all four layers of protection helps ensure process integrity and product safety. This risk-based approach to process closure validation is essential for maintaining the high standards required in biotechnology manufacturing, including meeting Annex 1.

Understanding Process Closure

Process closure refers to the isolation of the manufacturing process from the external environment to prevent contamination. In biotech, this is particularly crucial due to the sensitivity of biological products and the potential for microbial contamination.

The Four Layers of Protection

Throughout this process it is important to apply the four layers of protection that form the foundation of a robust contamination control strategy:

Process: The inherent ability of the process to prevent or control contamination
Equipment: The design and functionality of equipment to maintain closure
Operating Procedures: The practices and protocols followed by personnel
Production Environment: The controlled environment surrounding the process

I was discussing this with some colleagues this week (preparing for some risk assessments) and I was reminded that we really should put the Patient in at the center, the zero. Truer words have never been spoken as the patient truly is our zeroth law, the fundamental principle of the GxPs.

Key Steps for Validating Process Closure

Risk Assessment

Start with a comprehensive risk assessment using tools such as HACCP (Hazard Analysis and Critical Control Points) and FMEA (Failure Mode and Effects Analysis). It is important to remember this is not a one or another, but a multi-tiered approach where you first determine the hazards through the HACCP and then drill down into failures through an FMEA.

HACCP Approach

In the HACCP we will apply a systematic, preventative approach to identify hazards in the process with the aim to produce a documented plan to control these scenarios.

a) Conduct a hazard analysis
b) Identify Critical Control Points (CCPs)
c) Establish critical limits
d) Implement monitoring procedures
e) Define corrective actions
f) Establish verification procedures
g) Maintain documentation and records

FMEA Considerations

In the FMEA we will look for ways the process fails, focusing on the SUS components. We will evaluate failures at each level of control (process, equipment, operating procedure and environment).

Identify potential failure modes in the SUS components
Assess the severity, occurrence, and detectability of each failure mode
Calculate Risk Priority Numbers (RPN) to prioritize risks

Verification

Utilizing these risk assessments, define the user requirements specification (URS) for the SUS, focusing on critical aspects that could impact product quality and patient safety. This should include:

Process requirements (e.g. working volumes, flow rates, pressure ranges)
Material compatibility requirements
Sterility/bioburden control requirements
Leachables/extractables requirements
Integrity testing requirements
Connectivity and interface requirements

Following the ASTM E2500 approach, when we conduct the design review of the proposed SUS configuration, to evaluate how well it meets the URS, we want to ensure we cover:

Overall system design and component selection
Materials of construction
Sterilization/sanitization approach
Integrity assurance measures
Sampling and monitoring capabilities
Automation and control strategy

Circle back to the HACCP and FMEA to ensure they appropriately cover critical aspects like:

Loss of sterility/integrity
Leachables/extractables introduction
Bioburden control failures
Cross-contamination risks
Process parameter deviations

These risk assessments will define critical control parameters and acceptance criteria based on the risk assessment. These will form the basis for verification testing. We will through our verification plan have an appropriate approach to:

Verify proper installation of SUS components
Check integrity of connections and seals
Confirm correct placement of sensors and monitoring devices
Document as-built system configuration
Test system integrity under various operating conditions
Perform leak tests on connections and seals
Validate sterilization processes for SUS components
Verify functionality of critical sensors and control
Run simulated production cycles
Monitor for contamination using sensitive detection methods
Verify maintenance of sterility throughout the process
Assess product quality attributes

The verification strategy will leverage a variety of supplier documentation and internal testing.

Closure Analysis Risk Assessment (CLARA)

Acceptance and release will be to perform a detailed CLARA to:

Identify all potential points of contamination ingress
Assess the effectiveness of closure mechanisms
Evaluate the robustness of aseptic connections
Determine the impact of manual interventions on system closure

On Going Use

Coming out of our HACCP we will have a monitoring and verification plan, this will include some important aspects based on our CCPs.

Integrity Testing
- Implement routine integrity testing protocols for SUS components
- Utilize methods such as pressure decay tests or helium leak detection
- Establish acceptance criteria for integrity tests
Environmental Monitoring
- Develop a comprehensive environmental monitoring program
- Include viable and non-viable particle monitoring
- Establish alert and action limits for environmental contaminants
Operator Training and Qualification
- Develop detailed SOPs for SUS handling and assembly
- Implement a rigorous training program for operators
- Qualify operators through practical assessments
Change Control and Continuous Improvement
- Establish a robust change control process for any modifications to the SUS or process
- Regularly review and update risk assessments based on new data or changes
- Implement a continuous improvement program to enhance process closure

Leveraging the Four Layers of Protection

Throughout the validation process, ensure that each layer of protection is addressed:

Process:
- Optimize process parameters to minimize contamination risks
- Implement in-process controls to detect deviations
Equipment:
- Validate the design and functionality of SUS components
- Ensure proper integration of SUS with existing equipment
Operating Procedures:
- Develop and validate aseptic techniques for SUS handling
- Implement procedures for system assembly and disassembly
Production Environment:
- Qualify the cleanroom environment
- Validate HVAC systems and air filtration

Remember that validation is an ongoing process. Regular reviews, updates to risk assessments, and incorporation of new technologies and best practices are essential for maintaining a state of control in biotech manufacturing using single-use systems.

Connected to the Contamination Control Strategy

Closed systems are a key element of the overall contamination control strategy with closed processing and closed systems now accepted as the most effective contamination control risk mitigation strategy. I might not be able to manufacture in the woods yet, but darn if I won’t keep trying.

They serve as a primary barrier to prevent contamination from the manufacturing environment by helping to mitigate the risk of contamination by isolating the product from the surrounding environment. Closed systems are the key protective measure to prevent contamination from the manufacturing environment and cross-contamination from neighboring operations.

The risk assessments leveraged during the implementation of closed systems are a crucial part of developing an effective CCS and will communicate the (ideally) robust methods used to protect products from environmental contamination and cross-contamination. This is tied into the facility design, environmental controls, risk assessments, and overall manufacturing strategies, which are the key components of a comprehensive CCS.