I cannot believe that this is the year where the polio vaccine and fluoride in water is on the ballot.
Anyways, get out there and vote. You know what to do.

I cannot believe that this is the year where the polio vaccine and fluoride in water is on the ballot.
Anyways, get out there and vote. You know what to do.

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.
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.
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.
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
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.
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.
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.
I’m often asked where we’ll first see the real impact of AI/ML in GMP. I don’t think I’ve hidden my skepticism on the topic in the past, but people keep asking, so here’s one of the first places I think it will really impact our field.
AI algorithms, coupled with advanced sensing technology, can detect and respond to minute changes in critical parameters. I can, today, easily imagine a system that not only detects abnormal temperatures but also automatically adjusts pressure and pH levels to maintain optimal conditions to a level of responsiveness not possible in today’s automation system, with continuous monitoring of every aspect of the production process in real-time. This will drive huge gains in predictive maintenance and data-driven decision making for improved product quality through early defect detection, especially in continuous manufacturing processes.
AI and machine learning algorithms will more and more empower manufacturers to analyze complex data sets, revealing hidden patterns and trends that were previously undetectable. This deep analysis will allow for more informed decision-making and process optimization, leading to significant improvements in manufacturing efficiency. Including:
There is a lot of hype in this area, I personally do not see us as close as some would say, but we are seeing real implementations in this area, and I think we are on the cusp of some very interesting capabilities.
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:
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.
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.
Throughout this process it is important to apply the four layers of protection that form the foundation of a robust contamination control strategy:

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.
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.
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

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).
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:
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:
Circle back to the HACCP and FMEA to ensure they appropriately cover critical aspects like:
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:
The verification strategy will leverage a variety of supplier documentation and internal testing.
Acceptance and release will be to perform a detailed CLARA to:
Coming out of our HACCP we will have a monitoring and verification plan, this will include some important aspects based on our CCPs.
Throughout the validation process, ensure that each layer of protection is addressed:
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.
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.
PDCA (and it’s variants) are a pretty tried and true model for process improvement. In the PDCA model a plan is structured in four steps: P (plan) D (do) C (check) A (act). The intention is create a structured cycle that allows the process to flow in accordance with the objectives to be achieved (P), execute what was planned (D), check whether the objectives were achieved with emphasis on the verification of what went right and what went wrong (C) and identify factors of success or failure to feed a new process of planning (A).
Conceptually, the organization will be a fast turning wheel of endlessly learning from mistakes and seeking to maximize processes in order to remain forever in pursuit of strategic objectives, endlessly searching for the maximum efficiency and effectiveness of the system.

The OODA loop or cycle was designed by John R. Boyd and consists of a cycle of four phases:
Observe, Orient, Decide and Act (OODA).

While similar to the PDCA improvement of a known system making it more effective, efficient or effective (depending on the effect to be expected), the OODA strives to model a framework for situational awareness.
Boyd’s concentration on the specific set of circumstances relevant to military situations had for years meant the OODA loop has not received a lot of wide spread interest. I’ve been seeing a lot of recent adaptations of the OODA loop try to expand to address the needs of operating in volatile, uncertain, complex and ambiguous (VUCA) situations. I especially like seeing it as part of resilience and business continuity.
The OODA loop enables organizations to make faster, more informed decisions in rapidly changing environments. By continuously cycling through the observe-orient-decide-act process, organizations can respond more quickly to market crises, threats, and emerging opportunities.
The observation and orientation phases help organizations maintain a comprehensive understanding of their operating environment. This enhanced situational awareness allows us to identify trends, threats, and opportunities more effectively.
The iterative nature of the OODA loop promotes continuous learning and adaptation. This fosters a culture of flexibility and responsiveness, enabling organizations to adjust their strategies and operations as circumstances evolve.
In high-pressure situations or crises, the OODA loop provides a structured approach for rapid, effective decision-making. This can be invaluable for managing unexpected challenges or emergencies.
The OODA process encourages clear communication and coordination among team members as they move through each phase. This can lead to better team cohesion and more effective execution of strategies.
The OODA loop emphasizes the importance of observation and orientation based on current data. This promotes a data-driven culture where decisions are made based on real-time information rather than outdated assumptions.
The cyclical nature of the OODA loop supports ongoing refinement of processes and strategies. Each iteration provides feedback that can be used to improve future observations, orientations, decisions, and actions.
PDCA is typically used for long-term, systematic improvement projects, while OODA is better suited for rapid decision-making in dynamic environments. Using both allows organizations to address both strategic and tactical needs.