Typically perceived as overhead, quality control operations and laboratories in biomanufacturing are under constant scrutiny to become more effective and cost efficient. This article will explore how automation and artificial intelligence (AI) are adding pressure but also providing opportunities to increase accuracy and efficiency in the recently planned, best-in-class facilities coming online today.
What makes a best-in-class laboratory?
The key attributes of successful best-in-class laboratories emerge from a clear understanding of Lean principles, human-centric considerations, and flexibility.
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Lean principles
Lean principles—eliminating wasted effort, time, resources, movement, materials, and space—were originally developed for the Japanese automotive industry. Today, they are integral to the biomanufacturing industry worldwide and are fully relevant in QC operations.
Short-term workload volatility is often the biggest improvement opportunity in QC labs. Lean practices build on the foundation of standardized work to avoid excessive lead times or backlogs. They are also key in achieving the most efficient flow and pull of materials/samples, continuous improvement, and error prevention.
Credit: Eckert and Eckert
To enable Lean practices, the floor plan must consider key adjacencies and the amount of space needed for storage and transport. Locating people, materials, and equipment to follow logical flows reduces wasted time, effort, and movement.
Open space as opposed to siloed areas should be the default, unless there are specific needs for a controlled environment. Minimizing internal walls and separations between labs enables sharing workloads, equipment, and resources. It also enables cross-training opportunities, team building, as well as passive supervision and safety.
Human-centric considerations
A crucial but often overlooked consideration is the health and well-being of the people working in the lab. A healthy, motivated team goes hand-in-hand with operational efficiency. Health and well-being mean more than being physically healthy enough to complete a task. It includes mental, emotional, and occupational health.
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Providing a comfortable work environment in spaces that require PPE, large equipment, and/or strict temperature and exhaust requirements can be a challenge, but there are some factors that can have a significant positive impact on the space. To limit personnel’s exposure to noise and reduce heat loads within labs, heat and sound-generating equipment such as refrigerators and freezers can be placed in separate rooms. This also helps maintain optimal temperature and humidity levels, which are crucial for the proper functioning of testing equipment. Similarly, visual comfort factors such as lighting quality and glare reduction can be addressed to maximize comfort. When physical barriers are required, implementing large windows and glass walls in place of opaque walls provides transparency and a sense of awareness and connection among employees. In addition, exposure to natural light and views of the outdoors have been proven to significantly improve mood and reduce stress, which in turn boosts cognitive function and productivity.
Centralized and transparent open office and write-up areas combined with strategically located informal interaction spaces increases communication, collaboration, and supports teamwork and efficient problem solving.
Flexibility
While consistency is essential in QC labs, change is inevitable. As new breakthroughs open the door for new initiatives and workflows, it’s crucial that your facility is flexible, adaptable, and expandable.
To future-proof your facility, plan for flexible labs that can be easily reconfigured to make room for new equipment and technologies. This includes modular design and expandable spaces as well as elements like mobile lab benches and ceiling-mounted utilities.
Streamlining best-in-class labs with automation and AI
Today, there is immense potential for automation and AI to make operations leaner and more efficient. Ideally, these savings will translate to more affordable treatments and therapies. However, implementing new technologies is not always straightforward. It’s important to have a plan to effectively roll out these solutions in your lab.
Credit: Flad Architects
Developing a plan for automation
A carefully developed plan for implementing automation and digital technologies includes:
- Evaluating technologies: Identify technologies that align with lab excellence. Differentiate if the technology targets testing, in-line testing, storage and transport, or documentation.
- Understanding core operational benefits: Identify whether the technology is improving testing accuracy, capacity, contamination, data integrity, or employee health by reducing repetitive manual work. Do the benefits of this technology align with where your lab needs improvement?
- Analyzing ROI: Compare operational savings, including FTEs, energy reduction and/or cost avoidance against the capital expense. (Figure 1)
With the rapid pace that technology is advancing, implementation plans are typically developed over a timeframe of only one to three years (Figure 2). For organizations with multiple sites, it is important to consider whether the technology will be implemented at every site, only at top-tier sites, or piloted at one site.
Credit: Flad Architects
Artificial intelligence
Artificial intelligence is rapidly permeating the biomanufacturing industry. QC labs seeking to leverage its potential find themselves navigating a sea of considerations such as regulatory compliance, data quality and integrity, knowledge management, ethics and legal implications, and more.
It is important to understand that AI’s potential is not to replace humans, but to help humans do what they do more effectively. Opportunities for AI implementation in QC operations mostly fall into four categories:
- Data and image analysis
- Predictive maintenance
- Process optimization
- Automated reporting
However, many AI-driven projects fail to be implemented effectively. Often, these projects fail because they are not fully integrated into the business plan. Other reasons for failure can include:
- Data quality and integrity concerns—in the age of generative AI, hallucinations and “black box” output represent serious ramifications for labs.
- Validation and regulatory compliance issues—data is the lifeblood of AI models, but can your lab’s data serve as input? Or might that bring you out of compliance?
- Insufficient implementation team expertise / knowledge management—implementing AI in a production setting can be challenging and may require hiring external consultants.
In trying to heighten QC processes in the lab, teams must take care not to roll out technology that inadvertently undermines product quality.
Planning for success
When designing and planning a best-in-class QC laboratory, it is crucial to assemble a cross-disciplinary team of design professionals, lab operators, and subject matter experts to generate innovative ideas and solutions. Typically, the design and planning team includes architects, process architects, MEP engineers, Lean strategists, and process modeling experts.
The process should begin with an interactive session involving all stakeholders to establish a project vision and a list of aspirations. This vision should be continuously referenced throughout the design process. Guiding principles or "measures of success" must be defined for lab efficiencies, flexibility, future growth, employee health and well-being, and sustainability.
After visioning, the first step is to define testing processes and existing operational flows and adjacencies to understand how different processes and areas interact. Mapping operational flows includes defining the movement of personnel, materials, samples, and waste to identify potential bottlenecks or contamination risks.
Next, evaluating space and equipment utilization, along with automation and digitalization potential, is crucial to right-size and optimize the labs. This evaluation considers factors such as current and future testing volumes, the in-house test menu, the number of full-time equivalents, and the intended staffing model.
Industry benchmarks are also vital in planning a QC laboratory, providing standards and metrics to evaluate and compare the lab's performance against industry norms. These benchmarks help ensure the lab operates efficiently and meets quality standards.
Additionally, integrating digital software tools, such as capacity modeling and process flow simulation, can allow for rapid analysis of multiple planning scenarios with various parameters. These tools help determine the best future state and build a business case for process improvements, additional automation equipment, and staffing models. They optimize and validate operations during the initial planning and design phases and support ongoing improvements.
There is no one-size-fits-all plan for a lab to achieve optimal effectiveness. Understanding your people, processes, and technology needs will help you better recognize the benefits and costs of these opportunities to streamline lab operations.
