Highly regulated labs must find the right balance of embracing new technologies and tools and maintaining clear compliance with the regulatory requirements. The rise of AI-enhanced tools is providing labs the opportunity to greatly change how specific aspects of their work are accomplished, but those benefits must be taken with a clear understanding of the impact on compliance. Choosing effective partners can help alleviate concerns about how to embrace the technology and remain compliant with regulatory needs.
To learn more, we talked with Kimberly Remillard, senior regulatory affairs manager at Thermo Fisher Scientific.
Q: How is the changing regulatory landscape impacting life sciences labs in their day-to-day operations?
As new technologies hit the market, new regulations follow to ensure that the technology is used in ways that protect patients and scientific data. With that, regulations are modernizing to both allow new technologies and actively encourage digitalization across laboratory and manufacturing operations. This is accelerating the adoption of connected instruments, digital workflows, and data-driven decision-making.
There’s also a growing focus on the use of AI within Good Practice (GxP) laboratories. Regulators want to ensure that AI has a clear intended use and that the right controls are in place so that efficiency gains don’t come at the expense of quality or patient safety.
With these new technologies, ensuring compliance needs to be embedded in all activities. Labs need to make sure they stay current on security requirements, updates, and validation to ensure data integrity and compliance is maintained.
Q: What are the biggest compliance challenges that labs are facing when it comes to handling documentation and dataset requirements?
Many labs are at different stages of their digitalization journey, and therefore, how they handle documentation and data entry varies from lab to lab. When labs use a combination of manual processes and digital systems that can’t “talk” to each other, it presents risks to both efficiency and data integrity. Moving to connected digital systems that are designed with compliance in mind can help reduce these risks when validated and managed appropriately. Security is one of the biggest risks to data, so staying up to date with the latest security patches or software updates is critical to maintaining a secure system and protecting data integrity.
Q: How does AI make regulatory compliance more challenging? How does it make it easier?
A: When used with care, AI can support regulatory compliance by increasing quality, efficiency, and early risk detection in laboratory operations. When labs deploy AI with appropriate oversight, it can make compliance activities more consistent and robust.
However, while regulators are actively developing guidance for the use of AI, there remains uncertainty across various regulatory frameworks. For example, the proposed EU GMP Annex 22 (EudraLex Volume 4) explicitly prohibits the use of generative AI (GenAI) and large language models (LLMs) in critical GMP applications. The proposed Annex 22 allows for use of GenAI and LLMs in non-critical GMP activities when appropriate human-in-the-loop controls are applied, making it essential for laboratories to clearly define the intended use and impact when deploying AI technologies.
In parallel, the EU AI Act applies a risk-based framework that classifies AI systems into four risk levels and primarily regulates high-risk systems. Laboratories need to understand both the intended use of their AI systems and their role as provider or deployer to determine which regulatory obligations apply.
Regulatory expectations increasingly expect labs to clearly explain how AI is used within their workflows—the data inputs, the decision logic, the training approach, its limitations, and the oversight mechanisms. Where AI is used in GMP activities, AI use must be transparent and traceable, reinforcing the need for qualified personnel operating in a human-in-the-loop model to remain accountable for scientific and quality decisions within the lab's workflow.
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Q: What does real-time compliance look like in the lab?
Compliance should be embedded into day-to-day lab workflows. By engaging in real-time compliance, labs can prove they meet standards and regulations at any moment, not just when presented with an audit. By utilizing digital systems to enforce compliance with standard operating procedures, labs can log every sample, test, and result with the date, time, and user who handled the experiment. Digital systems allow for automatically capturing and analyzing results, while also notifying staff if a step is missed, if an instrument is misaligned, or if it is out of date on calibration. When quality is built into the process in an automated digital lab, it removes the risk of manual errors and inefficiencies and helps accelerate science.
Q: What should labs look for when selecting software vendors to help them manage compliance?
When selecting a software vendor, labs should choose a vendor that prioritizes staying up to date on global regulations and software quality so their tools can accurately enable real-time compliance. Since these rules guide lab operations, electronic records and digital systems in pharma and life sciences research must be designed to support these requirements. Labs should also look to ensure that the tools are adaptable to new regulations as they emerge and support ALCOA++ data integrity throughout the lifecycle. Vendors should be able to provide appropriate development and testing evidence to support the laboratory’s software validation activities.
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Q: What regulations may be coming down the line as we look to the future regulatory landscape? How can labs remain compliant?
With technology constantly evolving, and with labs looking to further integrate AI, we can expect some of the new regulations to include changes that reflect and encourage these new technologies. We already see proposed changes to the EU GMP Annex 11 and the proposed introduction of Annex 22, and we can expect additional clarity from the US FDA on the use of AI. Overall, labs should expect to see updated security and privacy guidance across regulatory bodies. We also see this reflected in industry groups, such as the recent release of the ISPE GAMP AI Guide. As new regulations and guidance documents are proposed, it is important for labs to keep up to date and participate in the regulatory review and comment process.
Q: Are there any new things that labs should be training staff on to make this transition easier and more effective?
As regulations and new technologies evolve, staff should be informed of regulatory changes that may impact their lab operations and receive adequate training and support to operate new technologies. To make the transition from manual to digital workflows easier, ensuring that the lab is set up to incorporate new technologies seamlessly into the operations will be crucial to the success of the integration. As lab teams work with new technologies, choosing a vendor who has available support and training modules to help technicians engage with the technology will be increasingly important.
AI-enhanced workflows can greatly improve the speed, productivity, and quality of the outcomes from the lab. In highly regulated environments, it is vital to stay abreast of the regulatory requirements and adopt tools, technologies, and processes that remain compliant while delivering the needed lab improvements.
