Keep An Eye On These Analytical And Monitoring Trends In 2025
A conversation with Caraugh Albany, Charlie Wakeham, and Steven Erb
The year behind us saw increasing enthusiasm for the analytical sciences as more companies explored solutions for capturing data in real time and exploiting it meaningfully.
As we look ahead to how the industry will build on progress in 2025, we asked three experts for their thoughts.
Caraugh Albany, a senior scientist at Autolus, Steven Erb of Crown Point Biotech Consulting, and Charlie Wakeham of WakeUp to Quality discuss a few key points of interest. Their answers have been lightly edited for clarity.
Emerging technologies: What emerging technologies or analytical techniques do you expect will have the most significant effect on biologic drug development in the coming year? How could these technologies improve efficiency, sensitivity, or specificity in analytical testing?
Less so emerging, but I think the continued push toward automation, both practical and digital, will continue to shape the development of cell and gene therapies (CGT), with an increased emphasis on their use in the QC setting. The manufacturing processes for many of the current cellular products often involve a lot of labor-intensive manual analytical steps, enabling potential error to occur. The combined use of automated liquid handling robots and online or inline process analytical technologies (PAT) could significantly reshape current quality control (QC) testing practices by reducing the need for human intervention and shifting the role of QC operatives toward data-driven monitoring.
For example, even a simple analytical procedure such as those used for assessing cell density and cell viability, both of which are key parameters and are performed at numerous times during manufacture, would be revolutionized using PAT. Currently, such assay(s) are prone to variability, typically involving the transfer of cells to a secondary device manually for offline analysis. Recently, in situ dielectric spectroscopy has shown promise as a PAT tool for such analysis during virus production. If successfully implemented by developers in other CGT areas, it could potentially enable real-time, continuous analysis throughout manufacture, enabling a more thorough process characterization.
Caraugh Albany, Autolus Therapeutics
I think the additional insights offered by correctly controlled and applied artificial intelligence and machine learning (AI/ML) will be the biggest game changer in analytical techniques.
Charlie Wakeham, WakeUp to Quality
Emerging technologies or modifications to existing technologies that are designed to speed up turnaround time (TAT) will have a significant impact on biologic drug development timelines. Reducing process analytics TAT improves product quality by reducing process holds and should increase process robustness. Introduction of automated analytical procedures or all in one instruments coupled with inline/online testing technologies will vastly improve process speed and can decrease assay variability. Additionally, standardizing foundational elements of currently used analytical workflows that are amenable to adaptation can speed up the introduction of methods that only require product-specific modifications.
Steven Erb, Crown Point Biotech Consulting LLC
Data: How do you envision data science and advanced analytics will further transform quality control and analytical sciences in 2024? What specific applications or use cases are you most excited about?
I think the evolving use of AI in areas such as advanced analytics will prove to have endless benefits in CGT. As we step into the era of Industry 4.0, the advantages and benefits of these technologies are immense, particularly when we consider QC and analytical sciences.
One particularly exciting application that has proven successful in the pharma industry is the use of digital twins. By creating virtual replicas of CGT processes, it’s possible to simulate and optimize various aspects of manufacturing, from cell culture to purification. This would enable process optimization, real-time monitoring, automated data collection, and documentation and support batch release decision-making. All of these can be particularly challenging in heterogeneous materials, such as cellular therapies.
Moreover, the benefits of digital twins extend beyond the laboratory; for example, as drug developers transition toward commercialization, digital twins could play a pivotal role in designing and operating scalable and risk-controlled supply chains. By simulating various scenarios and identifying potential bottlenecks, risks can be mitigated and resource allocation optimized.
Caraugh Albany, Autolus Therapeutics
AI/ML, powered by high-quality abundant and relevant data and using explainable, trained, and validated algorithms, can provide the knowledge and insights to truly close the loop between manufacturing and product quality.
It can help industry escape the trap of blaming every unknown out-of-specification result on operator error and instead allow the establishment of true root cause by analyzing trends and complex interactions within the process.
Charlie Wakeham, WakeUp to Quality
Data analysis across multiple batches with varied release and characterization assays can be cumbersome at times. Increasing the ability and accessibility of software or dashboards capable of comprehensively analyzing and visualizing data across a single batch production or against multiple runs will greatly benefit developers that struggle with variable processes. Insights from these data will help manufacturers identify out of control process parameters and unit operations.
Speaking more specifically to method development, analytical development scientists should be adopting analytical quality design to develop new or existing methods. JMP has a simplified, easy-to-use design of experiments module that increases accessibility and should promote further adoption by scientists. This is something I wish I had back in graduate school.
Steven Erb, Crown Point Biotech Consulting LLC
Digitalization: What digital tools or platforms are you exploring to enhance efficiency and decision-making? Can you share any recent examples that illustrate how digitalizing has helped — or possibly hampered — workflows?
Personally, I'm excited about the emergence of AI-based gating and analysis tools, such as BD ElastiGate. These technologies have the potential to revolutionize multi-parameter flow cytometry, addressing some of the current challenges in QC settings. Unlike more complex advancements like digital twins, AI-based gating tools are relatively straightforward to implement.
Caraugh Albany, Autolus Therapeutics
The focus is on the tools for digitalization without the essential groundwork to optimize workflows and build in both data quality and data integrity. This prevents the full benefits of digitalization being achieved.
Charlie Wakeham, WakeUp to Quality
Digitalization of process and analytical workflows will be a great benefit to biologics drug developers to increase speed, efficiency, and compliance. Being able to link process executions with analytical data and execution, including sample management, inventory control, and stability study execution, provides a comprehensive view of batch manufacture metrics ranging from reagent consumption to tracking critical process parameters. Many companies rely on paper-based quality systems and integration of the workflows necessary to manufacture a drug product into a digital package that is interconnected and talks to all functions will save in the long term on documentation errors, loss of samples, review delays, inventory deficiencies (setting alert limits for low quantities), and missed stability testing.
Some preclinical or early-phase companies may not be at a stage to invest in digitalization platform products yet, although they and midsize companies, CDMOs, and drug developers advancing to later stages should seriously consider how to move their systems to more comprehensive and compliant structures.
I have been impressed recently by L7 Informatics. They offer a full suite platform (L7/ESP) that contextualizes data at the point of execution to eliminate data silos that can enable real-time decision-making across research, manufacturing, and analytics; providing solutions to many of the aforementioned items. They’ve been able to increase efficiency gains by reducing manual processes by up to 80% and accelerate tech transfer timelines while also laying down a foundation for AI readiness. These types of digitalization platforms will become an integral part of compliant and holistic drug development.
Steven Erb, Crown Point Biotech Consulting LLC
Advanced therapies: How have analytical technology and technique kept pace with the complexity of advanced therapies? Where are the shortcomings?
In recent years, there have been huge technological advances in the field of analytics, including, for example, single-cell analysis. Such methodologies have been beneficial in the earlier research and development side of the industry. However, they have not yet managed to mitigate the QC challenges of developing advanced therapies.
CGTs are significantly more complex to manufacture than traditional small molecule and monoclonal antibodies. For example, bespoke medicines such as autologous CAR-T cell therapy are highly complex and require QC testing of each batch for clinical/commercial release, often on a patient-by-patient basis. Due to this increased demand for QC testing, there is a need to make analytical procedures higher throughput wherever possible, potentially through implementation of electronic pipettes, liquid handling systems, and similar automation technologies. However, the inherent complexity of the therapeutics has hindered the development of standardized "compendium" analytical methods and reference standards for critical assays. I also think the products’ complexity makes the development and implementation of PAT technologies additionally challenging as compared to other industries.
Caraugh Albany, Autolus Therapeutics
Much of the current analytical technology, and in particular the software used to drive the technology, is outdated and crude in its structure and operation. Vendors need to invest significantly in developing new and sophisticated solutions that leverage technological innovation, rather than promoting microscopic improvements in old tech.
Charlie Wakeham, WakeUp to Quality
Analytical technology for advanced therapies trends toward specific applications for each product, which can be diverse and complex. However, many of the methods required for advanced therapies, like cell therapy, for example, share commonalities.
Moving toward harmonization, automation, and availability of industry reagents would help keep pace. As an example, harmonization of cell count and viability methodology would be of great benefit to the industry. Increasing the availability of common substrates and reagents would benefit platforms by providing companies with the same reagents to perform potency assays. While these can be very product specific, many products have similar mechanisms of action, like cell killing and cytokine expression. In the future, I would love to see a broadly available inline flow cytometry technology to facilitate fast in-process testing for processes that culture cells.
Steven Erb, Crown Point Biotech Consulting LLC
Regulatory landscape: What key regulatory trends or challenges do you anticipate will shape the analytical and quality control landscape in 2025? How could they affect the development and approval of biologic drugs?
I anticipate the integration of AI based analytics and machine learning technologies to both shape and challenge the current regulatory landscape. Biologics are hugely complex, often heterogenous substances that present many challenges around their manufacture, administration, and even regulatory approval. Thus, AI presents a novel solution for some of these challenges.
Developers will need to balance the allure of using AI tools to identify new targets, optimize treatment protocols, and conduct in silico experiments with the limited regulatory guidance currently available. For example, regulatory agencies may require rigorous validation of AI models to assess their reliability and accuracy, but clear methods and standards for doing so are currently not well defined.
Historically, medicine personalization has been a case-by-case clinical decision. However, in the future this may become AI-driven, particularly in areas like dosing, which are currently tightly regulated. It's therefore imperative that regulatory frameworks adapt to emerging AI technologies based on their risks, benefits, and unique properties. It’s likely that rapid technological development may outpace regulatory guidelines, leading to potential bottlenecks in the approval process.
Ultimately, effective governance of any AI/ML based technology, despite being challenging, is needed to ensure patient safety. Especially in the coming years, as I speculate we will see an increasing number of regulatory submissions featuring AI-driven approaches.
Caraugh Albany, Autolus Therapeutics
I think the destructive attempts by Republicans to discredit and disrupt FDA via letters from Congress (June 21, 2024, and Oct. 18, 2024), combined with an incoming Republican president and the nomination of an anti-vaxxer as head of Health and Human Services, bodes very poorly for the future of safe, effective medicine regulation globally. FDA has always been the leader in protecting patient safety and now I fear politics will instead endanger patients.
If FDA has to focus its energies on defending itself from government detractors and on restructuring to please political pundits, then this will drastically reduce their capabilities and resources for their real task of regulating our industry.
Charlie Wakeham, WakeUp to Quality
Agencies will start expecting early adoption of analytical quality by design as prescribed by ICH Q14, and this should be encouraged so that analytical strategies are well thought out far before moving into pivotal studies. Potency assay development and drug product comparability have been significant challenges for development of ATMPs. Careful consideration of agency draft guidance related to these topics will help companies devise compliant strategies that will prevent losing time to clinical holds.
Finally, beginning in 2025, developers should be prepared for and pay close attention to potential changes to federal agencies like the FDA that might occur with the incoming new administration.
Steven Erb, Crown Point Biotech Consulting LLC
About The Experts:
Caraugh Albany is a senior scientist in the analytical development team at Autolus Therapeutics. She completed her Ph.D. at King's College London, focusing on the role of regulatory T cells in atherosclerosis.
Charlie Wakeham is the founder of WakeUp to Quality, a consultancy offering guidance and training in computerized systems quality and data integrity. Her career over 25 years has focused on GxP computerized systems and quality.
Steve Erb, Ph.D., is an independent consultant and founder of Crown Point Biotech Consulting with over 13 years of experience in CMC at small biotech and large pharma companies with experience managing CDMOs in analytical development, quality control, and technology transfer programs.