Real-Time Cell Analysis: Advancing Cell Therapy Research Through Smart Monitoring
As more cell and gene therapies become clinically and commercially viable and market competition intensifies, the pressure to develop consistent, scalable, and tightly controlled development processes is increasing. Whether working with CAR-T cells, stem cell–derived products, or other advanced modalities, success depends not only on culturing healthy, functional cells for these therapies but also on understanding how those cells behave over time.
Yet, many labs still rely on manual sampling and endpoint testing to assess key metabolic markers that indicate cell health. This can slow decision-making, introduce risk, and limit full visibility into the critical phases of the process. Real-time cell analysis could help change that. By enabling continuous, in-line monitoring of live cultures, teams can build smarter, more data-driven approaches, from early development through to manufacturing.
The Limits of Manual Cell Culture Monitoring
Cellular energy production relies heavily on glycolysis, during which cells break down glucose and release lactate as a byproduct. Tracking these metabolites offers a valuable window into the health, viability, and metabolic state of a culture.
Traditionally, this kind of monitoring has depended on manual sampling at fixed intervals — a time-consuming approach that captures only isolated snapshots of a dynamic system. In modern cell therapy workflows, particularly when working with high-value or patient-derived material, this method presents several limitations:
- Time-consuming and labor-intensive
- Only provides snapshots, not continuous data
- Requires more frequent cleanroom and incubator access, increasing contamination risk and potentially stressing cells
- Requires manual handling and additional benchtop space for equipment
- Delays the detection of key process changes
Endpoint testing may require that cells be sampled after a set number of hours, even if that falls on an evening, weekend, or holiday. Attempts to avoid working out-of-hours may limit flexibility in defining the start time (time zero) for a culture and can lead to workflow bottlenecks.
Additionally, each sampling event requires the user to open the incubator, remove a plate, and handle the culture, thereby increasing labor, and potentially increasing the risk of contamination and temperature fluctuations.
Small delays, big consequences
Each of these limitations can have significant knock-on effects. A delayed response to glucose depletion can compromise cell expansion, while undetected lactate accumulation may lead to early cell stress or process failure. Repeated entry into the cleanroom for routine measurements increases both overhead and contamination risks, which, in a worst-case scenario, can lead to the loss of valuable or irreplaceable cell product.
In cell therapy, where starting populations may be rare or patient-specific, even minor disruptions can be extremely costly. Ultimately, manual handling creates opportunities for small deviations in process, which can cascade into variability in the final product.
How Real-time Cell Analysis Works
Real-time systems, such as the
LiCellMo live cell metabolic pathway analyzer*, enable researchers to
continuously monitor glucose and lactate levels in-line. This means monitoring takes place within the cells’ preferred culturing environment—in the incubator, under standard growth conditions, and without introducing sampling artifacts. Consequently, the data accurately reflects culture dynamics, not stress responses caused by handling.
In this way, glucose and lactate concentrations can be recorded every minute for up to 10 days, providing a complete picture of cell metabolism. Metabolic rates are also calculated, offering researchers a powerful view of how cells grow, respond, and change over time.
Continuous Insight for Culture Optimization
Importantly, continuous sets of data can help researchers:
- Pinpoint the exact timing of key biological events (e.g., activation, differentiation, stress)
- Identify the most effective window for drug exposure
- Know the ideal time to change media or harvest cells
- Track shifts that may be too minor to appear statistically relevant in endpoint-only data
Over time, these insights can help refine protocols, enhance reproducibility, and support more predictive control strategies, particularly when combined with automation or AI.
Reduced Contamination Risk and Sample Loss
Because in-line real-time cell analysis systems operate inside the incubator, there's no need to open the incubator for multiple sampling points or to access the cleanroom frequently for routine checks. This minimizes disruption, reduces the risk of contamination, and helps maintain a stable environment for the cells. In regulated or GMP-aligned settings, fewer touchpoints also support cleaner batch records and reduce audit risk.
Importantly, cells are not consumed to generate data. This allows scientists to preserve the full population of cells in each sample for downstream use, which is especially valuable when working with rare, limited, or expensive cell types. Rather than sacrificing material for measurement, researchers can continue to grow, analyze, or characterize cells with confidence that data integrity is maintained.
Simplified Workflows and Reduced Logistical Burden
Real-time cell analysis also eliminates many of the scheduling and resource challenges associated with manual sampling. There's reduced need to plan endpoint tests around inconvenient time points, such as weekends or overnight periods. Sampling frequency is less restricted by staff availability, and laboratory teams are freed from repetitive measurement tasks. All the work for the LiCellMo is done at the beginning of the experiment, with calibration steps and plate mapping.
By minimizing these manual bottlenecks, researchers can redirect their time and expertise toward higher-value activities, such as analyzing data, refining protocols or developing new experiments, while still maintaining close oversight of their cultures. For organizations running multiple workflows in parallel, the operational efficiencies can quickly add up.
Cost Efficiency Through Better Resource Use
By preserving the entire cell population for other end-point experiments and reducing the chances of contamination-related failures, continuous real-time cell analysis can support more efficient use of both materials and personnel. This could lead to cost savings over the course of a project, particularly in long-term, large-scale, or donor-limited research.
Proven Benefits and Future Potential
In applications from CAR-T to disease modeling, continuous in-line monitoring could support smarter, faster, and more efficient research—laying the foundation for tomorrow's digital bioprocessing.
Looking ahead, the combination of continuous metabolic monitoring with automation, AI, and machine learning opens the door to intelligent, closed-loop control. With sufficient data, systems could potentially begin to predict when interventions are needed to maintain cell health and adapt in real time to changing cell behavior.
Conclusion: The future of metabolic insight
As cell-based therapies continue to evolve, so must the tools we use to support them. Conventional monitoring methods have long posed challenges, from large gaps in data to contamination risks and scheduling complexity. Continuous real-time cell analysis can help address many of these issues while providing unprecedented access to real-time metabolic insight.
Whether you're refining CAR-T cell manufacturing, guiding stem cell differentiation, or modelling disease more accurately, real-time analysis may enable smarter, faster, and more efficient research. As these systems become increasingly integrated with digital technologies, they could play a crucial role in shaping the future of advanced therapy development.
*LiCellMo is available for purchase in the U.S., Canada, and select other geographies globally. For research and education use only, not for use in diagnostic procedures in the U.S. or Canada. This product has not been approved or cleared as a medical device by the U.S. Food and Drug Administration or Health Canada.