Real-Time Metabolic Monitoring in Cell and Gene Therapy Manufacturing

Cell and gene therapies (CGTs) are expanding the boundaries of modern medicine, providing new avenues for treating cancers, genetic disorders, and other complex diseases.¹ While they are promising, the broader impact of CGTs is limited by a highly complex manufacturing process, where even small variations in cell culture conditions can influence product quality and batch success.¹ As researchers and manufacturers work to make these therapies available to more patients, they seek tools that provide greater control and insight into the cell culture environment.

In this innovation spotlight, Tia Harmon, technical science liaison for PHC Corporation of North America (PHCNA), discusses the key challenges in CGT manufacturing and how in-line monitoring technologies could help improve the process.

How have emerging CGT therapies changed the way researchers approach cell culture and monitoring in the lab?

The emergence of CGTs has placed greater emphasis on reproducibility and process control in cell culture so that early research can be more easily translated to scalable production.

Researchers have a growing focus on maintaining stable and well-defined culture conditions to ensure consistency in the final material. As a result, many labs are starting to supplement traditional endpoint assays with monitoring methods that provide a more continuous insight into cell health, so that they can detect subtle changes earlier and adapt their processes as needed.

As CGT production scales up, what are some of the main bottlenecks that researchers face?

One of the main bottlenecks in scaling CGT therapy production is the highly manual and complex nature of existing workflows.¹ Many critical steps rely on skilled hands-on work, making processes costly, time consuming, and difficult to standardize. Each manipulation introduces the risk of variability, and even small differences in timing or technique can affect cell quality and yield.

Developers also recognize the need for better, more accurate monitoring. Subtle shifts in culture conditions can have a big impact on cell metabolism and differentiation. However, given that most systems still depend on manual sampling and offline measurements,¹ researchers can find it difficult to effectively track those subtle changes. This means they are often making process decisions based on limited data, which increases the risk of failed runs and the need for additional iterations.

Why is continuous, real-time monitoring of cell cultures so important for both fundamental research and CGT manufacturing compared to traditional, static measurements?

When one is working with living cells, things can change quickly. Nutrient levels, pH, and metabolic activity can all fluctuate in short periods of time, and those changes can directly influence how cells grow and behave in culture. Traditional methods that rely on taking samples at set time points only give a snapshot, meaning that a researcher will miss what’s happening between measurements. With continuous, real-time monitoring, that’s not the case—one can see shifts as they occur minute by minute.

With this deeper insight, researchers can understand immediately how cells respond to different conditions and, in a manufacturing context, intervene earlier if something starts to drift. It’s about moving from reactive to more proactive control, whether you are studying cell biology or producing therapeutic material.

What kinds of insights can scientists expect from PHCNA’s cell monitoring technologies?

We have developed a technology that gives scientists full and clear picture of what is happening with their cells incell culture. LiCellMo®* focuses on real-time metabolic monitoring, tracking glucose and lactate levels continuously to give researchers insight into the growth and differentiation behavior of their cells.² That kind of visibility can reveal early signs of stress that researchers could miss between manual sampling points.

We are also developing another technology, the small-scale cell expansion system LiCellGrow**, which is intended to take the next step. We’re designing it to measure metabolic changes in real time and adjust cell culture conditions automatically to maintain an optimal culture environment.³ The goal with both systems will be to help researchers maintain healthier, more consistent cultures to support efficient workflows and reliable experimental outcomes.

How can new monitoring technologies help researchers take their discoveries from the bench to clinical-scale manufacturing?

Bridging the gap between the bench and clinical-scale manufacturing comes down to building a successful culture process. In research, you can accommodate some variability, but in a clinical or production environment, every run needs to behave predictably. Monitoring technologies can give scientists the data they need to capture what optimal conditions look like on a smaller scale. Then, once that profile is established, it’s easier to replicate on a larger scale. Real-time data can also help researchers identify potential issues early, reducing the number of experimental iterations needed before a process is ready for transfer.

How does real-time metabolic data improve consistency and support regulatory confidence in CGT workflows?

Regulatory agencies want to see that manufacturers understand and can consistently control their CGT workflows. Continuous metabolic monitoring provides the kind of data that demonstrates both. By tracking glucose and lactate levels throughout culture, researchers can show that the process remains stable and that the cells behave as expected. That data can also highlight when and why a culture deviates, which helps define tighter control limits for future runs.

In short, having that level of visibility supports greater transparency and consistency, which in turn helps build regulatory confidence in the process.

Looking ahead, how do you see automation, data connectivity, and AI-driven analytics influencing the future of cell culture and CGT manufacturing?

Automation and digital technologies are likely going to play a much bigger role in how we manage and interpret data from cell cultures. Continuous monitoring already generates a rich stream of information, and the next step is using that data more intelligently.

As connectivity improves, monitoring instruments and control systems will increasingly work together, providing a unified view of what’s happening across an entire workflow.¹ Adding AI and analytics will help make sense of that complexity, spotting patterns, predicting changes, and potentially adjusting conditions automatically. In the future, AI could be trained on data from past runs and used to develop a “digital twin” of a cell culture process that can forecast changes and recommend, or automatically implement, adjustments.¹ Over time, these advances could reduce manual oversight, cut down on repeated runs, and help make CGT manufacturing more efficient and consistent. And that can only be a good thing.

*LiCellMo is available for purchase in the US, Canada, and select other geographies globally. For research and education use only, not for use in diagnostic procedures in the US or Canada. This product has not been approved or cleared as a medical device by the US Food and Drug Administration or Health Canada.

**Product in development. All features described are subject to change. For research purposes only.