Cell and gene therapies (CGT) are one of the most promising areas of modern medicine, with the potential to redefine treatment across multiple disease areas. It’s no surprise then that the global CGT market was estimated to be worth $7.79 billion in 2024 and projected to grow at a compound annual growth rate of 17.98 percent between 2025 and 2034.
Yet, despite the encouraging scientific progress of CGTs, so far, their broader impact has been limited by the complexity and cost of their manufacturing processes, prompting a need to refocus on the fundamentals of process control, including how cell cultures are monitored. For CGTs to reach their full therapeutic and commercial potential, lab managers must find effective ways to overcome current process challenges and improve the consistency and efficiency of production.
Here, we explore the key challenges CGT lab managers face today and outline the potential of inline monitoring to enable more consistent, scalable production.
Key challenges in the cell and gene therapy production process
The main hurdles in CGT production arise during isolation, modification, and expansion, where living cells must be grown and handled under tightly controlled conditions to ensure a reliable final product. Key challenges include:
- Workflow bottlenecks: the processes of CGT production are highly manual and labor-intensive, particularly the expansion phase, which requires a large number of skilled specialists to conduct periodic sampling for several weeks. Even slight deviations in conditions during expansion can alter growth or differentiation trajectories, making adequate visibility and control of culture conditions at this stage essential.
- High costs: the combination of labor-intensive steps and iterative adjustments required to achieve consistent outcomes makes CGT production expensive. It is estimated that the cost of a single cell therapy for one patient can be at least $100,000.
- Scalability: autologous therapies require individual processing for each patient, which limits overall manufacturing capacity and makes parallel batch production challenging. Allogeneic therapies offer greater scale potential, but biological variability in donor material can introduce inconsistencies across batches.
- Quality control: the manual nature of CGT workflows means there are high risks of introducing contaminants that can create variations in final products, which can compromise potency, delay batch release, or lead to failed runs. Differences in starting material further complicate control efforts, making it difficult to maintain uniform quality.
Current strategies for tackling CGT manufacturing challenges
To address manufacturing challenges, labs are adopting different workflow architectures designed to improve efficiency, reduce contamination risk, and increase reproducibility.
Single-use systems
Single-use technologies involve disposable culture bags and other components used for a single production cycle.⁶ By eliminating the need for cleaning and sterilization, they can reduce contamination risk and offer flexibility, allowing teams to switch quickly between products and scales. However, they increase consumable waste and costs, and still rely on manual handling, which means some contamination risk remains.
Closed automation systems
Closed automation systems perform multiple stages of CGT production within partially or fully automated environments. By reducing human and environmental exposure, they can lower contamination risk and improve batch-to-batch consistency. However, these systems can be difficult to scale because long expansion periods often occupy a unit for one patient batch at a time, meaning additional systems are needed to scale production.
Optimized, step-dependent systems
This modular approach tailors each stage of the CGT workflow to the most appropriate technology, whether single-use, manual, or automated, to balance efficiency, quality, and scalability. It offers flexibility across therapies and production volumes and allows users to refine specific steps as they scale up, helping improve product quality and manage costs. This flexibility, however, could create differences between steps, making technology transfer or standardization challenging.
While each of these approaches offers distinct strengths and limitations, maintaining quality, reproducibility, and reducing the number of iterations needed for success all depend on having timely insight into cell behavior and culture conditions. Obtaining that level of understanding requires accurate, responsive monitoring, something that is difficult to achieve through periodic sampling alone.
Inline and offline monitoring in CGT processes
Effective process monitoring is essential for maintaining consistent culture conditions. Historically, CGT workflows have relied on offline, manual sampling, where small volumes of culture are removed periodically for analysis, but this can have several drawbacks:
- Data gaps: offline measurements provide only snapshots of culture health and behavior, with long gaps between sampling, where subtle changes in cell health can go undetected. In CGT manufacturing, even slight deviations in culture conditions can affect overall product quality, so these “blind spots” can have detrimental consequences for the final therapeutic product. Taking more manual measurements to minimize gaps may lead to contamination risks, logistical hurdles, and increased environmental stress on the cell culture.
- Logistical complexities: CGT workflows require sampling at precise time points during long expansion windows, including overnight or during the weekend. This can create scheduling and staffing challenges for lab managers and increase the burden on staff.
- Contamination risks: each sampling event requires opening or disturbing the culture, increasing the chance of introducing contaminants. In CGT, where each batch may represent a single patient's cells, contamination can mean losing the entire treatment, leading to significant delays.
- Loss of material: CGT batches often begin with a limited amount of patient- or donor-derived cells. Adding reagents or markers for sample analysis reduces the amount of usable culture, which can lower the amount of viable product at the end of the process.
The benefits of inline monitoring
Inline monitoring helps address many of the limitations associated with offline, manual sampling by placing sensors directly within the culture environment to track conditions in real time. Moving from intermittent checks to continuous observation provides a clearer, uninterrupted picture of cultured cells, with several advantages.
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Continuous visibility
Inline sensors provide minute-by-minute insight into culture performance, eliminating the blind spots created by periodic sampling. Real-time monitoring of glucose and lactate levels, for example, offers a continuous readout of metabolic activity, enabling a clearer picture of culture health. With this data, researchers can detect subtle shifts as they occur and intervene before these changes impact CGT product quality, helping maintain stable conditions and reduce the number of costly iterations needed to achieve a successful run.
Improved efficiency
By reducing the need for manual sampling, inline monitoring saves time and frees staff to focus on higher-value tasks. In CGT labs, often operating under tight timelines and capacity constraints, this improved efficiency helps maintain throughput without overextending personnel resources.
Reduced contamination risks
Limiting manual sampling minimizes the frequency of culture process disturbances. In CGT manufacturing, where each batch may represent a critical treatment window, lowering contamination risk reduces the likelihood of failed runs and protects patient timelines.
The future of inline monitoring: from observation to automated control
The next generation of inline systems is moving beyond continuous measurement and enabling automated process control. Current inline monitoring systems are being designed to monitor and adjust culture conditions in response to real-time pH/dissolved oxygen (DO) readings and metabolic data, maintaining a stable environment without manual intervention.
By reducing process drift and variability introduced by human handling, automated control could enhance reproducibility and scalability of CGT production processes. As these capabilities mature, they lay the groundwork for increasingly autonomous, closed-loop CGT manufacturing systems.
Strengthening the foundations of CGT manufacturing
As the cell and gene therapy market continues to expand, improving manufacturing consistency and scalability will be critical to realizing the full therapeutic potential. New workflow designs are a step in the right direction, but fully optimizing these processes depends on how effectively these systems are monitored.
By incorporating real-time, inline monitoring, lab managers could gain a clearer view of culture performance and act sooner to correct deviations, aiding in more efficient, reproducible, and lower-cost CGT manufacturing.
