Digital Biomanufacturing for Gene Therapy Production
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Published: October 2025
Over the past few years, the biologics industry, particularly monoclonal antibody , cell and gene therapies have seen a surge in number of approvals driven by ongoing technological innovations and their ability to provide targeted treatments for various indications. However, biopharmaceutical companies face certain challenges for the production of gene therapies, including batch-to-batch variation and product validation, leading to operational inefficiency.
Digital manufacturing addresses these challenges by offering various advancements, such as real-time monitoring, data analytics, automation, process optimization and other digital tools to transform the available raw manufacturing data into actionable insights. These technologies enable the creation of uniform processes that significantly reduce the deviations in quality of each batch. As a result, digitalization is rapidly becoming an essential part in biopharmaceutical manufacturing, empowering digital biomanufacturing companies to achieve superior quality, speed and sustainability in the production of advanced therapeutics.
Traditionally, biopharmaceutical companies have hesitated to adopt cutting-edge digital technologies, such as cloud computing, artificial intelligence, machine learning and internet of things (IoT), in the field of bioprocessing. This reluctance can be attributed to the lack of technical know-how, complex regulatory requirements and a substantial financial burden associated with their adoption. However, the advantages associated with the digitalization of biomanufacturing (such as enhanced process optimization, increased staff safety, environmental sustainability, and consistent product quality) has led pharmaceutical companies to explore the potential of digital innovations / technologies in bioprocessing.
Roots Analysis has conducted an exhaustive study on Digital Biomanufacturing Market featuring the current landscape and future opportunity for the companies engaged in the digital biomanufacturing domain. In this article, we have highlighted some of the technologies pertaining to digital biomanufacturing for gene therapy production that are likely to shape the evolution of this sector.
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Trends in Digital Biomanufacturing for Gene Therapy Production that are Likely to Shape the Future Potential of the Industry
1. Digital Twin: Virtual Twins Optimizing Gene Manufacturing
The digital twin technology enables biopharmaceutical companies to create a virtual model / replica of gene therapy process. The technology leverages historical data from experiment design to simulate bioprocesses in real time. These simulations enable precise control of critical factors involved in bioprocessing, such as temperature, pH, dissolved oxygen, and agitation in real-time for better process optimization. It is worth mentioning that continuous process monitoring and predictive capabilities of digital twins can facilitate the early identification of equipment failures and maintenance requirements. This helps to reduce the overall cost of biomanufacturing while enabling more informed decision-making to address issues immediately, thus reducing downtime. For instance, Fraunhofer’ RNAuto project integrates digital twin technology to automate its cell and gene therapy manufacturing, enabling real-time quality control and process adjustments.
2. Process Analytical Technology (PAT): Continuous Analysis Ensures Product Quality of Gene Therapies
Process analytical technology (PAT) is a scientific framework employed to design and analyze gene therapy manufacturing processes through continuous, real-time monitoring of process attributes. It is worth mentioning that the United States Food and Drug Administration (USFDA) acknowledges PAT as an essential component for contemporary pharmaceutical manufacturing. The implementation of PAT within quality by design (QbD) framework enables deeper understanding of complex gene therapy bioprocesses, facilitating advanced process control through real-time data analytics. This approach improves final product quality, reduces variability, and supports scalable production of gene therapy.
3. Manufacturing Execution Systems (MES): Automated Workflow for Gene Therapy Manufacturing
Manufacturing execution systems (MES) is a digitized solution which connects, monitors and controls intricate gene therapy production processes, along with synchronizing various processes related to bioprocessing in the manufacturing facility. The primary objective of MES is to ensure successful implementation of the manufacturing operations. In order to achieve its primary goal, MES monitors and collects accurate real-time data of the complete production pipeline, end-to-end. This collated data is analyzed to identify critical conditions and optimize the processes, facilitating continuous improvements in the overall production output. Notably, in July 2025, Lonza participated in the US Biospectrum conference to showcase its MODA-ES® platform , a purpose-built manufacturing execution system designed for cell and gene therapy production. This platform digitizes and automates batch record management, enabling faster batch reviews, and scalable gene therapy manufacturing.
4. Data Analysis Software (DAS): Leveraging Analytics Software in Gene Therapy Bioprocessing
Over the last few years, the adoption of data analysis software in cell and gene therapy manufacturing has substantially increased owing to their ability to analyze and extract valuable insights from large or complex data sets. It enable companies to identify correlation between various process parameters and quality attributes, leading to increased accuracy, efficiency and reliability of the biomanufacturing process model. Further, in order to ensure the product and process quality, the data collected from various channels is evaluated at every stage of production. Regular evaluation of the process helps in the identifications of gaps in both process development and ongoing manufacturing of gene therapy. In recent years, many companies have started to integrate digital biomanufacturing for gene therapy production. For instance, MyCellHub offers a data analytics platform for cell and gene therapy production. This platform monitors critical process parameters, detects anomalies, and predicts potential quality issues, leading to reduced batch failures.
5. Single Use and Modular Manufacturing Systems: Single-Use Systems Streamline Manufacturing
Single use and modular manufacturing systems offer sterile, disposable components that eliminate the need for extensive cleaning and validation, thereby reducing contamination risks and accelerating production timelines. Notably, when integrated with process analytical technologies, single use systems allow real-time monitoring of parameters (including pH and temperature) during production. These systems offer scalability and flexible manufacturing process which enables biopharmaceutical companies to adapt rapidly to different gene therapy approaches and production scales without incurring heavy infrastructure costs. Notably, Merck integrates digital biomanufacturing for gene therapy production in its Carlsbad facility. It utilizes 16 modular cleanroom suits which are equipped with single use equipment for the manufacturing of viral vectors and gene therapy.
6. End-To-End (E2E) Digitization Systems: Digital Ecosystem for Manufacturing
E2E digitization systems focus on converting traditional paper-based processes into digital formats aimed at enhancing efficiency and compliance. These systems integrate and automate all the stages of gene therapy manufacturing from research and development (including CRISPR target selection) to manufacturing process (including bioreactor operations), through clinical outcomes and patient delivery into a unified digital framework. This holistic approach supports scalability and reduces errors in complex, patient-tailored processes.
Conclusion
Digitalization is an evolution of conventional bioprocess control, which includes transition from use of hardware sensor controllers to software estimators, along with integration of statistical analyses and mathematical modelling. The digitalization of biopharmaceutical process has tremendous potential to tackle the existing complexities in this sector, specifically related to research and development of upstream and downstream operations. Innovative technologies have become part of an important strategy for companies to future-proof their business operations and address various issues, including increasing R&D expenditure and deteriorating profit margins. Considering the current market and innovation landscape, we anticipate that various innovative technologies will be integrated with data analytics, and process and equipment modeling to form comprehensive systems, for the purpose of real-time monitoring and predictive analysis.
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