Driving Innovation in Drug Development and Production

The biopharmaceutical industry increasingly is embracing digital technologies, automation, and data analytics to enhance quality and expedite drug development and manufacturing. Such advances allow for precise control and optimization of complex processes through solutions ranging from artificial intelligence (AI)–driven predictive models to real-time data analysis. With improved accuracy in forecasting production outcomes, advanced digital technologies can reduce errors and boost overall efficiency.

Samsung Biologics has integrated digital-twin (DT) technology as part of its commitment to fostering innovation, enhancing transparency with clients, and increasing responsiveness during manufacturing. A DT-based approach not only boosts operational efficiency, but also increases customer satisfaction through improved process control and rapid decision-making capabilities.

Advanced Digital Solutions for Biomanufacturing

Process Simulation and Optimization: DT technology creates a virtual model of physical processes, enabling scientists to explore “what-if” scenarios and identify optimal production conditions. Simulating adjustments to nutrient feed rates or temperature settings, for instance, can help to predict impacts on cell growth and prevent production issues. A DT-based approach also significantly reduces the need for physical experiments, saving time, materials, and labor.

Tools such as computational fluid dynamics (CFD) also are critical in modeling bioreactor conditions and analyzing phenomena, such as hypoxia, that can diminish cell-culture performance. CFD models offer insights into areas such as nutrient

distribution and gas flow, enabling scientists to optimize conditions that are essential for cell growth.

Samsung Biologics has refined its upstream processes not only by performing CFD analysis, but also by integrating machine-learning (ML)–based design-of-experiments (DoE) techniques to determine optimal process parameters systematically. Such approaches enable precise adjustments in temperature profiles and nutrient strategies, ensuring consistent product quality across production cycles.

Real-Time Monitoring and Data Analysis: Real-time monitoring systems and multivariate data analysis (MVDA) have become central to modern biomanufacturing, improving scientists’ understanding of complex bioprocesses. Real-time capabilities enable operators to monitor critical process parameters (CPPs) closely, detect potential deviations, and implement measures that preempt reductions in product quality. For specific projects, Samsung Biologics scientists have applied Raman spectroscopy to monitor glucose levels in real time, automate feeding strategies, and develop models for assessing critical quality attributes (CQAs). Such approaches deepen process understanding and allow for timely adjustments, ensuring smooth operations and consistent yields across manufacturing batches.

Integrated with electronic manufacturing batch record (eMBR) systems, the Samsung Biologics client portal provides customers with near– real-time access to their process data. That feature not only enhances transparency, but also facilitates process optimization, empowering clients to make data-driven decisions throughout a production cycle.

Ongoing Innovation for Enhanced Process Control: Samsung Biologics is at the forefront of developing advanced hybrid modeling techniques, combining mechanistic models based on scientific principles with statistical models that analyze data patterns. A dual approach enhances predictive capabilities, increasing the accuracy of bioprocess simulations. For example, hybrid models can provide insights into how changes in process parameters affect cell-growth dynamics. In turn, scientists can control production conditions more effectively than they could by using conventional optimization approaches. Additional services, such as “dry-lab” simulations and model predictive control (MPC), are set to improve process control further, maintaining consistent yields even in high-variability processes.

MPC is gaining attention for its ability to navigate the complexity of modern biopharmaceutical processes. The concept represents a robust framework for maintaining product quality through real-time adjustments. By using predictive models to anticipate changes in process conditions, MPC can help biologics manufacturers to make adjustments before deviations compromise product quality. That capability aligns with the process analytical technology (PAT) initiative, which emphasizes enhanced monitoring and control strategies. Integrating MPC and PAT could provide precise control over CQAs, reducing variability in product output — an essential factor for maintaining regulatory compliance and achieving efficiency in continuous biomanufacturing processes.

Streamlining Data Management

Data-Driven Insights and Decision- Making: In Chinese hamster ovary (CHO) cell culture, many process parameters are interdependent, making it difficult to isolate their effects on yield using traditional methods. Samsung Biologics applies ML models to capture such complex relationships. The result is improved prediction of yield and quality, even with limited experimental data. By integrating real-time dashboards into its system’s user interface, Samsung Biologics enables process scientists and operators to visualize key data insights in real time. Responsive, data-driven decision-making can improve production outcomes significantly.

Samsung Biologics leverages bioprocess replicas, which combine mechanistic and data-driven methods to develop high-accuracy models of bioprocesses. Those systems are designed to facilitate forecasting and optimization, helping manufacturers to adjust process variables proactively. Such an approach not only increases process efficiency, but also enhances production quality and consistency, ensuring that therapies meet the stringent standards required in the biopharmaceutical industry.

Centralized Data Systems for Enhanced Accessibility: Samsung Biologics has implemented a centralized management system for process data. It enhances access to historical and real-time data while seamlessly integrating information from different sources. Thus, scientists can leverage a single information source to perform comprehensive data analysis and interpretation. The system also enables creation of intuitive web dashboards that facilitate collaboration with customers by providing easy access to detailed process insights.

The client portal further supports transparency by providing customers with current insights into production processes. That high level of access allows clients to monitor their projects more closely than was possible with traditional PAT and collaboration tools. As a result, customers can make informed decisions about their processes and adjust project timelines based on real-time data.

Samsung Biologics also has implemented a generative-AI platform to streamline documentation processes, such as summarizing records and drafting deviation reports. By automating such tasks, the platform increases productivity while ensuring

compliance with stringent industry regulations regarding data compliance. Continuous-learning programs ensure that staff are equipped with the skills needed to leverage digital tools effectively, fostering a culture of ongoing process improvement.

Fostering Digital Transformation

Samsung Biologics draws on the technological expertise of Samsung Electronics, particularly in AI and robotics, to drive automation and improve cost-competitiveness. Integrating AI-driven automation and robotics for material handling has optimized several stages of biomanufacturing, from raw-material management to final-product packaging. A “smart” manufacturing environment not only enhances operational efficiency, but also improves response times to production challenges, ultimately benefiting customers with faster and more reliable delivery schedules than what could be achieved with typical means.

Hybrid MPC technology plays a key role in Samsung’s smart-facility ecosystem, enabling precise control over production variables and improving yield consistency. By using robotics alongside predictive models, the company has created a manufacturing environment that can adapt to changing customer needs while maintaining a high quality standard.

Adoption of DTs, ML, and advanced process-control methods has positioned the biopharmaceutical industry for significant advancements in optimizing drug development and production. Samsung Biologics’ commitment to integrating such technologies reflects its role in shaping an efficient, data-driven biomanufacturing landscape. As the industry continues to evolve, digital innovations will be critical to making advanced treatments accessible, reducing costs, and enhancing patient care. The ongoing focus on digital transformation not only will improve companies’ operational efficiency, but also will support the industry’s broader goals of achieving sustainability and adaptability in an ever-changing market.

Seongjin Kim is lead engineer in the Digital Excellence Group at Samsung Biologics; [email protected].