Samsung Biologics Digital Transformation & Smart Pharma Trends

At the JPMorgan Healthcare Conference in January 2026, Samsung Biologics CEO John Rim warned that rivals will catch up. His answer was to lead even faster. Digital work now sits at the center of that effort.

Samsung Biologics digital transformation spans simulation, plant software, analytics, and early robotics. A contract development and manufacturing organization (CDMO) runs many client processes at once. Its plants must behave the same way every time. This article explains what the company has disclosed, what works today, and what remains an ambition. 

For wider sector context, explore NextMSC's biologics market research.

Automation, AI and standardization anchor the strategy

Samsung Biologics has not published a single, comprehensive digital transformation roadmap. However, its public statements consistently highlight automation, artificial intelligence, and standardization as key strategic priorities. At the January 2026 conference, Rim identified automation, robotics, and AI as core pillars for addressing major supply chain challenges. The previous week, he attended CES 2026 in Las Vegas to explore advances in AI-driven manufacturing.

Standardization is another important priority that receives less attention than emerging technologies. The company's ExellenS framework builds on standardized facility designs, manufacturing processes, and digital technologies. According to Samsung Biologics, this framework helps maintain operational consistency and manufacturing readiness across its production network.

The company's expanding manufacturing capacity further increases the importance of these priorities. Including the 60,000-liter Rockville facility acquired in December, its total manufacturing capacity is expected to reach 845,000 liters. Managing consistency across a larger network requires stronger coordination, standardized processes, and greater reliance on digital systems.

What does a digital twin actually model?

A digital twin can be compared to a flight simulator for a bioreactor. It allows scientists and engineers to evaluate process changes in a virtual environment before implementing them in actual production. This approach helps teams understand potential outcomes while reducing the risks associated with changes to live manufacturing processes.

Samsung Biologics uses three main methods to develop its digital twins. Computational fluid dynamics models hydrodynamic conditions within bioreactors, mechanistic simulation evaluates biological processes, including cell growth and nutrient consumption, and multivariate data analysis uses manufacturing data to identify patterns and generate process forecasts.

The company describes its digital twin environment as more than a single simulation model. Its October 2026 article outlines an integrated approach that connects manufacturing data with process monitoring, simulation, predictive modelling, and emerging AI capabilities. The ExellenS framework reduces avoidable differences between manufacturing facilities, while digital twin technologies help monitor and manage the variations that remain.

Plant 5 demonstrates the practical application of this technology. A July 2026 report states that the facility uses digital twin technology across its operations to accelerate technology transfer. This approach supports more consistent process implementation and helps improve manufacturing readiness.

Paper-on-glass gave way to a connected plant

Samsung Biologics considers its manufacturing execution system (MES) the foundation of its smart manufacturing strategy. Its digital manufacturing journey has progressed through several stages, moving from paper-based processes towards integrated production management.

• MES programme launch in 2019: The company introduced its MES programme to reduce inefficiencies associated with paper-based documentation and minimize manual errors.

• Paperless electronic batch records: Plants 1 to 4 adopted electronic batch records (eBR) through a paper-on-glass approach. This system transferred conventional paper-based documentation into digital formats accessible through electronic screens.

• Full MES 1.0 implementation at Plant 5: Opened in April 2025, Plant 5 became the company's first facility to adopt MES 1.0 across its manufacturing operations.

The MES infrastructure subsequently expanded to connect with enterprise resource planning, laboratory information management, and process control systems. Samsung Biologics states that these integrations support more targeted reviews, faster deviation investigations, and greater confidence in batch release decisions.

Beyond digital documentation, the company is pursuing broader manufacturing automation. Its priorities include synchronized process automation, automated material handling, MES-driven production scheduling, and advanced equipment control. However, the company has not publicly confirmed an EBR 2.0 release or a dedicated AI-based deviation management tool. These developments should therefore be treated as potential areas of future advancement rather than established capabilities.

Where does AI help, and where does it stop?

Samsung Biologics has maintained a relatively focused position on the role of AI in manufacturing. A July 2026 report states that Plant 5 connects MES production data with QES quality data and applies AI to these datasets in real time. The same report indicates that manufacturing AI applications are also being implemented at the Rockville facility.

A 2026 industry roundtable provides further insight into the company's approach. Hongwoo Joo, Director of Digital Excellence at Samsung Biologics, emphasized the importance of technologies that improve data reliability and strengthen process understanding. He explained that the greatest value comes from tools that support human decision-making rather than attempting to replace it.

Generative AI represents another emerging area of interest. A September 2025 newsletter featuring a Samsung Biologics article identifies potential applications in regulatory compliance, quality assurance, and operational efficiency. However, the publicly available material reviewed for this article does not provide measurable implementation results or confirmed commercial outcomes from these applications.

Predictive models are learning to explain themselves

A June 2026 whitepaper on real-time analytics and predictive control in biomanufacturing explains how Samsung Biologics combines multiple analytical technologies to improve process monitoring. These include multivariate data analysis, predictive modelling, and explainable AI. Raman spectroscopy, a process analytical technology, provides real-time measurements that help monitor manufacturing conditions.

Explainability is essential because scientists and process engineers must understand the basis of a prediction before making operational decisions. SHAP-based interpretation helps identify which process variables influence a model's output. Engineers can use these insights to connect model-generated alerts with actual manufacturing conditions.

This approach helps teams understand not only when a production batch begins to deviate from expected conditions but also which underlying variables may be responsible. As a result, predictive analytics can provide more actionable insights for process monitoring and quality management.

The whitepaper also discusses the development of hybrid digital twins that combine mechanistic and data-driven models. These models bring together established scientific principles and real-time manufacturing data. This development represents a shift towards predictive systems that can explain their outputs and provide stronger support for technical decision-making.

Are humanoid robots coming to biopharmaceutical manufacturing?

Samsung Biologics has demonstrated interest in manufacturing robotics, but its public disclosures do not establish the commercial deployment of humanoid robots on production floors. The available information points to two distinct areas of development.

Established automation initiatives

The company identifies automated mobile robots, automated guided vehicles, and smart storage systems as technologies that can reduce material handling bottlenecks. These solutions support the movement and storage of materials while improving coordination across manufacturing facilities.

A September 2025 newsletter also highlights automated visual inspection. This approach combines robotics, imaging technologies, and defect recognition software to support inspection activities and improve manufacturing quality control.

Exploratory robotics applications

A July 2026 report states that Samsung Biologics is exploring the potential use of humanoid robots on its production floors. However, the available sources do not confirm a commercial deployment or an established implementation timeline.

Developments across the wider Samsung Group also provide relevant context. Samsung Electronics established a robotics division in July 2026 as part of its broader push into physical AI. However, this initiative belongs to Samsung Electronics and should not be interpreted as a direct investment or deployment initiative by Samsung Biologics.

Client data runs on the same pipes as production data

Samsung Biologics is developing an integrated data environment in which manufacturing information can support multiple operational and client-facing applications. According to its October 2026 article, manufacturing, process, quality, and batch context data are collected from different sources. Centralized systems then make this information available to digital twin platforms, AI models, monitoring applications, and client data-sharing systems.

This integration is particularly important for a contract development and manufacturing organization (CDMO). Pharmaceutical customers require reliable visibility into their products and manufacturing batches. Connected digital infrastructure helps provide access to relevant production information while supporting transparency across client relationships.

The June 2026 whitepaper also identifies secure data-sharing environments as an important development for improving transparency among manufacturing stakeholders. Such systems can help strengthen information exchange while maintaining appropriate controls over sensitive manufacturing and quality data.

Reducing manual data collection is another part of this transformation. At Bio Campus II, digital systems already collect and analyse manufacturing information automatically, allowing employees to access operational data in real time. Samsung Biologics is also working to reduce manual data collection across its wider manufacturing network. This direction supports more consistent data availability and creates a stronger foundation for advanced analytics and AI-driven manufacturing.

What should readers watch next?

Samsung Biologics' digital transformation priorities are reflected across company articles, technical reports, and conference discussions. However, the level of implementation varies across these initiatives. The following table summarizes the company's publicly disclosed progress and indicates which technologies are established, emerging, or still exploratory.

Quick answers on eBR and ALCOA++

What is an electronic batch record?

An electronic batch record (eBR) is the digital equivalent of a paper-based batch record used in regulated manufacturing. It documents the production activities and confirms whether each step in the master production record has been completed for a specific batch. Simply converting a paper document into a digital image does not constitute a fully functional eBR system. The electronic record system must be validated and comply with applicable regulatory requirements, including 21 CFR Part 11 where relevant.

What is ALCOA++?

ALCOA++ is a data integrity framework used in regulated pharmaceutical manufacturing. It extends the original ALCOA principles to include additional expectations for maintaining reliable and trustworthy records. Samsung Biologics engineers highlight traceability and contemporaneity as important considerations when addressing the limitations of paper-based documentation. Contemporaneity requires manufacturing data to be recorded at the time the activity takes place, while traceability ensures that records can be followed and verified throughout their lifecycle.

Where Samsung Biologics stands today

Samsung Biologics is advancing its digital transformation through a combination of established manufacturing systems and emerging technologies. Digital twins, manufacturing execution systems, and integrated data analytics have the clearest publicly documented applications. AI-driven manufacturing and predictive analytics are gaining traction, while humanoid robotics remains at an exploratory stage.

The company's approach indicates that digital transformation involves more than introducing advanced technologies. It also requires standardized processes, reliable data infrastructure, and connected manufacturing operations. For biopharmaceutical manufacturers and CDMOs, these capabilities will remain important indicators of operational efficiency, product quality, and manufacturing scalability.