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KEYWORDS: MES/MOM, New Platforms, Industrial AI, Pharmaceuticals, Biotech
Overview
Pharmaceutical and biotech manufacturers are redefining what they expect from manufacturing execution systems (MES), also referred to as Manufacturing Operations Systems today. Genealogy, traceability, quality integration, and compliant production execution remain essential, but market differentiation is increasingly shaped by usability, contextual intelligence, integration flexibility, and the ability to support faster, better-informed decisions.
The next generation of MES will be differentiated not only by applications and compliance depth, but also by how effectively it turns validated manufacturing data into intuitive, contextual, and actionable user experiences aligned with the connected worker.
This ARC Insight examines how next-generation MES/MOM platforms are evolving into intelligent operational environments for regulated manufacturing. It focuses on role-based user experiences, manufacturing intelligence, AI-assisted decision support, digital dashboards, knowledge-centered operations, and connected-worker ecosystems, while emphasizing that these innovations must be grounded in validated data, governance, cybersecurity, and human accountability.
Sanofi’s Global MES Program
Sanofi provides a strong example of MES delivering measurable value at enterprise scale. Its MARS program, launched in 2022, is replacing paper batch records with digital electronic batch records across a global manufacturing network. As reported publicly in 2025, the program reached 25 sites, onboarded about 4,000 users, and put more than 100 digital recipes into operation. Sanofi reported a 70 percent reduction in batch review time and an 80 percent decrease in production deviations—demonstrating how a standardized, modern MES can improve execution, quality review, and the scalability of digital manufacturing across regulated operations. Source: Siemens, “Driving pharma manufacturing excellence: Sanofi, Capgemini and Siemens on scaling MES with generative AI,” September 25, 2025.
Zhejiang Medicine’s FactoryTalk PharmaSuite Deployment
Zhejiang Medicine Company offers another example of a modern MES improving both regulated operations and day-to-day user experience. Using Rockwell Automation’s FactoryTalk PharmaSuite MES, the company moved to 100 percent paperless manufacturing operations, eliminating paper SOPs, hard-copy records, and equipment and material labels. Guided electronic workflows and automated data handling reduced manual documentation and data-entry risk, while contributing to reported labor savings of 5 to 10 percent, a 46 to 75 percent reduction in batch-product review cycle time, and a 50 percent reduction in management review cycle time. Although the published case study does not quantify user satisfaction, these results suggest a simpler, more efficient experience for production and quality personnel. Source: Rockwell Automation, “Zhejiang Medicine Company Improves Compliance with MES.
Eli Lilly’s Use of Technologies to Visualize and Optimize Production
At the ISPE Boston Chapter keynote on October 7, 2026, Eli Lilly’s Scott Lindsay described a manufacturing strategy built on common, connected technologies—including SAP S/4HANA, Rockwell Automation’s PharmaSuite MES for parenteral manufacturing, Emerson Syncade MES for API operations, LabVantage LIMS, EWM, and Tulip—to standardize processes, digitize records including GMP documentation, and to create consistent, AI-ready data. Scott mentioned that with each implementation and platform, they look for ways to do it better, go faster, and increase quality and output. In one complex syringe application, Rockwell Automation’s PharmaSuite was the first platform to go live. Eli Lilly’s ability to integrate and standardize data across these systems is essential to creating consistent, AI-ready information that teams can share and use to collaborate, make better data-based decisions, improve the user experience, visibility, and collaboration, and increase manufacturing speed and output—while maintaining control through GMP procedures and oversight. Lilly uses Claude as its primary AI copilot to help employees work faster and with less effort. For operations, Lilly is developing focused AI agents on its internally built platform, guided by its Manufacturing Standards for Operational Excellence.
Eli Lilly is using AI to help with their activity so teams can understand what is happening, see work at scale, and improve observability. Lilly’s stated safeguards include human review, explainable AI recommendations linked to their sources, and security and data protection guardrails. The keynote also covered embodied AI: adding sensing and AI capabilities to existing equipment such as AGVs, and using Boston Dynamics’ Spot robot for plant inspections, including visual checks, temperature and acoustic monitoring, and identifying potential issues. Together, these examples illustrate a future in which MES, integrated data, AI, robotics, and other technologies support collaborative, efficient manufacturing while enabling user experience, operational efficiency, and a collaborative environment among humans, machines, and technologies at speed.
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