A Fortune 500 life sciences company opened a $90 million facility to manufacture viral vector gene therapies for biotech customers and wanted the site to operate as a state-of-the-art environment from day one. To get there, the company needed a better way to connect siloed systems, contextualize industrial data, and make critical information accessible across the facility.
$90M Viral vector facility built for biotech customer production
2 Core source systems prioritized in the initial UNS use case: DCS and MES
3 Next-phase deployment workstreams defined for full rollout
A diversified life sciences manufacturer had invested in a new viral vector facility, but its data environment reflected many of the same limitations found in legacy industrial architectures. Data silos separated instruments, equipment, and systems. Point-to-point integrations were cumbersome and difficult to scale, and inconsistent data formats created additional validation effort.
The operational impact was tangible. Some cleanroom data, including viral status and room status, flowed through PharmaSuite MES, while other critical data such as temperature, relative humidity, and differential pressure remained in DeltaV DCS. Once operators were gowned, they had no single way to check and monitor overall cleanroom status, increasing compliance, quality, safety, and efficiency risks.
The company wanted to explore a Unified Namespace as a better architectural model: one that could organize and standardize industrial data, bridge the gap between enterprise and shop-floor systems, and make data more broadly accessible from a centralized structure.
Stellix led a Front-End Engineering Design study to determine what it would take to implement a Unified Namespace at the new facility. Working alongside the client’s automation engineers, the team developed multiple preliminary UNS design options and assessed their technical feasibility, logical considerations, potential implementation issues, and a high-level project timeline.
As part of the study, Stellix also helped evaluate the core technology stack needed to support the architecture. That included selecting and designing an MQTT broker and Data Operations platform to receive, filter, and deliver IIoT messages, as well as evaluating IIoT-ready HMI options for real-time data visualization and monitoring throughout the facility.
To ground the design in a practical use case, Stellix defined an approach to integrate with the onsite DCS for environmental monitoring data, integrate with the MES for room-state information, and design the UNS infrastructure needed to ingest, process, and distribute data to HMIs across the site.
Within a matter of weeks, Stellix and its partners designed and specified a Unified Namespace architecture for the viral vector facility. The resulting approach harmonized legacy components while creating a stronger foundation for scalability, agility, and future innovation.
At the close of the engagement, Stellix delivered a report summarizing deployment considerations, technical prerequisites, resource estimates, and a high-level implementation schedule. The work gave the customer a clearer path toward full deployment and helped frame the business and operational value of the UNS for site leadership and manufacturing management.
The engagement gave the site a concrete architectural direction for reducing integration complexity and improving access to contextualized operational data.
It also demonstrated value early. The automation team was pleased with the work, and an internal demo to site leadership and manufacturing management was well received, with stakeholders recognizing the near-term and future benefits of the UNS approach.
The project has continued into the next phase, including full UNS software design and configuration, full DeltaV and PharmaSuite integration into production environments, and hardware design and installation planning tied to a future plant outage window.
From FEED studies through architecture, platform selection, and deployment planning, we help teams turn industrial data complexity into operational clarity.
