Roger Gaemperle, industry strategy & marketing manager – consumer packaged goods & life science EMEA at Rockwell Automation discusses the role of MES in biopharma.
Rockwell Automation
1. How do you see the role of MES evolving in the biopharma industry in the next 5 to 10 years?
“In the next five to ten years, the role of MES in biopharma will continue to evolve through stronger integration with digital ecosystems such as ERP, LIMS, QMS and IoT-enabled equipment. Real time decision making will improve through AI, powered by both historical and live factory data.
As AI and analytics develop, the need for centralised, high-quality data becomes even more important. MES is well placed to provide this. It will also support personalised medicine, manage smaller batch production and help ensure data quality, particularly when handling patient-specific information.
Cloud-based MES is becoming more common among smaller manufacturers due to its lower cost and standardised deployment, although it is less flexible. MES is also expected to support improvements in sustainability and overall efficiency.”
2. What are the most significant challenges biopharma manufacturers face when it comes to managing production data across diverse platforms and vendors?
“One of the key challenges biopharma manufacturers face is managing resource consumption data, such as energy and water use, particularly in processes like equipment washdowns. These can be environmentally harmful, and MES systems will need to better support tracking and reduction of this impact.
The shift to single use equipment can speed up production and remove the need for cleaning, especially when paired with plug and play systems. However, it also introduces new waste streams that must be managed effectively.
Another major challenge is the lack of standardisation. Without a common data model across platforms and vendors, data collection requires extra engineering effort. When both machine builders and users adopt standardised approaches, data becomes easier to access and use immediately.”
3. Can you elaborate on how MES helps bridge the gap between manufacturing and the broader digital transformation happening in biopharma?
“MES serves as the digital core that connects operational technology on the shop floor with enterprise IT systems. It bridges the gap between equipment-level data, such as PLCs, and higher-level systems like ERP, QMS, LIMS and supply chain platforms.
This role becomes even more important in personalised medicine, where manufacturing must be linked with patient-specific feedback over time. MES enables this by integrating all systems into a single data layer while ensuring sensitive data, such as patient information, remains encrypted and secure.”
4. How critical is interoperability between different MES platforms for biopharma manufacturers? Are there any best practices for achieving this?
“Interoperability between MES platforms is critical in biopharma, especially when manufacturing spans multiple sites or partners using different systems. For example, if one site produces the active ingredient and another handles filling and packing, their MES platforms must be able to communicate to maintain continuity, traceability and efficiency.
This connectivity supports faster time to market, reduces engineering effort and enables more consistent execution across locations. Best practices include adopting industry standards such as ISA 88/95, using vendor-neutral protocols like OPC UA, and implementing a centralised data lake with standardised formats. Middleware solutions can also help bridge systems and support advanced analytics and AI applications.”
5. Could you explain the importance of standardised data frameworks in manufacturing and how they benefit biopharma manufacturers in the long term?
“Standardised data frameworks are essential for improving interoperability across systems such as ERP, LMS, QMS and MES. They allow seamless integration and support plug and play capabilities at both the machine and system levels, making it easier for equipment and platforms to communicate effectively.
For biopharma manufacturers, this means faster tech transfer, simpler regulatory compliance and stronger data integrity. In the long term, these frameworks also enable the use of AI, advanced analytics and modular, flexible manufacturing, key enablers of greater agility and innovation across production environments.”