Lab of the future

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Quality control (QC) labs in the biopharmaceutical industry have fallen behind the digital enablement of the manufacturing environment. Test execution is not automated, partly because a lot of lab equipment cannot yet be controlled digitally. Technicians use non-integrated systems, often with fixed user interfaces based on reports and documentation/paper rather than individualized personal user experiences; they are not guided or assisted by technology. Data is not captured automatically or consistently, and it is not exposed for external usage in a standard format, making it very difficult to use analytics to optimize outcomes. This situation can also lead to significant data integrity concerns with regulatory agencies. Technology advancements for at-line and in-line testing are not well supported.

The Lab of the Future workstream is a collaboration between 18 leading biopharmaceutical manufacturers, working with lab equipment and software vendors on a shared vision for digital technology to form the basis of the QC lab of the future. Our vision is that the lab of the future should leverage modern approaches and best practices to implement tools and technologies that maximize efficiency and performance of lab processes and operations.

This vision is explained in the Manifesto: digital technology-based capabilities for the quality control lab of the future intended to inform and educate and to be the basis for collaboration between the biomanufacturers and the vendors of lab instruments and IT/OT solutions to make the vision possible. It expresses what the user community believes needs to be enabled by technology between now and 2024. It sets out a framework to help both industrial laboratories and vendors of lab equipment and software to construct their roadmaps.

Within that overall framework, the group has prioritized a set of topics to progress together during 2020-21. Automation and data integration for lab equipment is the basis for many of the other capabilities. We’ll look at the different strategies for data aggregation and data integrity and the associated architectural partitioning and reference data foundations. There are many new opportunities (as well as challenges) with robots and cobots in the lab, and with augmented reality, virtual reality and speech interfaces leveraging AI technologies to assist users, create efficiencies, and increase ‘right first time’.

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