Sapio Sciences has announced that the Wellcome Sanger Institute will adopt its Informatics Platform as the central Laboratory Information Management System (LIMS) for a major laboratory transformation project. The initiative aims to replace multiple legacy LIMS solutions with Sapio’s platform, supporting large-scale genomic research and improving lab operations.
The digital transformation is being led by the Core Operations team at the Sanger Institute. This team manages cellular and genomic workflows essential to the institute’s research and data generation processes. Previously, various digital tools were used to address specific workflow needs such as sample management, storage, planning, and lab execution. However, this approach made it difficult to coordinate work across teams and limited visibility into progress for scientists.
A key objective of the project is to provide Core Operations and scientific teams with better insight into incoming work, movement through complex pipelines, resource requirements at each stage, and access to critical scientific data throughout processing. The new system will initially focus on Cellular Platforms and Genomic Platforms teams before expanding to all research groups at the institute.
Simon Moore, Chief Operating Officer at the Wellcome Sanger Institute, said: “Giving our scientists clear, reliable answers to ‘Where is my sample and where is my data?’ across complex, multi-team workflows is one of our biggest challenges. To plan and deliver their research, our scientists need confidence that sample progress and critical data are always visible and accessible. By moving to Sapio LIMS as our core platform, we can improve how we track, manage and orchestrate work; align resources; and streamline workflows. Sapio gives our scientists modern, configurable tools that keep pace with the way we do science.”
The program aims to give the Sanger Institute improved oversight of data generation progress, demand management, capacity planning, and scientific activity across its laboratories while reducing operational complexity.
