Concept
A laboratory information management system (LIMS), sometimes referred to as a laboratory information system (LIS) or laboratory management system (LMS), is a software-based solution with features that support a modern laboratory's operations. Key features include—but are not limited to—workflow and data tracking support, flexible architecture, and data exchange interfaces, which fully "support its use in regulated environments". The features and uses of a LIMS have evolved over the years from simple sample tracking to an enterprise resource planning tool that manages multiple aspects of laboratory informatics. There is no useful definition of the term "LIMS" as it is used to encompass a number of different laboratory informatics components. The spread and depth of these components is highly dependent on the LIMS implementation itself. All LIMSs have a workflow component and some summary data management facilities but beyond that there are significant differences in functionality. Historically the LIMS, LIS, and process development execution system (PDES) have all performed similar functions. The term "LIMS" has tended to refer to informatics systems targeted for environmental, research, or commercial analysis such as pharmaceutical or petrochemical work. "LIS" has tended to refer to laboratory informatics systems in the forensics and clinical markets, which often required special case management tools. "PDES" has generally applied to a wider scope, including, for example, virtual manufacturing techniques, while not necessarily integrating with laboratory equipment. In recent times LIMS functionality has spread even further beyond its original purpose of sample management. Assay data management, data mining, data analysis, and electronic laboratory notebook (ELN) integration have been added to many LIMS, enabling the realization of translational medicine completely within a single software solution. Additionally, the distinction between LIMS and LIS has blurred, as many LIMS now also fully support comprehensive case-centric clinical data.