Laboratory informatics is the specialized application of information through a platform of instruments, software, and data management tools that allow scientific data to be captured, migrated, processed, and interpreted for immediate use, as well as stored, managed, and shared to support future research, development, and lab testing efforts while maximizing the efficiency of laboratory operations.
The term "laboratory informatics" has been in use at least since the early 1980s and has expanded in meaning since then. Before the advent of computer technology, information management played an important role in laboratories and research efforts of all sorts. And while today the process of information management continues to be important, laboratory informatics tends to focus more on the technology associated with that information management process.
The field itself is one which has seen significant growth as demand for fast and efficient electronic data exchange has boomed. A rapid series of technological developments have made laboratory equipment less static and more interactive, allowing large networks of integrated lab devices, computers, and telecommunications equipment to log, analyze, and distribute data. This has progressively enabled scientific research projects to move from a localized model to a more global model, one that allows "involved researchers to spend less time collecting data or waiting for information to arrive from another location, which in turn allows them to focus more on the work at hand and makes their research both faster and more efficient." Tangentially, more robust and scalable data management systems have been developed to help laboratories stay competitive. Today, this often means adopting laboratory automation solutions that are capable of being developed and deployed in an agile fashion. Additionally, the rapid rate of change in the technological (e.g., cloud-computing, big data) and environmental needs (e.g., more automated workflows) of researchers—coupled with growing competition—has led to a variety of related efforts, such as conferences and trade shows, to assist directors, managers, and researchers in better keeping up with the industry.
As of May 2019[update], market researchers such as Research and Markets have estimated the global market for laboratory informatics applications will reach $3.8 billion (U.S.) by 2024, up from roughly $2.6 billion in 2019. "The increasing need for laboratory automation; development of integrated lab informatics solutions; need to comply with regulatory requirements; and the growing demand in biobanks/biorepositories, academic research institutes, and CROs are the major factors driving the growth of the laboratory informatics market," says Research and Markets.
Sub-elements in laboratory informatics
Laboratory informatics is often modeled as a central component or hub for other branching elements of the field. However, looking at the architecture in this fashion oversimplifies the field of laboratory informatics and risks giving the false appearance that branched elements of the field have greater importance than others. Instead, a multi-layered, non-hierarchical model of these elements that places an emphasis on an individual laboratory's identified business needs may be more appropriate. A cottage industry of businesses and consultants has developed from this philosophy, helping laboratories map their informatics needs to their corporate strategy.
Yet it's difficult to deny the existence of branching elements of laboratory informatics. Many scientific pursuits require a laboratory, from medicine to astrophysics. This has led to special "sub-applications" of informatics to more specialized laboratories. Genome informatics developed as genetics laboratories sought more efficient ways to manage the large amounts of data being acquired from experiments and research. As scientists continue their pursuit of unlocking the secrets of the brain, neuroinformatics and its associated technology has developed to aid those researchers in their endeavors. And as hydrologists tackle the issues of equitable and efficient use of water for many different purposes, hydroinformatics and computational hydraulics have emerged.
These sub-applications of laboratory informatics are also discussed in ASTM International's ASTM E1578-18 Standard Guide for Laboratory Informatics. Updated in mid-2018, the standard not only covers applications of informatics to general laboratories but also to environmental, life science, medical, industrial, and public sector labs. The update brought with it new insights into laboratory informatics tools and how to integrate them into laboratory workflow, and with other hardware and software. And though relatively in their infancy in laboratory application, the revision added content about the application of the internet of things (IoT), artificial intelligence (AI), and smart objects to the laboratory.
Additional considerations in laboratory informatics
The actual processes that involve information management in the laboratory should not be overlooked. Laboratories are usually required to meet regulatory requirements that dictate what data should be managed; when it should be collected and stored; how it should be collected, used, and stored; where it should be housed; and who has access to it. This type of regulation has, of course, had an impact on the development of software in general, including laboratory informatics applications. Developers of these applications must take into account:
- audit trail implementation
- authentication protocols
- configuration management
- data backup
- data integrity
- electronic signature implementation
- information privacy
- network security
Technology of laboratory informatics
Important hardware and software systems that play a role in laboratory informatics include but are not limited to:
- Chromatography data systems (CDS)
- Electronic laboratory notebooks (ELN)
- Enterprise content management applications (ECM)
- Enterprise resource planning applications (ERP)
- Laboratory execution systems (LES)
- Laboratory information management systems (LIMS)
- Laboratory information systems (LIS)
- Manufacturing enterprise systems (MES)
- Process analytical technology (PAT)
- Scientific data management systems (SDMS)
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