Building a Smart Laboratory 2012 Laboratory automation and laboratory informatics


informatics market has experienced two interesting developments: firstly, the previously separate LIMS and ELN sub- markets have started to overlap, causing a certain amount of confusion as a consequence of our application-centric mind-set. And secondly, a number of merger and acquisition activities have reshaped the vendor line-up, specifically in the ELN field. So what do these developments mean? Do they represent something more fundamental than just functional and commercial opportunism and present some tentative steps towards addressing the integration problem? Tere is no distinct boundary between


laboratory automation and laboratory informatics. At one extreme, lab automation can be interpreted as a field of engineering and laboratory informatics as a field of information management, but both contribute to a common objective of enhancing the efficiency of laboratory processes.


Industry evolution and trends


During the past 40 years, the development of increasingly powerful computers has played a major role in the advancement of laboratory data and information management. Initially, the high processing capabilities of computers were exploited to perform complex calculations at unprecedented speeds, oſten off-line on a company’s mainframe. Gradually, as digital technologies


progressed and with the development of the microprocessor, computers were brought into the lab and used for data acquisition and data processing. As a consequence, a number of laboratory techniques were revolutionised to such an extent that it is now difficult to believe, by modern standards, just how crude certain measurements had been and also what degree of confidence or accuracy they offered. Te cutting out and weighing of chromatography peaks to obtain quantitative data is one such example.


The LIMS market


As computers became more prevalent in the laboratory, another of their capabilities started to be exploited, i.e. their ability to manage workflow transactions. Tis led enterprising scientists to develop simple, custom computerised workflow systems to operate in conjunction with data acquisition and data processing. And that basically is how


laboratory information management systems were born. In the early 1980s, first generation commercial LIMS systems started to appear, usually based on minicomputers, and offered some basic functionality to support sample and test management, and reporting of results. A second generation of commercial LIMS


started to appear in the late 1980s, typically taking advantage of relational databases to provide more sophisticated functionality. Te development of client-server based systems represented the next (third) generation of commercial systems, taking advantage of the evolution of the personal computer. Te


“During the past 40 years, the development of increasingly powerful computers has played a major role in the advancement of laboratory data and information management”


fourth generation emerged as the internet and wireless connectivity developed, offering opportunities to extend the reach of LIMS beyond the confines of the laboratory. As LIMS products were increasingly


adopted by labs, three specific additional requirements gradually became apparent. Firstly, the need to be able to transfer data from instruments directly to the LIMS in order to avoid transcription errors; secondly, the need to manage the instrument data files from which data stored in the LIMS was derived; and thirdly, the need to handle unstructured data, graphical data and collate sample data. Tese requirements led to the development of scientific data management systems (SDMS) and electronic laboratory notebooks (ELNs). Functionally, the LIMS products have


become increasingly sophisticated through the successive generations to the point that the dividing line between LIMS and other informatics solutions has become less clear.


The ELN market


Te ELN market has been developing rapidly during the past decade, with continuing growth, but it still exhibits some degree of instability with a large number of vendors (in excess of 30 purveyors of products that purport to be an ELN) competing for market


share. As a consequence, the market suffers from some degree of ‘hype’ (see Figure 1). Just where ELNs sit on the Gartner Hype Cycle[3]


is dependent on the view you take


within your organisation and your scientific domain. Te general market position is probably somewhere around the ‘Trough of Disillusionment’, although individual vendors may occupy positions either side of this point. Te ‘Trough of Disillusionment’ can be considered to be the turning point when we’ve got past the hype and can then focus on delivering true benefit. Chemistry- based and generic ELNs are probably already beyond this point, as indeed are the majority of LIMS products. Commercial ELNs have evolved from two


approaches: discipline-specific and generic. Generic soſtware provides the architecture and tools to create and search content, and to work collaboratively in a way that satisfies the needs of almost any science-related industry. Discipline-specific ELNs are aimed at a particular market segment such as chemistry, biology or analytical. Tese systems are usually tailored to work with other discipline-specific soſtware tools. Most of the commercial ELNs offer a combination of generic and discipline-specific functionality. Te initial evolution of the ELN market


was centred on the provision of functionality to support small molecule chemistry. Most of the experimental processes associated with synthetic chemistry are well established, reasonably consistent and are well supported by desktop soſtware tools. Integrating these functions in an ELN that addresses the broader capability to create, manage and store a full experimental record was a logical progression. As a consequence, chemistry-based ELNs


exhibit a good deal of maturity. If there is segmentation in this part of the market, it is determined to some extent by the origins and scope of the available products. Some, for example, will be perceived as an enterprise- wide solution, others will have more of a focus on utility and personal productivity, whilst others will provide a generic ELN capability that accepts the integration of third-party soſtware tools. Biology, however, has presented a bigger


challenge to the ELN vendors. Te more diverse and complex nature of biological processes and outcomes creates a need to capture not just the data, but also the complex interrelationships between the data. Tis, coupled with a diverse portfolio of biology-specific soſtware tools, begs the


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