LABORATORY INFORMATICS GUIDE 2013 | TECHNOLOGY TRENDS ➤
data and concepts are challenged – and, when shared with others, or added to existing concepts, ideas can become innovations.
DEALING WITH DATA For laboratory informatics to provide more support for the scientific method, the opportunities are (a) in the realm of data analysis – can we use the tools to turn data into information, moving the emphasis from ‘data in’ to ‘information out’, and (b) in the area of communication – can we do more to facilitate collaboration to compensate for the declining level of face-to-face conversation? One specific feature of the new alignments
in the laboratory informatics market is the incorporation of data analysis and data visualisation tools in the product offerings. As we probe deeper into the nature of materials, organisms and processes, we are faced with increasing complexity, and our ability to derive understanding from complex data sets (big data) is lagging behind our ability to acquire the data. Up to now, laboratory informatics has mainly concentrated on gathering and organising data. The growing strategic emphasis being put on data analysis and data visualisation reflects the increased concern about ‘big data’. Turning data into useful information
starts to address a broader trend towards meeting scientific, rather than throughput requirements. In the words of Clive Higgins, VP of marketing at PerkinElmer, scientists are being confronted with the need to make informed decisions using an unprecedented volume of complex data from a multitude of sources – structured, unstructured, text, images, chemical properties, biological assays and more. Big data is a big challenge; however, with the right tools it can be the key to unlocking the important new discoveries. Matthew Segall, CEO at Optibrium, suggests
that future trends will focus more on the application of this data to guide decisions; for example, decision analysis to efficiently select the best compounds for progression, use of data for predictive modelling to guide the design of better compounds and the analysis of historical data to find the rules for early (calculated or in vitro) data that indicate a higher chance of downstream success. Collaborative use of data is also likely to increase within organisations and as pharma outsources more research. Steve Gallagher also subscribes to this view,
placing emphasis on the tools being able to apply context to data, offering visual cues and
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context to aid interpretation. Paolo Concio defines a ‘laboratory intelligence’ approach in which data discovery can replace some traditional forms of reporting by using an established data discovery tool as the engine, with a consumer-style approach to data interrogation. By linking the output to suitable social media methods of sharing, available across a range of desktop and mobile devices, requirements for information and knowledge sharing can be addressed.
THE COLLABORATION CHALLENGE This leads us on to the question of communication and collaboration, and whether social media has a role in laboratory
but within those boundaries it is up to you to go and look. Most social tools operate in a different way by exploiting ‘push’ technologies to deliver information rather than ‘pull’, i.e. you are informed of new information rather than having to go and find it. One of the consequences is that a simple ‘social tool’ such as a blog or wiki may have inherent functionality that supports sharing, alerting, and commenting that is consistent with the principles of scientific communication and debate. There are many examples of this approach among academic groups where the cost and resource demands of conventional laboratory systems preclude their use, and downloadable, cloud-based social tools offer alternative generic functionality to support the group’s scientific work. Of course, in the commercial world, there
driven in part by continual business demand for efficiency’
informatics. The potential for social tools to fulfil some of the requirements for sharing information and collaborating amongst laboratory staff dispersed over different organisational units and different geographies seems quite obvious. Sharing and collaboration are two important requirements defined in most informatics’ projects. There are a number of instances where social tools have been successfully deployed to support laboratory operations – but, in the main, these tend to be supplementary to the informatics tools themselves. By definition, multi-user laboratory
informatics systems facilitate sharing by default; their limitations are determined by the security and access control requirements within the business rules. Typically, there are some constraints on what you can see,
laboratory informatics sector, there is a sense of change in the air,
‘On reflection, and despite the conservative nature of the
are a number of challenges and concerns about IP protection, security and compliance that mean that it is unlikely that the familiar consumer social tools can fulfil a serious role in the laboratory. However, the opportunity does exist to incorporate ‘social’ functionality into commercial informatics tools on a ‘push’ rather than ‘pull’ basis, in a way that facilitates sharing, notifications and debate, if for no other reason than to eliminate email as the source of those communications, and to tie all discussion to the physically and logically project. This is a concept articulated by Steven Gallagher as a ‘collaborative workflow’, in which all information is accessible from a wiki- like tool via a single interface and which would offer ‘push’ technologies to increase awareness of new information, the achievement of specific milestones in laboratory projects, or correlations between similar types of information. On reflection, and despite the conservative
nature of the laboratory informatics sector, there is a sense of change in the air, driven in part by continual business demand for efficiency, both from a productive (throughput) and scientific perspective. The laboratory informatics market has undergone a number of realignments in the past few years; the low- level technologies offer more capability within the development process to adopt a modular approach; and the incursion of consumer technologies offers the prospect of a better user experience. The real challenge, however, is to protect the principles of the scientific method from risks associated with increasingly diverse business models, and to ensure that laboratory informatics extends its influence from laboratory throughput to scientific output. l
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