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LABORATORY INFORMATICS GUIDE 2016 | ANNUAL REVIEW ➤


configurability,’ Boother continued. ‘This configurability requires no new custom coding, which means that Matrix Gemini can be adapted – without the need for programmers or IT specialists – to just about any setting where database management is required’. The software is written in Microsoft’s C#, part of the .net architecture, and this central core code remains the same, howsoever the product is configured. ‘Even if we are asked to configure it for a lottery.’ Matrix Gemini is shipped with a series


of configuration tools, and customers can go on a three-day training course and learn how to configure the product to match their requirements. Most commonly, clients will receive a tailored package from Autoscribe, and then carry out future configurations to the system in-house, as their requirements evolve. In fact, ‘90 per cent of the time, we deliver a complete turnkey solution based on user requirements, although some customers have configured the whole system from the ground up,’ Boother said. ‘What is really important for all our clients is that, because there is no requirement for custom coding at any level of configuration, customers can send their home- grown configurations to us, and we will support these at no charge, as part of their standard service package.’ Flexibility is particularly important for


multi-site and global customers, the company believes. The software can be installed at one site and configured to that site’s needs, and then rolled out to other global sites, which can then configure the system to their requirements, again, with no need for any custom coding. ‘It’s still the same central server and database, but configured on a site-specific basis to individual needs and preferences.’


ANALYSING AS WELL AS MANAGING DATA As all the above examples illustrate, powerful tools are required to manage data, whether it be in the laboratory, the mortuary, or the lottery. But managing data is only a means to an end. Ultimately, whether it be a pharmaceutical company or a food and beverage supplier, the purpose is to analyse the data and make sense of the work. So some companies are offering data analytical – not just data management – tools to try to enhance the value of what they provide to their customers. Among them are IDBS, ACD/ Labs, and The Edge. According to Paul Denny-Gouldson, VP of


strategic solutions at IDBS: ‘Today’s software for analytical science is really stuck in the dark ages compared with platforms for chemistry and biology.’ Effectively, scientists don’t have the


16 | www.scientific-computing.com/lig2016


Abbott Informatics system


ability to search and interrogate heterogeneous data from different types of analytical instrumentation. In contrast, cheminformatics packages are almost commoditised and there is mature software for managing complex biological data. Analytics, on the other hand, represents a major bottleneck for R&D organisations. IDBS and partner ACD/Labs have joined forces


to deliver what the companies say will represent an enhanced analytical sciences environment. It starts with an integration of ACD/Spectrus and IDBS’s web E-WorkBook technologies, to bring live analytical data into scientists’ ELN interface. IDBS’s ultimate goal is to develop E-WorkBook


Powerful tools are required to manage data, whether it be in the laboratory, the mortuary, or the lottery


into a single platform that offers not only an electronic laboratory notebook (ELN), but also chemistry, biology, asset data management, and data analysis software. It recognises that this is not something the company can do alone. So, for example, in May, it announced a partnership to integrate ChemAxon’s cheminformatics platform with E-WorkBook and the ActivityBase suite for high-throughput screening. It also teamed up with Neural ID, in a niche


area of preclinical development centred on cardiosafety testing, and with Osthus, to develop integration modules for offline mobile data capture, or lab request handling. Also in 2014, an agreement between IDBS and scientific data consulting firm Rancho BioSciences, allows the two firms to offer mutual customers manual data curation services for E-WorkBook products in the translational science and clinical research areas. But according to Denny-Gouldson: ‘Our aim is


not to make existing informatics infrastructures redundant, but rather to enable companies to “sweat the assets” that they already have. We need to incorporate into our platform software that broadens its capabilities. But we also need to offer tools that will allow our platform to integrate with the laboratory instrumentation, as well as other systems or IT infrastructures.’ The Edge Software Consultancy, also, offers its


flagship BioRails solution as a way of combining data management capabilities with an ELN in a single environment, and it has developed Morphit, a data analytics solution for capturing and analysing multi-dimensional study data. In a similar vein to the IDBS development, The


Edge’s BioRails can also connect with existing informatics infrastructure and bridge the gaps left by systems such as LIMS. In a further example of how informatics software is developing far beyond sample tracking and data management, Andrew Lemon, co-founder and CEO of the company, noted: ‘LIMS is very sample orientated, and if it’s not a sample that you are testing, then a LIMS doesn’t know what to do with it. In contrast, BioRails doesn’t care what you are testing. It could be a sample, or a compound, or an animal, or a target. You can configure BioRails to store whatever test data you want, and use it to request that test and then track its progress.’ The Morphit data analytics solution takes


things one stage further: ‘We have prepared Morphit binders and matching workflows in BioRails for commonly used assays,’ Lemon explains. ‘All the client needs to do is purchase the solution pack, install it locally, and teach it about the files that they are using. We are also enhancing Morphit to extend its analytical capabilities, so there is now support for pharmacokinetic modelling, for example.’





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