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laboratory informatics ➤

at the discovery stage with the interplay of genomics, proteomics, next-generation sequencing and biological molecule design and expression. ‘With chemistry you are repeating well-

rehearsed workflows for designing and manipulating synthetic small molecules that behave in predictable ways. With biology you have to design, produce, and test hugely complex large molecules such as DNA, RNA, siRNAs, proteins, antibodies, and even combinations of biological and synthetic compounds, against biological pathways. Biologists may also have a far more unstructured approach to experimentation than chemists, which means that the capabilities for data input as well as output has to be very flexible.’

Too much to handle? Te unstructured nature of early-stage discovery, in the biologics field especially, is something highlighted by Anthony Uzzo, Core Informatics’ president and cofounder. ‘You have to develop informatics tools that allow the scientist to think about, plan, and execute the experiment,’ he states, mirroring Denny-Gouldson’s sentiments. ‘Scientists start with an idea or an experiment, rather than a sample, which is problematic enough, but that then leads to huge libraries of samples of multiple biological types, associated with a wide range of results and metadata that are highly heterogeneous across different therapeutic fields. Consider the advanced detection technologies that are now being employed in discovery labs, such as next- generation screening (NGS) and high-content screening, and it becomes evident that the complexity and volume of data emerging from early experimentation is already too much for many legacy informatics systems to handle.’ Today’s discovery laboratories require soſtware platforms that offer a flexible

system architecture and powerful application programming interfaces (APIs) that empower the customer to be more agile, Uzzo continues. ‘We started with a highly flexible system. It’s impossible to add flexibility aſter the fact to a system – a real challenge for most other LIMS providers. Soſtware must therefore address scientists’ unique workflows and integrate with a laboratory’s existing infrastructure, without the need to write and implement custom applications. Our enterprise system has been designed to empower scientists to rapidly configure the platform to accept any workflow,

View of a typical biotherapeutic project CORE INFORMATICS’


including tracking biological sample genealogy and lineage, for example, without writing a single line of custom code. Tis means scientists can deploy applications in a matter of hours instead of the months that it can take with customised soſtware approaches.’

Efficient data analysis Core Informatics’ cloud-based Platform for Science combines LIMS, ELN, and an SDMS (scientific data management system). SDMS is an automated data capture framework that is capable of driving the integration of Core LIMS and Core ELN with any laboratory instrument or workflow. ‘SDMS enables researchers to capture data directly from a wide range of instrumentation, including plate readers, imaging systems, NGS platforms, analytical equipment and liquid handlers, and to transform that raw information and load it into the database,’ Uzzo says. ‘Tis facilitates much more efficient decision-making and data analysis than

if scientists had to manually take files off the instruments and convert them into usable data.’ It’s the combination of a LIMS, ELN, and the

SDMS infrastructure that provides the power and flexibility to handle and utilise the most complex unstructured and structured data, he believes. ‘As well as being particularly well suited to tracking samples of any type, LIMS facilitates the streamlining of data analysis into a series of workflows that can be configured to meet each laboratory’s unique needs. Unlike an ELN, which isn’t geared to producing structured reports, LIMS inherently gives the scientist the opportunity to generate structured output and perform multiparametric queries to aid decision making. But actually, what we really need to do is to change people’s perception of individual tools such as LIMS and ELN, and encourage them to think more about an integrated informatics infrastructure.’

Getting data across the firewall Te cloud-based nature of the Core Informatics Platform for Science also facilitates networking and collaboration between laboratories, Uzzo says: ‘Customers are telling us that they want to be able to work more effectively with their external collaborators. Tey come to us because their legacy systems simply don’t have the inherent ability to allow laboratories to capture results and other data from remote sites, and pull them back across their firewall into the local informatics infrastructure. We enable them to have a scalable, seamless connection with partners through a synchronous exchange of data from anywhere, on any device, at any time.’ Partnerships and outsourced contracts are

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made and broken with rapidity, and working in the cloud enables expedited provision of computing resources with less complexity of implementation and at lower cost, Uzzo concludes: ‘Te bottom line is: when it comes to choosing a vendor the proof is in the pudding – you should expect to see your data and workflows in the system in the first vendor demonstration.’

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