so their products can participate in the exchange. This opens the way to lab interconnectivity, communication and the exchange of data and instructions.’ In addition to the development of

its integration platform, Scitara has generated an orchestration layer that allows users ‘in a user-friendly, drag-and- drop interface type of way’, to create automated, event-driven lab workflows, Gerhardt explains. So, when an ELN, for example, requests a balance reading, this triggers a cascade of events as an automation. ‘The user will be notified to take the balance reading which, once taken, will be published as a new event, and the resulting data and metadata then moves back into the ELN,’ he explains. ‘And then it becomes feasible to execute this workflow seamlessly.’

Transforming data Keeping data in an inherently adaptable format, such as JSON, also makes it possible to transform data, agnostic to the original format, Gerhardt notes. ‘Data can be transformed, in flight, to the format required by its destination, whether that be an ELN, or an artificial intelligence and machine-learning tool. Rather than imposing standardisation on everything, our approach allows this flexible data transformation, which is enabled by taking the data out if its native format, putting it into a friendly format, such as JSON, and then transforming that data into the shape that your destination application, such as an AI tool, can ingest.’

28 Scientific Computing World Summer 2021

”Making sure that everyone is on board and engaged with change is critical”

One of the major problems with applying

data-driven R&D is that you cannot go straight to unsupervised learning models, comments Max Petersen, AVP of chemicals and materials marketing at Dotmatics. ‘You need to have some kind of supervision to train your algorithms to explain and demonstrate the data that contributes to a positive outcome, and that relies on complete, clean data.’ The ability to derive end-to-end, clean and insightful data for that learning model by interrogating a complete ecosystem of data is hampered when your informatics infrastructure is founded on different point solutions, Petersen notes. ‘It’s a foundational issue that Dotmatics has addressed through the development of its unified platform. We are driving the technology to effectively integrate all the different data types that might populate an experimental ecosystem, and so connect all the dots.’

A major challenge for data-driven R&D is the lack of high-quality data, he continues. ‘While accurate sample, analytical and physical characterisation data may exist, they are generally not helpful when analysing why or how a specific experiment contributed to the overall success of an innovation project.

This can only be achieved with a unified platform approach that links data from all disciplines together and contextualises experiments by implementing workflows and roles. This provides data insights that are otherwise impossible and helps our customers to innovate faster.’ What you can achieve using the unified platform is a more holistic data- centric view, across disciplines, so it’s possible to cross-reference disparate data from chemistry, biology, process, physical characterisation, formulation and analytical perspectives. ‘In the synthetic chemistry lab, for example, this could give the scientist a way to map a complete synthetic route, pulling out all the experimental data that would then facilitate data modelling, because you can generate a complete data framework for instructing an algorithm,’ says Petersen. The unified platform also gives labs

flexibility in the configuration of workflows, and a free hand to query all experimental data in the context of that workflow, and then visualise analyses in multiple ways. UK firm Interactive Software has

developed its Achiever Medical LIMS as a web-based platform for labs and biobanks. The software solution has been specially designed to aid lab digitalisation and regulatory compliance, from the central point of a LIMS outwards into all areas of lab and business operation. The Achiever Medical LIMS solution offers the flexibility to share and configure data from the labs on site, as well as external platforms, share data between collaborators, automate

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