LABORATORY INFORMATICS
laboratory development Robert Roe reports on the Paperless Lab Academy event held in Milan on the bank of Lake Maggiore
Managing a new era in
The Paperless Lab Academy conference held this year in Milan, Italy celebrated its sixth year in 2018. With the conference held in a hotel on the bank of Lake Maggiore it was the first time the event had been held in Italy after three years in Barcelona. The event kicked off with the usual
introduction from organisers Isabel Munoz and Roberto Castelnovo, who welcomed the attendees and highlighted some key facts including a 10 per cent increase in the number of visitors. The first keynote was delivered by Pat
Pijanowski, managing director at Accenture Scientific Informatics Services (ASIS), and Dr Matt Ellis, senior manager, ASIS Europe on the potential for blockchain technology to be used in the laboratory. Pijanowski opened with quotes from
various sources highlighting the hype behind this technology in recent years quoting The Economist, who said that the technology was ‘a catalyst for global prosperity’ and Gartner who reported that ’10 per cent of global GDP will be on blockchain in 10 years. While these claims refer to the use of
blockchain as a technology underpinning the development of cryptocurrencies, the technology has other potential use cases that can help to increase the security and traceability of data. In the same way that blockchain can help to produce a secure and distributed record of transactions the technology can also be applied to laboratory systems. Blockchain allows for the creation of a
chain consisting of blocks of transactions, the order of transactions is represented by their order in the chain. Transactions cannot be modified and each participant or node keeps an identical copy of all transactions so new data can only be added by consensus between nodes.
What does this mean for the laboratory? In simple terms blockchain can be used to create a distributed database of data transactions that is secure and cannot be
28 Scientific Computing World April/May 2018
tampered with or edited after creation. This provides regulatory authorities such as the FDA with a full, chronologically ordered record of all experiments and data recorded in a laboratory for a given project. Pijanowski did note that was not
necessary for all scenarios but highlighted two potential use cases where the technology could be applied – externalisation and increased data integrity. In the case of data integrity, Pijanowski
stated that ‘replication of data across all nodes provides a reliable source of truth.’ While a network of nodes can self-verify all transactions an orgnaisation could also introduce ‘smart contracts that could be used to apply business logic and process transactions in near to real-time.’
The cost of data The following presentation, from Eric Little, chief data officer Osthus, helped to clarify the importance of recording and storing data correctly in order to maximise its use and therefore its value to an organisation. Little provided a strategy for reference
master data management ‘Meeting the Challenge to support analytics in the e-data lifecycle’ Little noted that in a world of
increasingly costly and difficult research and development pharma companies must reduce costs through better use of data that is generated within an organisation. Little stated that companies should
‘use the data you have before you generate more.’ This can be accomplished by reducing the number of re-run experiments system integration and standardisation. Little also noted that once data is
available an organisation should ‘automate as much as possible’ starting with simple reoccurring tasks such as workflows, models, query patterns and then expanding the process.
“Replication of data across all nodes provides a reliable source of truth”
‘We need to move from big data to big analysis’ stated Little. ‘It’s about making big data small data; it’s about making big data usable data.’
The importance of maintaining data integrity If costs and productivity alone do not make the case for drastic new approaches to the way in which data is recorded and stored then these changes will be enforced through regulation. One example of this can be found in the
way that new GPDR regulation will affect patient and medical data but looking into the future Mark Newton, from Heartland QA, suggests that fraud and data integrity issues may result in significant changes in the way that research data is collected, processed, and retained. Newton opened his presentation with
some facts regarding fraud in scientific research. He highlighted several examples and one article in 2017 reporting that the scale may be much larger than originally
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