Planning your lab
Building a Smart Laboratory 2018
‘eConnect, eDecide, eManage, eArchive’
The key layers of a laboratory paperless strategy
Isabel Muñoz-Willery and Roberto Castelnovo, of NL42 Consulting, highlight the importance of developing a robust strategy for the adoption paperless laboratory operations
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will be discussed in detail at the Paperless Lab Academy 2018. Te annual European event aims to become a learning platform for anyone looking to consolidate, integrate or simplify their data management systems.
n the new era of the internet of things and artificial intelligence, the majority of laboratories still have a long way to move from paper-based processes to paperless
ones. Te electronic data life cycle, as it is
described in several regulations and documents used in paperless projects, can be divided in four layers of data, information and activities: eConnect; eManage; eDecide and eArchive. Tese keywords refer to initial capture of
data, the data management to create useful information, the decisions taken based on information and data available in the lower layers and, finally, the electronic data archiving to ensure long-term availability of the information and the related data. Tose are the four-main streams that
‘eConnect’: effective workflows based on self-documenting data capture strategies
Even if data integrity is a critical aspect of the entire data life cycle, data capture requires a strong focus from both the inspectors and auditors. Most lab instruments are now offered with intelligent soſtware embedded into them. Labware and sensors are beginning to embrace the internet of things, ensuring the collection of the raw data and the related metadata which can then be transferred to the next phase of the data life cycle. Several laboratories are using instruments
which are not able to connect the current platforms. While searching for the business justification for their replacement, intermediate solutions should be considered to generate digital inputs and reduce paper-based processes and
manual transcriptions. Te goal is to reduce the manual documentation, the risk of human errors, and more importantly, to maintain the information about the source that has generated the raw data. Te raw data may be a critical part of the
activities performed in the systems of the upper layers. Data management and the creation of meaningful information and decisions should be always taken with the possibility to go back to the original data from the system in which it was generated. Finally, while in this first stage of collecting
data we should not obviate the ones coming from collaborators. Collaborators are generators of data and potential sources of information. If external organisations such as academic contributors or outsourced services from CRO and CMO are generating the data, it can create immediate security concerns. With the latest GDPR considerations, we need to incorporate data protection assessment at least on the most vulnerable data. By May 2018, companies will need to design their processes and also include serious considerations on cybersecurity protection to avoid any risk in losing data.
www.scientific-computing.com/BASL2018
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