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An introduction to Building a Smart Laboratory 2017


Choosing the right soſtware can be a complex task but this introduction aims to illuminate the options available to laboratory users.


Today we live in a world that is reliant on technology to connect people and help them to share ideas and even collaborate on projects from opposite ends of the world. Tis is also true in the laboratory, as users can now make use of technologies that not only record samples and experimental data, but also deliver connectivity and scope for collaboration on an unprecedented scale. Tis year’s Building a Smart Laboratory (BASL) aims to highlight the technologies available to the modern lab manager, allowing them to make informed decisions when deploying the latest laboratory informatics technologies. Collaboration is easier than it has ever been.


But the options available to bring technology into the laboratory can make it complicated for veterans and new users alike, who must make key decisions about whether to stick with legacy technologies or to adopt the next generation of informatics’ soſtware and all of the advantages that this delivers.


Making the right choice


To accurately select the right tools for a particular laboratory or set of workflows requires a cost/benefit analysis which must consider the functionality already provided


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by legacy applications, future workflows – as well as business justifications. It is of the utmost importance for laboratory managers to understand the role of a laboratory and how this might change in the future. In the past, many organisations have treated


the laboratory as a necessary cost centre. Only by becoming smart – as this guide


outlines – can lab managers change that mind- set and generate the neccesary value from a laboratory infrastructure. Many laboratory operations are still


predominantly paper-based. Even with the enormous potential to reduce data integrity for compliance, to make global efficiency gains


“Going digital in the laboratory has been a relatively slow process”


in manufacturing and to increase knowledge sharing, the barriers to implementing successful electronic integrated processes oſten remain a bridge too far.


Paperless or less paper?


Data-intensive science is becoming far more mainstream; however, going digital in the laboratory has been a relatively slow process. More than 75 per cent of laboratory analysis starts with a manual process such as weighing; the majority of results of these measurements are


still written down or re-typed into a spreadsheet or electronic document. Tere are exceptions: probably the best


example of integrated laboratory automation can be found in how chromatography data handling systems (CDS) operate in modern laboratories. Te characteristics of such a system include repeatable, oſten standardised, automated processes that create a significant amount of raw and processed data.


New trends


Te power of life cycle process improvement Te scientist is no longer in the laboratory but integrated into the overall quality process. Quality should be built into the design throughout the specification, design, and verification process. Performance metrics on non-conformance tracking are mandated and monitored by regulatory authorities. Integrating laboratory systems will add significant value by decreasing non-conformance.


New budgeting and licensing models Managing operating budgets will be redefined in the next decade. Te days of purchasing soſtware as a capital investment (CAPEX) are changing to a new model based on a ‘pay-as-you-go’ or operational expenditure (OPEX) philosophy. CRM applications such as SalesForce.com started this business model in the traditional enterprise business soſtware segment. Popular


www.scientific-computing.com/BASL2017


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