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There were many reasons for this approach:.

The group agreed that opportunities to magnify the value output of laboratories lie within the broad spectrum of data, automation/growth in data processing, and smart technology and systems.Artificial Intelligence and Machine Learning offer transformational change in value creation.

Although there are some individual examples of its real-life deployment, we are at the start of an exponential curve.. A thread of discussion around the idea that systems could be self-validating created significant energy in the room, as well as friction between those who understood how transformational such a realised idea could be with those who saw the potential disaster.Regulators are clearly going to be either a key partner/enabler or barrier to smart developments.Or both.. What appears to be clear already is that the impacts of the growth of these technologies will be felt in all parts of laboratory operations: people, skills required, job satisfaction, locations, collaborations, buildings.

This is certainly not a time to be wedded to the bench..Intimately linked, still early in its industrialisation but a few stages ahead of smart-technology, is automation and digitisation.

Certainly, for automation, there is more confidence and immediate view about the tangible benefits that it could bring.. ‘Automating out’ routine work can have a significant impact on cost where there is the scale to support the investment.

Routine laboratory work takes scientists away from research thinking and potentially is a turn-off to those considering a career in laboratories.There are no dead ends, so you don’t have to go back on yourself.

You just keep going all the way round.’.Maswiken also remarks on this ease of movement within the hospital.

He enjoys the freedom of not having to ‘push things aside’ to walk between areas.The hallways are very spacious, particularly when compared to the ‘narrow corridors’ of other hospitals in which he has worked.