Laboratory trends: a playbook for remote research collaboration

As life slowly edges towards a new normal, Lab News reached out to some of our laboratory experts to ask what they believe research teams will be excited about and how laboratory managers can access and integrate real solutions right now…

Pandemic response to COVID-19, and lessons learned to enable future pandemic preparedness, will continue to drive transformational change. It is clear there is a need for all sectors to evolve working practices to minimise the number of employees in laboratories at any one time. This might be achieved by taking all non-site-dependant work to remote status and strengthening the communication and infrastructures needed to support seamless collaboration between core laboratories and satellite offices in more remote locations. Of course, even before the current pandemic threw a motivational bomb under our basement, the need to embrace automation technologies that supported greater efficiencies, reliable processes, reproducible results, and effective use of resources to stay competitive and cost-effective was already universal. A great deal of research innovation, and on-the-market laboratory and point-of-care equipment advances already leverage the power of the algorithm to drive autonomous machine learning and decision making. Unsurprising then that, when asked for opinion around trends for laboratories, our expert authors nearly all mentioned digital transformation. They also seek practical solutions that enable digital integration to both support the wider need for remote working and continue to improve scientific and business efficiencies. The terms ‘machine learning’ and ‘artificial intelligence’ are almost ubiquitous in our collection of responses, and the breadth of application for algorithm-driven automation covers process, discovery, analysis, and even autonomous diagnosis. But, according to our experts, these future forward techniques are worth nought unless they can be made accessible and easily integrated into current infrastructures. While cutting-edge digital advances are all well and good for driving global scientific research and development, when it comes to every day working practices the simple act of providing a framework that supports and encourages the conversion of paper-based, results-gathering practices into efficient, standardised, digital data recording across teams can transform data asset management, improve results analysis and support remote collaboration for even the smallest independent laboratory. Afterall, while we may wish to drive artificial intelligence and machine learning for technological innovation, the ultimate goal of digital transformation must be to support the collective intelligence and leverage people power to solve people problems. But don't take my word for it.

The following pages are filled with some excellent thought leadership and practical advice from the real experts...

Sarah M Lawton Editor