Automation is transforming numerous industries. From factory floors to checkout lines to our own homes, more and more processes are being handled by computerized machines – and research labs are finally starting to embrace this change as well. While some industries have turned to automation just to cut labor costs, scientific research can use it to do much more than to simply please some shareholders – in the sciences, automation could actually help save lives by accelerating the pace of drug discovery and development.

As Melanie De Almeida explains in an article in, too many young scientists have been wasting time doing “repetitive pipetting tasks” rather than focusing on the science itself. In order to maximize their productivity, numerous pharma and biotech companies have started automating the liquid-handling work. University labs, too, are increasingly adopting this form of automation, especially as the technology has become more affordable. De Almeida cites the example of US-based company Opentrons, which sells a robot that performs such tasks for just $3,000.

But some labs are moving to the next level and giving the robots even greater responsibility. Case in point, the UK is launching its first automated center for the study of reactions at Imperial College London. “Laboratory robots at the £4.7 million facility will automatically set up experiments, while online analytical instruments will take samples and analyze reactions in real time,” announces Katrina Kramer of Chemistry World, noting that the facility is part of an initiative meant to make chemical synthesis faster and more reproducible. “Automating lab processes will help researchers to record in-depth data about their reactions, which then can be fed to machine learning algorithms.”

No longer is automation just about robots performing rote tasks. IoT-enabled machines provide connectivity that allow the robots to receive new information (by accessing inventories, for example) and to dispense it as well (e.g. alerting its human “co-workers” of a potential problem). Armed with skills and connectivity, lab robots are poised to take on roles that we previously thought only lab humans were capable of doing.

Discussing the future of biotechnology and automation in R&D, Claire Hill and Paul Denny-Gouldson of IDBS say the next phase of development is “a self-monitoring and regulating closed system that can make decisions on what task should be undertaken next based on the current status of an experiment.” They also remind us how important it will be for informatics solutions to keep pace so that the growing amount of data produced at each experimental stage can be turned into useful information.  

The possibilities that lab automation presents for accelerated discovery and development are thrilling. As predictive synthesis models continue to develop in accuracy and power, these predictions will be combined with automated labs like the one at Imperial College London to create a feedback loop where the predictive models learn from successful (or unsuccessful) reactions in the real world and a host of new substances are created to expand the known chemistry compound space.

These developments are all unfolding right before our eyes, and will continue to do so as AI, machine learning, robotics and other technologies continue to rapidly advance.

Elia Lima-Walton, MD

Elia Suzette Lima-Walton, MD is part of the Elsevier Content Transformation & Health Analytics team in her role as a Clinical Knowledge Representation Specialist. She applies her clinical knowledge and analytics experience to support clinical ontologies, Smart Content applications, precision medicine, clinical decision support and inference products.