Labs go auto

Pandemics, pressure, and people shortages are driving automation in scientific and biomedical laboratories.

The Covid-19 crisis has taxed biomedical laboratories to their utmost, under the urgent imperatives of rapid diagnostic testing and drug discovery. On top of workflow pressures, facilities had to cope with the added stresses of workplace distancing and staff sickness. For many, the pandemic has highlighted a need to automate many standard laboratory procedures sooner rather than later.

Automated technology has become increasingly important in the conduct of many types of standard lab-based work. Collaborative robots – cobots – can now be configured to perform routine tests such as batch sample screening and even chemical experimentation. As well as helping to reduce chances of human error caused by heavy workloads, automation also releases researchers from repetitive tasks, enabling them to make best use of available human expertise.

On-demand cloud-based ‘virtual’ lab platforms from providers such as Strateos and Emerald Cloud Lab are another form of laboratory automation. These enable scientists to work remotely, using a range of IT-driven automated robotic installations in specially designed facilities to conduct their work. These facilities are fitted out with shared automated infrastructure: conveyor systems, robotics, machine vision, and control software working in concert to perform tasks that had formerly been done by humans.

Most standard clinical laboratory applications, like drug discovery, clinical diagnostics, and genomics and proteomics solutions, can be automated. Scientists ship samples to a facility and design their experiments using an integrated application that encodes tests in software designed to enable remote operation and reproducibility. Procedural wet-sample steps like sample storing, sorting, de-capping, recapping, retrieval, accessioning and centrifugation can be assigned to robotic apparatus under controls remotely managed by scientists.

For conventional laboratories, cobots deliver performance gains because they can be set up and running – as static or mobile units – without the need to reconfigure existing laboratory layouts that humans are already used to. Different sized mobile robots are designed to move around lab workspaces and manipulate test apparatus, usually via articulated arms that offer various degrees of dexterity and interactivity.

Mobile cobots usually function attached to a base unit that transports them around the lab and contains batteries that power both the cobot’s actions and the motors that move it from one place to the next. This means that, dependent on the demands of the task they are engaged on during any one ‘shift’, they have to park in a charging station every three-and-a-half to four hours.

The market for cobots is set to grow steadily over the next five years, according to forecaster MarketsandMarkets: the analyst expects the global cobot market to go from $981m (£708m) in 2020 to $7,972m (£5,757m) by the end of 2026; that’s a CAGR of 41.8 per cent over the forecast period. This growth will bring down cobot prices and thereby drive adoption, MarketsandMarkets says, so that workspaces may have teams of cobots working concurrently. It will also make them affordable to small and mid-sized businesses.

Collaborative robots are already operational in academic research. In the UK, at the University of Liverpool, scientists have even credited the cobot there with new chemical discoveries.

The university’s Department of Chemistry developed and deployed an autonomous mobile cobot to assist in materials research programmes. Based on core technology from automation specialist KUKA, it communicates wirelessly with a software control system and can be calibrated to interact with most standard laboratory equipment and machinery.

The 400kg, 1.75m-high cobot moves around its physical environment – and its human co-workers – by using lidar laser scanning coupled with touch feedback to map its place in its immediate environment. In a prototyping exercise, University of Liverpool’s cobot conducted 688 experiments over eight days, in operation for 172 out of 192 hours. To do this, it made 319 moves, completed 6,500 manipulations and travelled a distance of 2.17km.

To date, it’s been engaged on research into developing photocatalysts – materials that help produce hydrogen from water by use of light. Like a human chemist, the cobot has to be able to adapt its workflow based on the outcome of its experiments.

“This requires a computational solution,” explained Professor Andrew Cooper, director of the Materials Innovation Factory at University of Liverpool. “If you work out the number of possible combinations of the components in the experiment, it’s something like 98 million.”

Because of this the cobot uses an optimisation algorithm – a type of AI that uses a design strategy Bayesian optimisation – to ‘navigate’ that chemical space and give it decision-making capabilities.

“The robot weighs out the solid catalysts, it dispenses the liquids, it shines light onto the samples, it removes air from vessels and then it measures the outputs [i.e. the hydrogen],” Cooper says. “Then, based on the output from the experiment – the hydrogen emission – it makes a decision about what to do next.”

He added: “The cobot’s ‘brain’ uses a search algorithm to navigate a 10-dimensional space of the 98 million candidate experiments, and decides the best chemistry experiment to do next, based on the outcomes of the previous ones. By doing this, it autonomously discovered a catalyst that is six times more active, with no additional guidance from the research team.”

Test and analysis

Cobots keep hospital’s sample analysis rates on target

Faced with a 20 per cent increase in the amount of blood samples arriving at its test laboratory, Copenhagen University Hospital in Denmark sought to uphold its target of having 90 per cent of samples analysed within an hour. The hospital deployed two cobots from Universal Robots to sort blood samples into four different pathways for further analysis.

The cobots operated in a space-constrained area where larger, automated bulk loaders were not an option. “The blood samples arrive on a conveyor in a corner of the lab with no room to erect safety fencing,” explains Steen Stender, chief physician at the hospital. “Laboratory technicians are able to interact with the cobots and easily intervene if necessary.”

He adds: “We needed a solution that would respond to vision-guided programming, pick up, sort, and load the samples into the entry module for analysis. The first cobot picks up a sample and places it in a barcode scanner. A camera photographs the colour of the screw cap, and the cobot is guided to place the sample in one of four racks according to colour. The second robot picks up the rack samples and places them in the machine feeder for centrifugation and analysis.” The cobots handle seven to eight tubes per minute.

Covid testing

Robot swab tester gets right up your nose

The risks of close contact between medical staff and patients has proved an inhibitory factor in regulating the pace of Covid-19 testing. Taiwanese biotechnology start-up Brain Navi has developed a collaborative robot to perform nasal swab tests autonomously with the aim of zeroing the chances of cross-infections between patients and healthcare staff.

The procedure begins when the patient attaches a nasal clip that’s used by the cobot to orientate itself. The patient then places their head in a fixed chin holder.

A depth-sensing camera scans the patient’s face and measures the distance from nostril to ear canal as a proxy for the depth of the nasal cavity. This enables the device to probe safely within the nasal cavity.

The robot then determines the patient’s facial structure and their nostril’s location, and proceeds to gently take a sample by twisting and swaying a nasopharyngeal swab within the designated nostril – which it does for exactly 10 seconds, so each test is precisely timed (and recorded). It then deposits the swab in a sterile container that can be borne away by secondary cobots for rapid analysis.

As demonstrated, the Nasal Swab Robot is not currently a fast worker, and takes about 90 seconds to take the sample and deposit the swab before the next patient can be tested.

However, following clinical trials, Brain Navi is now launching ‘zero-contact’ medical stations in hospitals across Taiwan to provide robotic nasal swabbing while protecting patients and staff from cross-infection.


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