SmartLab: all-in-one automation, digitalization, and miniaturization

Laboratories have to analyze and interpret an ever-increasing number of samples for research and diagnostic services, generating lots of data in the process. At the same time, labs are required to produce quality results and operate with speed. Processes that could once be managed using laboratory notebooks and isolated systems must become smart in the future to improve lab efficiency.

In this MEDICA-tradefair.com interview, Dr. Felix Lenk talks about laboratory automation, outlines the road to a digital laboratory and reveals the hurdles we still must overcome.

Dr. Lenk, what is the objective of the SmartLab Systems research group?

Dr. Felix Lenk: We explore three key research areas: first, the automated handling of chemicals, consumables and lab automation in general, second, the automated 2D and 3D image analysis of biological samples, and third, miniaturized measurement technology.

For us, the SmartLab, also called the laboratory of the future, is a term that sums up these technologies - automation, digitalization, and miniaturization.

What projects are you working on as it relates to applications in biomedicine and biotechnology?

Lenk: We use the PetriJet platform to screen for new antibiotic agents. Researchers use a zone of inhibition test for identification: When a microorganism produces an antibiotic substance, it is combined in a co-culture with another organism that triggers the production. This might be yeast cells or bacteria. A circular area forms around the organism where the substance is effective. The size of the zone of inhibition relates to the level of antimicrobial activity present in the sample.

The optical PetriJet allows high-throughput screening because we have to combine different types of organisms, always in multiple cultures. The platform can process culture dishes individually, open them, pour and cultivate the contents in a new culture dish. It also takes images of the process flow under different light exposure and from different perspectives and measures the zone of inhibition. This enables us to non-invasively screen a wide range of microorganisms and select new antibiotic candidates.

What prompted these ideas?

Lenk: We are an interdisciplinary research group that includes molecular biotechnologists, regenerative medicine doctors, chemists, mathematicians, automation and controls engineers, and several bioprocess engineers. Our goal is to bridge the gap between biology and technology. This is the interface that gives rise to new ideas because everyone looks at problems from a different perspective.

What is the current state of digitalization in the laboratory? What role do networking, the Internet of Things and big data play in this setting?

Lenk: This is best described by our "five-tiered approach to digital transformation". Tier One refers to sensors that record short-latency and high-frequency laboratory processes. Tier Two is a sensor network. This means that the sensors must be able to deliver data via wireless or wired connection. Tier Three pertains to how this data is stored in a database structure even for long periods of time and is called the "data lake".

Tier Four refers to the "structured data lake". This turns the database structure into a kind of network. Terms and measurement data are thus put into correlation. This gives data context. And finally, Tier Five means making the data human-interpretable. Researchers seek answers to questions such as "Is this a great antibiotic candidate?" or "How do I change culture media for optimized growth?" If you capture data with three dimensions, it often makes it difficult for humans to understand because you can no longer display it in a diagram. Neural networks can process this data. It can be visualized with tools such as mixed reality headsets, voice output, or assistive technologies.

I would say that laboratory digitalization presently ranges somewhere between Tier One and Tier Four, with some applications reaching Tier Five.

What’s next for this area?

Lenk: So far, point solutions have worked well to improve processes and data management, though interfaces are slightly more problematic. For example, when a pharmaceutical company moves a project from development to production, the process often has to be revamped at the pilot or production scale.

While you have the specific formula composition, there is no information about the form factor of the lab reactor, the power input, or the stirring speed. The biggest challenge is to create interfaces to allow all data transfer. To ensure connectivity and a network approach, standards are being created including the OPC-UA initiative by SPECTARIS e.V., or the SiLA Consortium (Standardization in Lab Automation) in Switzerland.

Connectivity also entails difficult adjustments. It is comparatively easy to map the actual workflow analysis and create requirement specifications for the target status. Many believe adjustments can be easily made during ongoing lab operations, clearly underestimating the difficulty of the implementation process. Yet many devices are incompatible because of the lack of standards. Each application requires individual driver programming. Joint standards and interfaces would make transition phases more effective, easier, and faster. Laboratory employees not only have to focus on their manual work tasks, but they must also determine whether the devices are performing the required tasks and produce quality test results. This requires a shift in mindset, and we are still in the beginning stages of our journey.