Hannover. In the age of digitalization and Industry 4.0, scientific labs are also busily gearing up for the future. Laboratory 4.0 promises robotic systems and automation, full digitalization, a flexible, modular work environment, smart materials and functional surfaces. Everything is possible, but who needs exactly what? Decisions relative to automation and robotic systems, laboratory setups and laboratory IT deserve careful consideration. LABVOLUTION, which forms part of the life sciences event BIOTECHNICA (next to be staged from 16 to 18 May 2017 in Hannover, Germany) provides the perfect opportunity to do just that. LABVOLUTION is Europe's dedicated trade show for innovative laboratory equipment and the optimization of laboratory workflows, and its "smartLAB" display is a major highlight of the event. Focusing on the intelligent laboratory of the future, smartLAB shows how next-generation laboratories will be able to think and communicate.
The growing complexity of laboratory processes, interdisciplinary collaboration and the growth of regulatory requirements are making lab scientists rethink the way they work. This applies in principle to every laboratory. But not every laboratory is the same. Here we give a brief summary of what Laboratory 4.0 could mean for three different types of laboratory: labs that carry out routine diagnostic tests, R&D labs, and production labs.
In diagnostic test laboratories, samples must be processed and analyzed speedily, accurately, with full traceability and in accordance with certified quality criteria and established standards. These are demanding requirements, which can more easily be met with the help of digitalization and automation – from the automated logging of the samples when they arrive at the lab to the final printout of test reports and certificates. Ideally, with specialized software and all the instruments and equipment linked to a data network, the entire processing sequence can be fully automated, including accounting and billing.
Functional surfaces with integrated devices such as scales, stirrers, heating and cooling plates, provide an ideal work surface. The preparation of a solution is instructed, monitored and documented via a digital protocol, and the data are then stored in the lab notebook and QM.
The biggest time factor in the laboratory is manual labor. This is also where the majority of errors occur. Robotic systems and machines are the best tools for methodical screening, and they ensure a high degree of reproducibility. But the focus on automation here should be the same as it is in industry: it is only really worthwhile for series production.
Research laboratories operate quite differently. Here the emphasis is on flexibility. Interdisciplinary working calls for top-to-bottom digitalization. Those collaborating on a project are often at different locations, but they need to exchange data on a regular basis and in a standardized way. If, for example, an experiment is conducted in another laboratory because the right equipment is available there, then the same standardized conditions must apply, and cloud storage is an essential requirement so that the results can be shared.
Modular designs allow for flexible workflows, set-ups and processes. Both the lab furnishings and the experimental set-up should lend themselves to rearranging of the workplace as required. So when a new project or step begins, the lab can then be reconfigured accordingly, and any equipment mounted on the work surfaces can either be rearranged or swapped out as necessary.
It is a well-documented fact that quality improvements and reproducibility can be achieved in R&D labs through the use of automation. Automation solutions set the bar higher, however, than strict standardization in the diagnostic test laboratory, and therefore they have to be more complex. The drawback here lies in the complicated handling, which makes access to the instruments and equipment more difficult.
The production laboratory is subject to the pressures of the free market. Efficiency, process optimization, security and flexibility are key priorities here. Process automation should be a necessary requirement, once reaction parameters have been established. Smart materials with sensors and actuators (e.g. for emergency cooling) make it possible to digitally monitor and control reaction vessels continuously, thereby ensuring improved safety where potentially dangerous processes are involved. Lab furniture with functional surfaces and integrated instruments and devices (including robotic systems) make standard procedures easier, while modular furniture can readily be reconfigured to create new process sequences. In this way, production can be constantly adapted to changing market needs.
How best to upgrade to Laboratory 4.0 at a time when money is tight is something that needs careful thought. Digitalization improves planning, control and quality assurance, and in the near future it will – of necessity – be adopted by every laboratory. The time has come for everyone to think towards acquiring a carefully planned laboratory IT system and a good data network.