Automation Research Solutions

The Lab of the Future: Artificial Intelligence, Machine Learning, and Microfluidics

Today’s laboratories look very different to ten years ago, but what about ten years from now?

The way in which scientist’s approach research has been drastically influenced by the advancement of technologies. The integration of and automation has revolutionized procedures, transforming tedious manual processes to automated liquid-handling systems.
The introduction of microfluidics and lab-on-a-chip technologies, adoption of paperless workflows, and the ever-increasing interest in , machine , and artificial intelligenceArtificial Intelligence knows many different definitions, but in general it can be defined as a machine completing complex tasks intelligently, meaning that it mirrors human intelligence and evolves with time. () are just a few factors instrumental in the transformation of the laboratory. More specifically, influencing procedure efficiency, reproducibility, data collection, analysis and sharing, and much more.

Microfluidics and lab-on-a-chip technologies

Microfluidics enables the manipulation and analysis of extremely small fluid volumes within a multichannel system (10 –9 to 10 –18 litre). The capacity to downsize large-scale biology coupled with the capability of housing multiple experiments on a single chip, which is small enough to fit in the palm of your hand, is an attractive concept.

The ability of microfluidics to miniaturize multiple laboratory operations, is reflected in its use across a multitude of scientific fields, including the areas of genomics, materials science, molecular biology, and organic chemistry. There are several advantages to microfluidic technologies. Firstly, very little sample is required, meaning precious or scarce samples can be conserved. The volume of reagents is also significantly reduced compared to traditional large-scale analyses, translating to an overall cost saving. Another benefit is that the miniaturized system can still achieve high-resolution analysis, whilst maintaining sensitivity. The nature of the channels (high surface-to-volume ratio) means that reagents rapidly diffuse into the reaction chamber, reducing the time it takes to complete a reaction, generating results faster. Finally, lab-on-chip systems can be automated and standardized meaning there is little need for human intervention, eliminating the risk of ‘human error’.1,2 This is particularly beneficial considering the continued evolution of and automation within laboratories.

Automation and

To merely say ‘technology has changed the way we conduct research’ is an understatement— it has truly transformed it.

has enabled significant restructuring of the workplace. Many areas traditionally reserved for ‘wet lab’ benchwork have been reallocated to liquid handling robots that are capable of processing hundreds, if not thousands, of samples, through the use of pre-programmed and customizable procedures, requiring limited supervision. Such automation allows researchers to invest more time on data analysisData analysis is simply put the study of data in order to take better informed decisions. All business decisions should be made with the best information available, data analysis tries to provide this information through different algorithms and statistical techniques.. An important point to note is that the implementation of robotic instruments does require ‘fit for purpose’ workflows and data storage solutions to ensure one’s ability to sort, organize and access the data. This challenge has been a major focus for cloud-based data storage, and machine developers over that last few years. […]

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