Lab operation is complex, which means that any analytical lab deals with a variety of instruments. When there are a huge number of instruments, variety of data systems and compliance is important and people procedure and methods is something that comes into picture. This is where lab efficiency triangle comes which means that every business needs speedy opportunity with quality results as well as lower costs. This is something which every lab manager needs to look into. As the lab environment is complex, with this complexity, there come lot of data systems like LIMS, CDS and other multiple instruments that come into picture and there is always a challenge of integrating those systems. They do not talk to each other and this is where the insufficient communication comes into picture, which is one of the major pain points. Further, since these systems work in silos, there is always an incomplete knowledge for whether it is a lab person who is performing the day-to-day task as well as for the lab manager who is responsible for the overall productivity of the lab. With this incomplete knowledge, you have an uneven workload; and, many times, with the traditional systems, there is a lack of visualisation tools, which again contributes to loss in productivity.
The solution for all the challenges is the digital labs and when we talk about the complex environment, there is no turnkey solution, you have to come up with a solution that helps you to improve your productivity and efficiency. How about a system which allows you to reduce all paperwork to all automated calculations? How about connected labs? I have all my data and all the insights of my lab are available at the click of a button. This is something that a digital lab talks about.
Talking about the guiding principles for a digital lab, it should have an integrated solution which should be sample and workflow-centric as we all work in a multi-technique and multi-vendor environment. Interfaces should be able to enable people and workflows. These should be easy to deploy, validate and maintain, and secure enough to ensure that the data remains secure and integrated, and compliance is the major aspect, and I should be able to use and reuse the data. I should be able to get the context and analytics from my data.
When we talk about analysing the data, we also need to understand that whether we have analysed it right or not. With the robust and explorer tools that we have in open lab CDS system, you can see a complete helicopter view or bird’s eye view of your sequence so that you can find out any anomaly in your system and can take the right decision.
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