Lab automation is transforming the life sciences industry in fields such as synthetic biology and genetic engineering by streamlining processes and supercharging research and development. These advances will transform the practices of medicine, manufacturing, and agriculture, among others. Achieving lab automation may seem like a utopian dream, but it’s not as far off as you think. Many labs are already taking steps toward automated processes and data analysis. Some of this automation is born of necessity. In industries where high throughput and low cost are paramount, automation is a business imperative.
The large amounts of data that such processes generate are becoming standard to life science laboratory workflows. True, end-to-end, laboratory automation has the potential to lessen the burden of handling mass quantities of data, revolutionize laboratory processes, dramatically improve throughput and improve outcomes for everyone from the shareholders to the end users and consumers. This utopian goal doesn’t have to be achieved at once; it can be reached incrementally.
Lab automation can be carried out in stages by implementing specific building blocks in phases. Some of the building blocks that could be selected include automated sample handlers, solution handlers, incubators, and microplate readers. Robots can be added to move samples from one building block to another. Of course, if the plan is to automate the complete workflow that you must plan overall implementation with the end in mind.
Some lab staff may worry about the potential of automation to replace their jobs. It’s important for everyone involved to recognize that although labor is replaceable, the capacity for scientific reasoning is not. Creative leaps and insights remain a uniquely human trait. Freeing up time that previously was devoted to repetitive tasks gives your lab staff the bandwidth for value-added activities like training, reporting, or higher level analysis. Automation also leads to increased efficiency, accuracy, and reproducibility, which benefit your lab when you need to demonstrate results.
Lab automation will involve LIMS interfacing and will have impacts on your data integrity and security as well. Therefore, automated and interconnected systems must be properly validated to ensure the accuracy of their results. In addition to the familiar IQ, OQ, and PQ testing of the usual lab informatics system validation, you may need to add design qualification (DQ) and equipment qualification (EQ) testing to your lab automation validation process. Depending on your industry, any instrument systems involved in the automation process may also need to be validated. These additional levels of testing will help you ensure the integrity of your data as it flows through your automated lab.
Lab automation- is already transforming the way research is conducted in various fields of life sciences. Successful implementations of lab automation are leading to remarkable achievements and breakthroughs. Robotic systems for pipetting or other repetitive activities don’t get tired and lose their mental focus; they can work around the clock without risk of repetitive stress injuries.
Lab automation is accelerating the drug discovery and development process, from high-throughput screening to compound management. AstraZeneca has built a prototype automated lab to synthesize small molecule compounds. In genomics and proteomics research, lab automation is having significant impacts on various avenues of research including next-generation sequencing, gene expression analysis, and protein characterization. The quality and quantity of data provided by Lab automation also increases the application of artificial intelligence capabilities to refine and streamline drug development processes.
The interest in continuous manufacturing among pharmaceutical companies is driving the expansion of in-line testing, an area ripe for automation. The U.S. Food and Drug Administration (FDA) is encouraging the use of process analytical testing, which will enable the spread of automation beyond the life science lab to the manufacturing line.
Future advancements of lab automation technology in the life sciences are promising, with exciting possibilities on the horizon. We’ve touched briefly on the potential of robotics and artificial intelligence/machine learning, which will drive innovation forward. Mixing these technologies together will increase the accuracy of predictive analytics and data-driven decision making. These improvements will continue to accentuate the importance of making the best use of your available data from the beginning of your automation journey. Increased automation has the potential to expand the application of personalized medicine and precision healthcare, making it possible to tailor treatments to individual patients based on their genetics.
Embracing true lab automation will bring your lab efficiency gains and, perhaps, research breakthroughs that would not have been possible with your existing workflows and processes. Increasing numbers of organizations are looking to automation as the way of the future, not only within the lab but also across the organization. Don’t be left behind; prepare your organization for true lab automation by making smart business decisions now.
What lab automation moves are you considering? Let us know in the comments.