The Lab of the Future will be powered by two kinds of technologies: new innovations that are only in their infancy today, and adaptations of more conventional techniques given a digital upgrade to make them fit for interconnected, data-led workflows.
In this immersive article, we’ll take a tour through the Lab of the Future, reviewing the technologies and trends that will power the next generation of research.
The data advances we currently see in the modern-day lab would not have been possible without the implementation of laboratory information management systems (LIMS), which act as a central hub to track sample and data management. In the Lab of the Future, LIMS will further expand their capabilities, moving to cloud-first software that scales to the requirements of individual labs. Voice activation systems will make recording and managing lab data easier for users and the Internet of Things will make LIMS able to manage the minutiae of the lab environment, ensuring optimal performance.
The Lab of the Future will produce and require greater volumes of outputted data, held to a higher standard. The ability to track your samples’ origin and passage through the lab will be essential. Using smart consumables, such as vials with barcoded details and built-in compliance, will ensure that automated systems elsewhere in the lab have the raw materials required to function accurately and efficiently. The information in these smart consumables can be interfaced and stored on lab informatics systems.
Researchers in the Lab of the Future will work alongside automated systems to achieve higher throughput and more accurate results. Currently, a third of a technician’s time can be occupied by manual tasks, like pipetting. Automated systems, some of which can process up to 2000 samples an hour, will be the workhorses of the Lab of the Future, freeing up researchers to focus on more important tasks. Automation will be dynamic, with some labs opting for wholly automated workflows, and others targeting individual processes and hardware within the lab that bottlenecks existing protocols.
The Lab of the Future will produce and require greater volumes of outputted data, held to a higher standard. The ability to track your samples’ origin and passage through the lab will be essential. Using smart consumables, such as vials with barcoded details and built-in compliance, will ensure that automated systems elsewhere in the lab have the raw materials required to function accurately and efficiently. The information in these smart consumables can be interfaced and stored on lab informatics systems.
Researchers in the Lab of the Future will work alongside automated systems to achieve higher throughput and more accurate results. Currently, a third of a technician’s time can be occupied by manual tasks, like pipetting. Automated systems, some of which can process up to 2000 samples an hour, will be the workhorses of the Lab of the Future, freeing up researchers to focus on more important tasks. Automation will be dynamic, with some labs opting for wholly automated workflows, and others targeting individual processes and hardware within the lab that bottlenecks existing protocols.
Hardware and instrumentation in the Lab of the Future will not just be used to generate data about samples but will output data on their own performance too. Remote monitoring of lab equipment will help lab managers keep track of any hardware that is overused or underutilized, allowing senior staff to direct users to available instruments and reduce bottlenecks for heavily used equipment. Smart instruments will build in predictive maintenance, which will stop an unexpected malfunction putting a lab out of action for long repair waits.
Robots have an essential role to play in these automated systems, moving and processing samples according to predetermined programs. Modern lab robots have full six-axis motion, with built-in servo technology for smooth movement. Using paired software, the robots can be trained for new protocols easily. Their high reliability and repeatability make compliance with data integrity regulations, like 21 CFR Part 211, simpler than when using manual protocols. Prototype mobile robots and the emergence of soft robots promises to make the Lab of the Future’s robotics more dynamic than currently available technology, opening up further lab protocols to automation.
Robots have an essential role to play in these automated systems, moving and processing samples according to predetermined programs. Modern lab robots have full six-axis motion, with built-in servo technology for smooth movement. Using paired software, the robots can be trained for new protocols easily. Their high reliability and repeatability make compliance with data integrity regulations, like 21 CFR Part 211, simpler than when using manual protocols. Prototype mobile robots and the emergence of soft robots promises to make the Lab of the Future’s robotics more dynamic than currently available technology, opening up further lab protocols to automation.
Electronic laboratory notebooks (ELNs) have faced challenges in their adoption, but the direction of travel is clear – they will come to replace paper-based data recording systems in the Lab of the Future. Cutting out paper waste helps towards sustainable lab practices and is also essential for meeting data integrity and compliance targets. Audit trail-enabled, role-defined ELNs help lab managers keep track of what data has been generated and by whom. As regulators like the US Food and Drug Administration put a greater emphasis on the importance of digital data, regulated labs will come to see ELNs as the only option for laboratory compliance.
Automation, smart instruments and informatics systems are helpful on their own. But, without the Internet of Things (IoT), future labs risk becoming islands of automation, with different systems all generating useful data, but in isolated siloes. The IoT allows smart instruments, LIMS and ELNs to share their data. By using AI- and ML-based refinement, lab analytics can be personalized to each individual lab, identifying bottlenecks and sources of error before they begin to impact on lab processes.
Automation, smart instruments and informatics systems are helpful on their own. But, without the Internet of Things (IoT), future labs risk becoming islands of automation, with different systems all generating useful data, but in isolated siloes. The IoT allows smart instruments, LIMS and ELNs to share their data. By using AI- and ML-based refinement, lab analytics can be personalized to each individual lab, identifying bottlenecks and sources of error before they begin to impact on lab processes.
The vast amount of data produced by Lab of the Future technologies is meaningless unless it can be effectively analyzed and stored. Cloud computing looks to be the answer to this big data burden. Currently available cloud solutions are fully scalable, meaning smaller labs don’t have to pay over the odds for more limited functionality, while larger labs can fully take advantage of remote silos and servers. Cloud computing means that labs have access to analytical power far beyond what they would be able to acquire in hardware. The remaining question of security and data integrity has become the focus of cloud providers’ offerings.
The Lab of the Future might not exist yet, but the tour we’ve taken through the technologies and adaptations of the next generation of lab has hopefully given you an idea of the advances that will shape it. Interconnectivity and data-first approaches will power the lab’s advances and it is only by combining these technologies that research can fully reach its future potential.
The Lab of the Future might not exist yet, but the tour we’ve taken through the technologies and adaptations of the next generation of lab has hopefully given you an idea of the advances that will shape it. Interconnectivity and data-first approaches will power the lab’s advances and it is only by combining these technologies that research can fully reach its future potential.
With recent technological advances in automation, Internet of Things (IoT), informatics and data analytics, laboratories have seen huge developments in processes and instruments, yet the fundamental goals of the laboratory remain the same; generating results that are accurate, fast, cost-effective, regulatory compliant and reproducible.
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