The topic of optimizing laboratory efficiencies is at the forefront of discussions for many lab managers. With the support of new and improved smarter technologies, previous efficiency- and productivity-related challenges are beginning to dissipate as manual processes are starting to be replaced with automated and integrated applications, helping to pave the way towards a fully digitalized lab as part of the internet of things (IoT) movement.
According to the global advisory firm Gartner, a digitalized lab is one that is using digital technologies to change the way they operate their lab, optimize their business model, and ultimately provide new revenue and value-producing opportunities. In a nutshell, it is the process of moving to a digital business.
The results from an Agilent survey of pharma lab leaders support this observation. Responses highlighted the urgency to improve and update laboratory processes. Survey takers said that they:
- Wanted to achieve quicker results (55%)
- Saw a demand for superior quality (44%)
- Wanted to improve data integrity (43%)
- Found that their current workflow requires optimization (83%)
Additional survey results showed that only 4% of lab managers are using utilization data (a tool to understand how all instrumentation in labs is performing) for decision making.1 More astonishingly, on average, some lab instruments were only being used 35% of the time. 2
Goodbye laborious systems, hello smart technology
To combat some of the key challenges often faced with existing lab workflows, smart technology is increasingly at the core of change. By helping transform ordinary labs into smart technological labs, analytical companies such as Agilent can provide better instrumentation and services to their customers without compromising the quality of results, cost effectiveness, or laboratory space.
The lab of the future is a concept built on the foundation of digitalized labs. It encompasses smart technological workflow systems that are connected and capable of collecting vast amounts of data via integrated automation. At the Lab of the Future 2020 congress in Cambridge, UK, a keynote speaker at the event was quoted as saying “The lab of the future won’t be bound by walls,” 3 suggesting that the digitalization of labs will enable more fluidity and interconnectivity between assays and other procedures.
Transforming science with digitally connected labs
A digitalized lab should be considered a more advanced lab as it has more access to data. With data being key to transforming science, increasing amounts of data generated in any lab, let alone a digitally connected lab, could be a game-changer – but only if it’s collected and synthesized into information and knowledge that is useful.
The digital environment (i.e., paperless work in an electronic format) capitalizes on digitalization. It incorporates all of the necessary instrumentation for complete data analysis, and enables the full value of the data for decision making.
Artificial intelligence (AI) is often defined as the ability of a machine to learn how to solve cognitive challenges. However, in the context of scientific methodology and laboratory interconnectivity, AI is starting to be used for capturing data to model human observation and decision-making processes. Taken forward, connecting all instruments in a lab via AI enables the opportunity for an even more astute understanding of the interactions between technology and also users, potentially providing an all-inclusive view of all laboratory operations.
By monitoring and identifying inefficiencies and making recommendations, AI goes beyond data interpretation to the level of suggestive intelligence, which could be used to more effectively manage lab operations, and ultimately accelerate research and discovery.
AI technology will augment digitalization of the lab
The ability to monitor operations and provide more sophisticated insights is a core reasoning for introducing AI into the operational lab environment. Accessing this powerful source of information will become a necessary component of scientific productivity. This is an inevitable next step in creating lab management systems that are so efficient and provide knowledge that is so valuable that only AI will be able to produce them.
AI, coupled with universal sensing capabilities to detect and monitor a range of variables, e.g., an instrument’s power draw, enables companies to realize certain operational and financial benefits to their business and plan for the future. Through high-quality and readily available insights, AI enables the simultaneous monitoring of all equipment usage in the lab and holistic capacity tracking.
A schematic diagram to represent elements of a digital lab in practice.
Providing digitalized innovations to address customers’ key challenges
Agilent has developed an array of technologies and platforms that have pushed the boundaries in providing solutions that support the needs of its customers by enhancing the interconnectivity of its instrument products, services, and consumables through:
- Integrated products and services that advance the digital lab
- Faster, customer-preferred online interactions that improve the ease of doing business
- Solutions that increase operational efficiencies
As an example, part of the Agilent CrossLab Group, the Digital Lab Program, is an ecosystem of products designed to complement one another by delivering enhanced digital capabilities to customer end-users, improving their laboratory experience. This initiative has brought certain technologies to life with industry-leading tools in data intelligence to enhance the scientific and economic outcomes of labs worldwide, such as:
- Asset Monitoring – Agilent CrossLab Asset Monitoring combines advanced IoT sensor technology and data analytics to enable lab-wide visibility. It integrates sensor-based utilization monitoring with business analytics, allowing you to capture lab-wide instrument utilization data across all of your workflows, view analytics compiled in dashboards to drive insights for improvements, and justify CapEx, OpEx, and productivity decisions using fact-based data.
- Smart Alerts – Monitoring instrument health and providing email-based alerts, notifying lab operators when to consider replacing key consumables, when to perform preventive maintenance, and when an Agilent instrument stops running anywhere in the lab. Digital lab-wide connectivity lets users remotely monitor all of their Agilent instruments.
- SLIMS – End-users can effectively track samples as they progress through the laboratory from sample receipt to automated result reporting. SLIMS combines the best of a laboratory information management system (LIMS) with an electronic laboratory notebook (ELN) to enable end-to-end solutions and manage the full content and context of your laboratory.
- OpenLab Software/Cloud Storage – Has become a viable option for virtually every computing workload in the laboratory, from sample management to complex analytics to secure data storage.
Staying competitive in a competitive world
Globally, scientific innovation is accelerating, so labs need to consider the technology investments required to become digitally enabled in order to keep up and stay competitive. We live in a data-driven world, so scientific laboratories must fundamentally transform how they create, manage, and effectively use all the data that is generated in their lab ecosystem. Achieving and sustaining a competitive edge in a world of constant change will require the continual transformation of lab operations and scientific data management. This will be the first and most important step toward becoming a truly digitalized lab.
1 Agilent asset management survey of lab and operations managers
2 Utilization data from Agilent Asset Monitoring; blend across high-value Cat 1, 2, 3 assets in R&D and QC