To keep up with today's rapid pace of innovation and research, lab leaders need to ensure their systems and processes are as efficient as possible. Many manual processes can now be replaced with automation or digital tools. But to reach a modern, connected lab requires a holistic approach to build a digital ecosystem where systems can be monitored and data can be shared. Below, Brian Stan, director of connected solutions at Thermo Fisher Scientific, discusses the concept of a connected lab and how to achieve it.
Q: What does the concept of a truly "connected" lab mean to you?
A: The concept of a truly connected lab refers to one that has undergone a digital transformation to provide visibility across the entire lab and connect end-to-end processes and all aspects of the laboratory (e.g., people, consumables/reagents, software, and instruments). While many individual pieces of equipment have connected features, a truly “connected lab” goes beyond the lab equipment itself. Creating a connected lab takes a more holistic approach including a digital ecosystem that extends across labs and institutions. Through this cloud-based network, systems, samples, and processes can be monitored, data can be shared, and insights from analytics can help lab personnel make informed decisions and improve productivity to help accelerate science. Furthermore, a connected lab can utilize predictive analytics to decrease costs by maximizing equipment longevity and reduce wasted energy by supporting sustainability programs and goals.
Q: Can you explain the difference(s) between digitization and digitalization and why this distinction is important for lab managers to understand?
A: Digitization refers to the process of converting analog managed data and processes, such as paper records or locally maintained information stores, and making that information available in a digital format, like electronic tracking systems such as electronic laboratory notebooks (ELNs) and setting up an electronic database of standard operating procedures.
Digitalization is the next step—it takes all that easily accessible digital information and makes it actionable, such as running analytics and using the flexibility of the new digital format to harmonize processes and workflows. Digitalization also integrates other lab components to help labs achieve full digital transformation. An example of digitization might be creating an electronic inventory record. Digitalization would then take this record and develop a digital inventory tracking system that is connected to supply chain management tools, enabling scientists to easily reorder supplies as they run low. In this case, the digitalization of the process is what enables the lab team to act on the information and make the process more efficient.
Lab managers must understand the difference between digitization and digitalization so they can be strategic when converting their lab from a manual analog process-driven approach to a digital approach. It is important to understand that digitization itself does not solve the problem a lab may be facing. Digitization without digitalization may cause more complexity and confusion. Although digitization provides visibility across the lab, this information needs to be discerned, and lab managers need to ask how the data will add value to the work being conducted and how it could help provide new insight in a connected network.
Q: What initial steps do lab managers need to take to create a connected lab?
A: Creating a connected lab requires the transformation of lab operations across the entire business; the complete end-to-end process must be transformed to maximize the benefits.
To do this cost-effectively and efficiently, lab managers need to analyze the biggest challenges, unmet needs, inefficiencies, and pain points of their current approach. Once they have identified their pain points, they can then start thinking about what digital solutions are available and what vendor to partner with to help address their laboratory needs and align their objectives with business goals. Labs can then create a clear roadmap for digital transformation and take the three following steps to create a connected lab:
- Connect everything to make data available and visible: before taking action through a connected lab, there needs to be high-quality data that can be trusted and reused, including experimental and operational (instrument) data.
- Make use of data and advanced analytics tools to make informed decisions: this includes the use of tools like machine learning or artificial intelligence, as well as immersive technology like virtual reality systems to continually improve processes and accelerate experiment results.
- Automate end-to-end workflows: when data has been digitized, automating workflows allows labs to maximize their throughput, enhance reproducibility of processes, and more readily adapt to changing workflows.
Q: What types of tools and technologies will be most helpful for labs to implement to help them move away from manual processes?
A: The most helpful tools and technologies that labs can implement to move away from manual processes should start with digital solutions that will have an impact across a lab’s ecosystem to support the entire lifecycle of highly regulated processes.
The tools that will make the biggest impact will be different across research labs and biopharma production labs based on the level of regulatory oversight but should offer flexibility to adapt to varying workflow and data management needs.
For research labs, lab managers should focus on the process and what the equipment and people are doing at each step in the workflow. Monitoring systems to automate this tracking can make an immediate impact and are typically the first step in the digital evolution. There are a number of monitoring systems available on the market, and the lab should consider their regulatory requirements when selecting technology.
ELNs are also a very common first step in creating a connected lab. While a person is going through to assess what is happening at each step, the ELN immediately translates this information into a digital format that can be transferred to and stored on a central server on the labs network for future review or imported into a lab information management system.
On the other hand, biopharma production labs or large-scale production environments might find the most benefit from tools or technologies that create a repetitive, reproducible, highly efficient process. This is often where more sophisticated automation can play a role as a more mature evolution in leveraging the Internet of Things platform in a lab. Automation delivers consistency, cost efficiency, clear documentation in case of an audit, and facilitates reporting.
Q: How can lab leaders stay up to date on the latest digital tools and technologies that can benefit their operations?
A: Today, there are several resources available for lab leaders to share information with their peers, from online publications to regular webinars that connect lab technicians with peers in the industry who share insight on how they are addressing certain issues or connecting them with solution providers to educate on tools available to face laboratory challenges. Another way lab leaders can stay up to date on the latest digital tools and technologies is by attending in-person industry and cross-industry events that are lab-forward and IoT based.
Q: How do you envision the modern lab environment will continue to evolve?
A: Currently, there are two phases to this modern lab evolution. The first is the interim experience we’re in today, where digital tools are starting to be embraced but many labs are in the process of moving toward the next step to convert data to insights or to automate or take action on these insights. In the next five years, most labs will have the ability for lab managers to access lab data through their mobile devices. They will have access and insights into the activities and research taking place in the lab at any given time from any given location, like their home or other remote location. That level of access and insight, coupled with process efficiencies from technologies like automation, are brought to their business operations by having a connected platform in their lab and driving a Lab 4.0 workflow approach.
However, beyond Lab 4.0, future labs will benefit from the emergence of innovative technologies. For example, in addition to automation, integrating voice recognition, augmented reality, and biometric authentication into experimental workflows will increase the consistency of processes and enhance data quality and security by reducing human interaction and automating data capture. We are increasingly likely to see fully cloud-based labs, where researchers can access facilities anywhere in the world and manage a physical lab entirely online.
As connected solutions continue to be embraced in the laboratory, personnel managing the lab will be able to enhance sustainability by making data-based decisions for their business operations. Predictive technology that facilitates this is already available today. For instance, an operations manager overseeing a fleet can analyze energy consumption. Data like this can help guide decisions on equipment one may want to replace with something more efficient, or it can even indicate a malfunctioning or failing unit. Modern lab implementation can also include sample tracking. Implementing a sample tracking solution can potentially free up shelf space because it allows lab personnel to see where there is space available or if there are samples that are no longer needed that are still being stored. Improved organization goes a long way when you start thinking of how to operate more sustainably.
Industry surveys show that researchers have high expectations of the labs they contract, with not only expectations for research evolution but also technology evolution. If labs want to remain competitive, connectivity is a huge step in the right direction.
Brian Stan is director of the Connected Solutions group for Thermo Fisher Scientific’s Laboratory Products Division. Brian has spent much of his career working on connected solutions for the healthcare and life sciences industries. When not thinking about how to improve lives via connectivity, Brian enjoys mountain biking, cycling, and occasionally noodling around on the guitar.