by Brian Stan, Director of Connected Solutions at Thermo Fisher Scientific
While the idea of a “connected” or remotely monitored lab may sound like something from the future, virtual globalization and the exponential growth of data, processes, and technologies has made it unsustainable for labs to operate with entirely manual processes. According to the International Data Corporation (IDC), 85% of enterprise decision-makers believe that they must make significant inroads into digital transformation within two years to avoid falling behind their competitors and suffering financially.
With the advent of new technologies, challenges spurred by a global pandemic have forced the scientific community to increase the pace of new research and innovation. As a result, laboratory processes that were traditionally entirely manual are being optimized through the use of automation and data connectivity to increase efficiency in the lab. By creating a connected laboratory, facilities can improve productivity and transparency, increase staff satisfaction, reduce errors, and ultimately accelerate science.
The Foundation for Connectivity
Lab managers must analyze their biggest challenges, unmet needs, inefficiencies and pain points of their current approach to identify where their digital transformation journey should begin. Once they have identified their pain points, they then can start thinking about what digital solutions are available and what vendor to partner with to help address their laboratory needs and meet business goals.
Across healthcare, the life sciences, and research communities, paper-based record-keeping and workflows are transitioning to digital mediums that enable scientists or clinicians to store their records in a secure and future-proof format. Digitizing these files is the first step in integrating digital technology to optimize business processes and improve user experience. But digital transformation involves much more than simply taking paper-based recording and putting them online. Instead, it involves a deep change in the management of technology, data, and associated processes that ultimately creates new opportunities for the lab. These opportunities are enabled through true connectivity – visibility across an entire lab that connects end-to-end processes with all aspects of the laboratory.
To capitalize on this visibility of a connected lab ecosystem, companies must transform the way they create, organize, and store data to support a transparent flow of information. Through this change, laboratories face their own unique challenges as they develop strategies that must comply with regulatory guidelines to enforce and maintain data security.
Many new technologies or pieces of lab equipment have connected features that allow for remote monitoring, mobile control, or data insights. However, true connectivity goes beyond any one piece of equipment. Therefore, creating a connected lab takes a more holistic approach – it takes a digital ecosystem that extends across labs and institutions to build a cloud-based network through which systems can be monitored and data can be shared. Further, integrating automation and hardware only provides so much; organizations must align their objectives with business goals, putting people at the heart of their digital strategy.
What Does It Mean to Be “Connected”?
To create a connected lab, facilities must undergo multiple stages of digital transformation through the integration of technology, optimization of data management, improvement in process, and facilitation of change management across the system. This change is complete through both a digitization of data from analog to digital and the digitalization of lab processes to enable the conversion to digital technology, as well as associated training for teams to manage this shift.
While digitization in the lab refers to the information and how it is stored and managed, digitalization involves optimizing that digital data, for example, through connecting instruments, harmonizing processes and workflows, and reconciling software and data, to optimize the output or workflow of the lab. Looking at one specific example, digitization in the lab may refer to the creation of electronic inventory records. Digitalization would take this one step further and could involve developing a digital inventory tracking system that is connected to supply chain records, enabling scientists to easily reorder supplies as they run low. In this way, it is the digitalization of the process that empowers improvement and increased efficiency, not just having the digital records alone.
Similarly, for a connected lab to truly see improvement in its processes, it must not only have individual elements that are digital or on the cloud, but also optimize these elements to improve how things are done in the lab. Research teams must also be trained on the new equipment, with required reskilling and a redesign of workflows as essential steps in embedding new technology. This training comes with a valuable payoff – this connected ecosystem is what will ultimately free up researchers’ time from quotidian tasks so they can focus on answering challenging research questions to advance new scientific findings.
How Connectivity Fosters Quality
Removing human elements where possible in manual, daily processes can significantly reduce errors and subjectivity of processes in the lab, making results more reliable and ensuring reproducibility. Beyond offering insights that can improve processes in the lab, connected tools can help ensure sample integrity and security beyond that which is available through manual processes and tracking. Data security is a top concern, particularly for patient data, when moving information to the cloud. Implementing a well-architected cloud environment should include:
- Operational excellence
- Security reliability
- Performance efficiency
- Cost optimization
- Ensuring regulatory compliance
To the last point, new digital systems must comply with regulatory requirements for electronic data systems, with mechanisms in place to streamline the audit process. Particularly in today’s regulatory environment, this visibility and transparency can determine if a regulatory audit derails lab operations, or is simply a checkpoint along the way to scientific innovation.
The implementation of laboratory information management systems (LIMS) allows researchers to provide audit records for things like sample management, assay performance, equipment management, and lab processes quickly and more easily. Similarly, tools like blockchain can be used to track and trace products and raw materials throughout the supply chain.
Improving Efficiency with Technology
Automation and data transparency in the lab allows leaders to quickly identify trends in processes that can lead to small, incremental and consistent improvements across the organization. Similarly, cloud-based data systems allow for the rapid and consistent sharing of data across the organization, empowering various stakeholders to remain in sync with each other and the evolving needs of customers across their journey.
The increased collaboration in a digitally connected laboratory also makes training, troubleshooting, and maintenance easier for lab personnel. Ultimately, this improvement in process and visibility helps save costs by improving instrument and equipment uptime. A connected lab can also minimize costs by helping lab personnel more readily identify inefficiencies in process and improve best practices, helping drive revenue growth. With increasingly thin margins and a worsening labor shortage, these improvements to efficiency and the bottom line are vital for laboratory operations to continue.
In a similar vein, tools that leverage artificial intelligence (AI) can be used to perform tasks that typically require human involvement or decision making so that lab personnel can remain focused on higher level work. By managing the live-monitoring or processes and data interpretation, but also real-time troubleshooting systems, AI can be used as a holistic lab manager for many tasks. These applications may include inventory management – monitoring inventory levels and automatically reordering new supplies when they are low – equipment maintenance, and data analysis.
Staying Connected to Remain Competitive
Industry surveys show that researchers have high expectations of the labs they contract, with not only expectations for research evolution but also technology evolution. As COVID-19 demonstrated, processes and workflows may need to rapidly evolve on a moment’s notice and implementing a comprehensive digital strategy is key to building an agile and connected scientific ecosystem. However, it can require adjustments to company culture, and leaders must consider the people, instruments, processes, and data within an organization.
Facilities considering digital transformation must evaluate how workflows may evolve in the future, and how they can adopt the right connected solutions and technologies today to meet the needs of tomorrow. With emerging technologies such as AI helping reduce production costs and optimize performance of the lab, leaders must adapt to remain operationally agile and ready for future challenges.
Future labs will benefit from the emergence of innovative technologies, and someday will likely see fully cloud-based labs, where researchers can access facilities anywhere in the world and manage a physical lab entirely online. As lab managers ready for the next wave of innovation, they must begin their digital transformation journey so they can be prepared to capitalize on the value of continuous monitoring, inventory management, and automated data collection and analysis to reduce manual tasks and increase productivity.
About the Author: Brian Stan is Director of the Connected Solutions group for Thermo Fisher Scientific’s Laboratory Products Division. With partners across the Thermo Fisher organization, Brian and his team are focused on developing and introducing Lab 4.0 solutions which help labs address challenges they encounter while running their daily business operations, achieve better science results, and increase competitiveness. Brian has spent much of his career working on connected solutions for the healthcare and life sciences industries.