The digital era has arrived in full force as a result of the pandemic — but many laboratories are just at the beginning of their journey to digital transformation. To meet the demands of increasing data volumes and device connectivity, new ways of documentation and instrument monitoring have emerged such as digital lab notebooks and cloud-based platforms to enable users to securely record data and protocols, track samples, and access lab devices from any location. However, with regulatory barriers to overcome and highly-sensitive data at stake, life science and pharmaceutical industries have been slow to adopt these technologies, leaving the full benefits of lab connectivity and automation yet to be realized.
“With so much connectivity in our own lives, when you step into a lab, it can feel like you're stepping back in time,” says Dr. Geoff Gerhardt, Chief Technology Officer and co-founder of Scitara, a company dedicated to empowering lab digitalization through its cloud-based Scientific Integration Platform SIP. “People are quite surprised when they realize you can have the same level of connectivity and user experience from the consumer space in the lab now.”
One of the major reasons the science industry has lagged behind other sectors in the adoption of digital technology is the unique diversity of instrumentation, applications, and services found within most labs. Relying upon both legacy systems and new technologies, researchers can generate vast amounts of disparate data at each step of an experiment, with efficient data transfer hindered by one-to-one vendor-specific connections, siloed instruments, and manual transcription processes.
Connecting these data sources requires an integration platform to curate, store, interpret, and share data more effectively and efficiently. In addition, as instruments become more sophisticated and big data becomes an integral part of research, there is a growing pressure upon lab infrastructure to house the increasing quantities of this crucial data.
As a solution to these challenges, cloud-based iPaaS (Integration Platform as a Service) offerings have emerged that can enable companies to connect instruments, applications, web services, and informatics systems to a single data source in the cloud. In comparison to traditional data management infrastructure such as on-site servers, these platforms allow data to be shared seamlessly in real time across multiple locations, offer virtually unlimited data capacity, and provide a host of add-ons that can improve the speed and scope of research efforts.
Cloud-based connectivity can also enable advanced analytics to be quickly scaled and deployed along the entire value chain, from using instrument utilization data to streamline routine maintenance, to leveraging advanced technologies such as artificial intelligence and machine learning to drive deeper research insights and derive next steps. “Once you have everything connected and talking, you can interrogate the stream of event activity in the lab and access all this contextual information,” explains Gerhardt. “A lot of our customers didn’t anticipate the level of analytics that you can now put on top.”
Despite these advantages, hesitancy to use external networks and cloud-based software solutions has persisted for decades among life science and pharmaceutical companies due to concerns relating to regulatory compliance, data security, and the control of sensitive data.
Scitara’s cloud-based Scientific Integration Platform harnesses the power of emerging technologies to connect entire ecosystems of lab instruments, applications, and services to enable the seamless exchange of scientific data in real time.
The heart of the SIP, Digital Lab Exchange DLX™ is a secure, compliant technology and service suite that connects entire enterprises to a global, cloud-based digital platform. In doing so, it enables users to automate tasks and workflows, ensure data integrity and deliver true data mobility.
Only recently has this started to change, fueled by a growing acceptance that the benefits of cloud-based architectures can in many cases outweigh the perceived risks. “It's been an evolution, even just over the last three years, of how comfortable companies are with the cloud,” says Gerhardt. “I think as a lot of these companies get comfortable with the security, then true cloud deployments are going to become more common.”
Cloud environments have long been perceived to be less secure than on-premises systems. However, as data security is the crux of any reputable cloud service, providers tend to incorporate many more layers of encryption and employ large numbers of security professionals to continuously monitor potential threats and respond to incidents, offering a level of data protection that most on-site IT departments can’t manage themselves.
In addition, concerns over ensuring continued compliance with data integrity and evolving regulatory requirements have become increasingly addressed by advances in cloud integration software. iPaaS platforms such as SIP can provide end-to-end data integrity and compliance for data in flight, along with configurable accessibility settings to prevent risks of human input errors or data manipulation. “When our system is in place, all lab activity is recorded in an event stream, making it possible to track workflow progress, avoid bottlenecks, and obtain all the relevant information for audits,” adds Gerhardt.
Across the pharmaceutical industry, the control of data remains one of the biggest barriers to cloud implementation, with companies moving to cloud-based platforms seeking to retain internal oversight and management rather than rely solely upon external providers. “Deployment options are now a major point of discussion and private clouds have become the new on-premises,” says Gerhardt. While offering greater control over data privacy, “single tenant installation means companies have to manage our application in their own private cloud and, like any cloud system, it has dependencies on many additional services,” he warns. “This can be difficult for companies to manage as opposed to just allowing the software to exist in our cloud and connecting all their devices.”
Deployment options also have regulatory implications, as any new updates to the system need to be validated. “We have a multi-tenant version and there are cost benefits from sharing that infrastructure with several tenants, however, if the software is updated, each of those tenants has to validate this new version,” explains Gerhardt. “That's another reason companies like their own version running in their own cloud so when an update is available, they can schedule when they're going to revalidate and move to that.”
As with any system migration, the implementation of cloud-based platforms can be seen by many as a daunting task, and Gerhardt concludes by offering the following advice for those looking to make the shift, “It can be overwhelming initially, but you don’t need to wipe the slate clean and start from ground zero,” he says. “All your systems can still stay in place – just find a workflow that you want to better automate, connect those instruments and informatics, and build out from there.”
To this end, improving the ease of implementation and broadening who can use iPaaS solutions is a key focus for future development. “Our clients want to have applications that regular analysts can configure, and not just experienced lab IT managers,” he adds. “This is pushing us to make more low-code or no-code interfaces, where users can simply drag and drop to manipulate data and move it around without knowing code.”
With cloud computing expected to grow at an annual rate of 14.9% over the next five years1, life science and pharmaceutical companies, as well as manufacturers, are likely to further embrace these technologies to stay competitive. “We’ve found ourselves in a nice nexus of demand, where the instrument companies that provide all this great technology are a bit weary of explaining how to connect their instruments, and customers just want everything to work better,” says Gerhardt. “For us, it's just getting all these things connected. I'm looking forward to the time when we've got broad connectivity, but for now, it’s a lot of work and the quicker we can get on top of this, the better,” he concludes.
1. Grand View Research (2020) Cloud Computing Market Size, Share & Trends Analysis Report By Service (SaaS, PaaS, IaaS), By Workload, By Deployment, By Enterprise Size, By End-use, By Region, And Segment Forecasts, 2020 – 2027