Making the ‘lab of the future’ the ‘lab of today’

With the right technology and strategy, pharmaceutical companies can transform their labs—and drive business outcomes.

In the pharmaceutical and life sciences industries, the lab of the future is a visionary concept for a fully modernized laboratory, complete with the most advanced technology available. As technology has evolved over time, so has the vision for what the lab of the future should look like. That is, until now. 

With the rise of advanced data and predictive analytics capabilities and cutting-edge artificial intelligence (A.I.) and machine learning (ML) solutions comes the potential for a digitized, streamlined, automated lab that is no longer just a future vision but a tangible reality today. And this lab transformation—when implemented with clear, long-term digital strategy—has the potential to drive significant value for today’s pharmaceutical companies.

Harnessing the power of technology 

The time to invest in the lab of the future is now, or else, organizations risk falling behind, according to Gaurav Marya—strategic business unit head and global head, mergers and acquisitions, Life Sciences, at leading IT services and business consulting firm Cognizant.

“There are a lot of companies sitting on the sidelines, waiting and watching where the industry is heading,” Marya says. “They’re not taking that leap of faith toward modernizing their labs, and the longer they wait will only increase the pain to catch up with the competition. And, ultimately, it will become very cost prohibitive.”

From a monetary perspective, applying A.I.-based solutions to modernize labs could save life sciences leaders up to a staggering $360 billion a year alone, and with automation, they could save another $25 billion annually. Cloud applications and smart data management tools could help lab stakeholders reconcile diverse information sources and ensure that data is shared seamlessly. ML capabilities, which allow devices to learn from every new interaction, could help lab systems become smarter, more self-aware, and more cybersecure. And automation functions can streamline workflows and processes and minimize human time spent on routine lab tasks.

For example, Marya explains, robots could take over the repetitive task of injecting fluid into testing samples; ML could help take care of regulatory submissions and audits, as well as validate treatments once they are in the development stage; and predictive analytics could prevent quality issues from occurring before they happen. 

“The key approach is for the machines to do the mundane—error-free—while the humans do the high-end and leverage technologies for decision-making,” says Saurav Ghosh, senior director and lab practice head, Life Sciences, at Cognizant. 

When it comes to business results, smart technology-enabled labs could give pharmaceutical companies the ability to offer more personalized treatments and accelerate drug approval processes to bring them to market faster and more reliably.

“A modern lab will play a huge role in reducing the time needed to develop methods of drug product analysis,” says Marya. “Advanced technology, automation, and an integrated system will allow therapy stakeholders to have a more collaborate environment, make decisions quickly, and reduce the time to market for treatments.”

Thinking strategically and finding the right partner

So if the technologies to fully digitize and modernize labs exist, and the business case for them lies in plain sight, why haven’t pharmaceutical labs already undergone the transformation? According to a 2021 Cognizant report on the future of work, while companies may be adopting small, sectionalized digitization practices, many lack clear long-term strategies. That’s where companies like Cognizant can help organizations modernize and digitize their labs.

“We listen to the customer and understand what their aspirations are as well as their current landscape. We have worked with some of the larger vendors in the life sciences space to streamline their lab processes and maximize their efficiencies, whether in the sample preparation, data entry, or analysis areas, and help them if they are struggling with the technology,” Marya says. “Having the right partner who can show you the guideposts toward a fully modernized and digitized lab is critical, and its impact will go a long way—from a cost perspective, a regulatory perspective, and an impact perspective.”

Cognizant’s work in the life sciences space includes helping a global biotechnology leader create an A.I. application, powered by ML and natural language processing technology, to analyze and extract meaning from every note that its patient services division had taken. Doing so allowed the firm to drastically improve customer care, enhance workflows, and heighten patient engagement and outcomes. Similarly, Cognizant’s data science and analytics experts worked with a life sciences company to automate and analyze information on clinical trials. These efforts allowed the company to reduce drug outcome review times from 20 months to just 20 days and shorten the oncology drug development process by four years.

When Cognizant partners with companies to help guide their lab transformation strategies, it provides a step-by-step framework on how to approach the process that includes four layers of IT investment. The first layer companies should build is a foundational layer that underlies all laboratory processes and interactions, including systems to manage samples, documents, and data. The second is an integration layer to promote smooth data flows and connectivity among lab systems. The third is a data orchestration layer which can standardize and reconcile information from a host of different sources and formats. And the fourth is an overarching predictive analytics layer, featuring tools that can help scientists quickly gain vital insights and more effectively manage and enhance metrics, such as lab efficiency and time to market, with new solutions.

“The foundational layer is the most important,” Ghosh says. “Building it requires departments to come together and really talk to each other to figure out the standard for how all data and technology capabilities are going to work together and operate seamlessly.” 

And if pharmaceutical companies need an ultimate guiding light as they have conversations about laying the groundwork for their lab transformation efforts, Ghosh has one to offer. 

“The end goal is about the success of therapies and serving the patients and the communities at large,” he says. “A highly digitized modern lab drives better outcomes for our patients. So the investment is totally worth it.”