🔒Fast, accurate drug development: Rentschler Biopharma is harnessing AI-driven automation to stay competitive

Inside Rentschler Biopharma’s facility in Milford, a new liquid-handling robot is being installed to take over one of the most repetitive – and time-consuming – steps in drug development: preparing and diluting samples for testing. For a process that can be repeated thousands of times in bringing a single therapy to market, even small efficiency gains can ripple outward, shaving time off development and freeing up scientists for higher-level work. That kind of incremental speed is becoming a competitive necessity among contract development and manufacturing organizations, where Rentschler and other Central Massachusetts CDMOs contend against hundreds of competitors across the country to work with pharmaceutical companies to bring drugs to market. “Our clients are asking for more data that we deliver to them, and they also want our insights about what that data is,” said Gerrick Rodrigues, global head of IT at Rentschler. CDMOs’ partnerships with pharma companies are long-term and resource-intensive. Bringing a new drug to market takes 10 to 15 years and up to $2.6 billion, according to Washington, D.C.-based Pharmaceutical Research and Manufacturers of America. Rentschler plays a significant role in that process, having contributed to nearly 25% of the 17 biopharmaceuticals approved by the U.S. Food and Drug Administration in 2023.

Push for AI-driven automation

Generative AI is expected to create up to $110 billion in economic value annually worldwide by speeding up drug development, according to a 2024 report by global consulting firm McKinsey & Co. That includes $28 billion for research and early discovery processes and another $25 billion for clinical development. The FDA’s Center for Drug Evaluation and Research has seen a significant increase in the use of AI throughout the drug product life cycle, leading to the creation of its AI Council in 2024.

This push toward automation can be credited to drug development’s diversification, including an increase in advanced gene therapies, cancer therapies, and biosimilars, said Joe Makowiecki, director of product management and process engineering, integrated solutions at Cytiva, a biotechnology company with a U.S. headquarters in Marlborough. At Rentschler, deciding the tasks to automate can be simplified to one question: “Is the juice worth the squeeze?” Rodrigues said. The Germany-based CDMO focuses on manufacturing and administrative steps that can be digitized to improve speed, efficiency, and accuracy. With 270 local employees and 1,400 worldwide, Rentschler is the 16th largest life sciences and biotechnology firm in Central Massachusetts. On top of the firm’s new liquid-handling robot, Rentschler uses software that automates and integrates business functions to cut down on manual, iterative administrative tasks like processing invoices. The company uses AI to prepare documents, such as analytical reports, that are then reviewed, edited, and finalized by experts. “Our digitalization and automation roadmap focuses on ‘How do we gain value?’” Rodrigues said. “We need to balance that investment of our people's time and effort with what their reward of that outcome is.”

Veristat, a fellow CDMO out of Southborough, uses a similar approach. The firm feeds statistical data into AI tools to help prepare documents such as clinical study reports, safety narratives, and regulatory briefings. These tools can draft up to 80% of certain sections, said Kyle McBride, Veristat’s vice president of statistical analysis. This can reduce report-writing time from two to three months to five to 10 days, allowing medical writers to focus on the interpretation of data. “It's helping us get to decisions that are backed by the data,” said McBride. “It helps us get there faster and with more confidence.”

Moving faster, smarter

A growing need in drug development calls for automation to connect equipment and centralize data, known as the orchestration layer of a control system, said Makowiecki. Rentschler uses a manufacturing execution system that pulls data from the company’s pumps, flow systems, and filters to make sure they’re working properly, said Rodrigues. “What it allows us to then do is to analyze [data] and look for inefficiencies or opportunities to refine or adjust so that we can ensure that we're being as efficient as possible in the production process,” he said. Implementing automation in these ways allows CDMOs to deliver more data, faster and differentiate themselves to stay attractive to biopharmaceutical companies, Makowiecki said. “And typically, a way of differentiation is ‘We move faster,’ or ‘We leverage intelligent digital solutions to help us move you faster through process development,’” he said. That speed can’t come at the cost of quality, Rodrigues said. “The inherent risk in a digitalization and automation roadmap and journey is to see it as the answer,” said Rodrigues. “Automation enables that efficiency, it gets value. It enables flexibility, but it isn't, in and of itself, a solution.” Rentschler would never implement automation in certain areas, including direct interaction with a client. “It doesn't take the experts out of that space in place,” said Rodrigues. “It doesn't take the critical role of collaboration.” Rentschler has organized an internal AI working group to evaluate current processes that are working efficiently and to identify areas where automation could prove beneficial. “For us, it's the ability to deliver the work we do,” said Rodrigues. “It's also the ability to then have deeper engagements and bring more, better benefit to our clients.” Mica Kanner-Mascolo is a staff writer at Worcester Business Journal, who primarily covers the healthcare, manufacturing, and higher education industries.