Inside Daiichi Sankyo’s Smart Research Lab: A High-Tech Hub for AI-Driven Drug Discovery

Daiichi Sankyo’s Smart Research Laboratory in San Diego integrates robotics, automation, and AI-driven tools within a uniquely renovated 10,000-sf space, enhancing drug discovery efficiency through continuous autonomous operation. Image: Daiichi Sankyo

Healthcare company Daiichi Sankyo has launched a cutting-edge research laboratory in San Diego, CA, to enhance and accelerate its drug discovery efforts through robotics, automation, and advanced software. The new facility is designed to streamline data generation and analysis, supporting AI-driven approaches to identify potential drug candidates more efficiently. By leveraging autonomous robotics that operate continuously alongside sophisticated data management software, the lab aims to improve research productivity and enable scientists to focus on intellectual advancements.

Lab Design News spoke to Daniel Rines, PhD, site head, Smart Research Laboratory, Daiichi Sankyo, about how this initiative will revolutionize the company’s research processes, driving innovation and expediting the development of life-changing medicines for patients worldwide.

Q: What were the primary objectives for establishing the "Smart" Research Laboratory in San Diego, and how do these align with Daiichi Sankyo’s broader R&D goals?

A: Daiichi Sankyo aims to accelerate the development of life-changing medicines and deliver them to patients around the world as quickly and efficiently as possible. By leveraging the extensive data collected by autonomous robotics that operate continuously and cutting-edge software for automated orchestration and data management, the laboratory is set to revolutionize Daiichi Sankyo’s research processes as it will not only achieve unprecedented levels of repeatability and productivity but also enable our scientists to concentrate on intellectual advancements and leverage AI-based analytical tools.

Q: How did the incorporation of robotics, automation, and AI-driven tools shape the laboratory’s architectural and technological design?

A: First, we designed overall labs through a collaboration between our scientific staff in Japan and the automation team in the US. We leased a 10,000 sf (1000 sm) facility that required a unique set of renovations before the robots and automated research equipment could be installed. The new team is currently installing and testing the new technology. We are also developing sophisticated software tools to incorporate robotics and other tools.

Q: What specific feedback did you gather from scientists and other end-users during the design phase, and how did this input influence key design decisions?

A: We gathered various feedback from scientists and research functions, and decided to identify sample management and evaluation, followed by data management as an initial scope to improve research workflow in the Smart Research Lab.

Q: How does the laboratory’s design support continuous operation of autonomous robotics while maintaining optimal conditions for precision and reliability?

A: The design qualifies as a wet lab but offers functionalities beyond a typical wet lab. This Smart Research Lab conducts experiments through automation of robots and equipment using proprietary software (this part corresponds to the "wet" aspect) to generate data. The key feature is that the scientific team enters their experimental protocols online and then those are executed by the robotic platforms. Of course, the results are automatically stored in the data management system, where the profile data of a given asset is systematically consolidated and organized.

The lab’s innovative design enables scientists to input experimental protocols online, which are executed by robotic platforms, with results automatically stored in a sophisticated data management system for seamless analysis. Image: Daiichi Sankyo

Q: Were there any unique challenges in integrating advanced software and hardware tools into the laboratory's infrastructure? If so, how were they addressed?

A: The features of our proprietary software are highly unique to our lab. Software to control each robot is not new; however, orchestrating a fully automated lab introduces many new challenges not previously addressed in the field. The resulting software reflects our experience and expertise in drug discovery research so scientific rigor and intent is maintained. While we cannot disclose the details, we believe it is superior to external vendor software in terms of streamlining the drug discovery process and integrating with peripheral systems.

Q: How does the laboratory’s layout promote collaboration among scientists and engineers while ensuring the efficiency of automated processes?

A: Scientists and engineers are working closely in the labs. They deal with each discipline’s unique challenges to identify robust solutions that become more than the just the sum of the parts assembled.

Q: In what ways does the design support the long-term scalability and adaptability of technologies used in drug discovery efforts?

A: Flexibility and scalability are important point of the design and was an important part of the overall lab implementation.

Q: Can you elaborate on how sustainability and energy efficiency were incorporated into the construction and operational plans for the facility?

A: We considered that point. Regarding operational plans, developing a more robust approach to experimental execution saves on use of reagents, reduces hazardous material generation, debulks the use of plastics, and robots can be packed in tighter than lab benches for scientists.

Q: What role did end-user feedback play in designing spaces for data management and analysis, and how do these spaces enhance productivity?

A: There is feedback to minimize manual operation on the data management and analysis, leading to reduction of human error and data fluctuations dramatically by the combination of the automation and online software tools.

Q: Looking ahead, how do you see the laboratory’s design and technological capabilities evolving to meet future advancements in drug discovery and AI-based research?

A: Drug discovery workflow could be evolved from current workflow to adapt advanced technologies including AI. Our lab design and standardized experimental technology capabilities help to harmonize data. Through standardization, we increase the FAIR (findable, accessible, interoperable, and reusable) value of our data and increase its application to future therapeutic development. In the future, there is a possibility of introducing similar functions to our laboratories in Japan.