Next-Gen Drug Discovery at Our Smart Research Lab

Recent stories to learn more about the Smart Research Lab

Background and Purpose

Complex fields like molecularly targeted therapies and antibody-drug conjugates (ADCs) have long timelines from candidate identification to clinical trials.

Traditional research approaches struggle with speed, reproducibility, and managing vast data. To overcome these challenges, an advanced drug discovery data platform is essential.

Thankfully, artificial intelligence (AI)-driven predictive modeling and simulation now enable the utilization of large-scale, high-precision data critical for success. However, they also require advanced automation and highly integrated systems.

Daiichi Sankyo’s SRL in San Diego was established to meet this need, leveraging robotics and proprietary software to accelerate and enhance the generation of new drug candidate.

Differences Between SRL and Conventional Drug Discovery

Traditional drug discovery relies on manual work and researchers’ intuition, making processes slow and variable. In contrast, the SRL’s data-driven discovery automates data collection and standardization, applying AI and machine learning for analysis.

Integrated workflows also enable real-time feedback and predictive modeling, allowing faster, more accurate candidate selection. This approach significantly reduces time and cost, accelerating research and development. Simultaneously, extensive standardized data open the door to new scientific discoveries.

Functions, Features, and Proprietary Software Driving Drug Discovery

• Advanced software combines with robotics to automate experimental instruments under a unified control system.
• Robots run 24/7, 365 days a year, executing experiments and generating large volumes of data.
• In-house developed systems manage the entire workflow—experimental design, sample handling, robot execution, metadata capture, and cloud integration.
• Processes and data structures tailored to Daiichi Sankyo enable multidimensional data utilization and future AI compatibility.
• AI-ready infrastructure supports predictive modeling and machine learning for faster, more accurate drug candidate selection.
• Application of FAIR principles ensures data is “Findable, Accessible, Interoperable, and Reusable,” improving reproducibility and transparency.
• Proven hardware and proprietary software are leveraged for an optimized, integrated platform that accelerates drug discovery for strategic advantage.

Why San Diego is Important

• San Diego, California, is one of the leading U.S. centers for biotechnology and pharmaceutical innovation.
• The location means more access to collaboration opportunities with companies and universities specializing in AI-driven drug discovery and robotics.
• Ideal for recruiting engineers with expertise in advanced system technologies and pharmaceutical development.
• The facility is built for seamless automated workflows and close collaboration between researchers and engineers.
• Daiichi Sankyo’s first dedicated drug discovery research base in the U.S., strengthening our global R&D framework.

Empowering Researchers Through Automation

By integrating everything from experimental design to robotic execution and automated data collection, SRL minimizes manual tasks and time constraints.

Automated systems enable large-scale sample evaluation under diverse conditions and 24/7 operation, accelerating screening and evaluation.

Routine, repetitive work—essential but time-consuming—is handled by robots and proprietary software, freeing researchers to focus on high-value activities like hypothesis generation and strategic design.

Scope of Lab Smartification: Next-Generation DMTA（Design, Make/Build, Test, Analyze/Learn）Cycle Enabled by Digital Technology and Automation