AI- and Model-Based Tools to Streamline Drug Development

This Lonza resource explains how AI, high-throughput experimentation (HTE), and model-based tools can streamline small-molecule drug development. These technologies help researchers select better synthetic routes, optimize processes faster, reduce development risks, and improve scalability from early development through commercialization.

• AI-enabled route scouting: AI combines chemical, pricing, and supply-chain data to identify synthetic routes that are efficient, scalable, and economically feasible.
• High-throughput experimentation: HTE enables researchers to test many reaction conditions in parallel, reducing time and resources needed for process optimization.
• Design2Optimize™: This model-based platform combines DoE with existing process knowledge to build predictive models and reduce the number of experiments required.
• Faster, lower-risk development:Combining AI route scouting, HTE, and Design2Optimize™ helps improve process scalability, identify risks early, and accelerate the path from API development to commercialization.