In this webinar, discover how Artificial Intelligence (AI) is transforming early-phase drug development by enabling smarter, faster, and more cost-efficient decision-making. You’ll learn how predictive AI is being applied to tackle traditional synthesis challenges, identifying optimal chemical routes that reduce raw material costs and shorten development timelines. A real-world case study will demonstrate the tangible benefits of this data-driven approach.

The session will also explore how AI is transforming solid-form screening. By leveraging advanced machine learning models, Lonza scientists can accurately predict and identify the most stable cocrystal forms, enhancing efficiency and reducing development risks.

This webinar offers a practical roadmap for using AI to de-risk your small molecule programs and accelerate progress to the clinic.

Key Learning Objectives:

  • Understand how AI can uncover more efficient and cost-effective synthesis routes
  • Learn how machine learning predicts optimal crystal and cocrystal forms
  • See how real-world case studies demonstrate measurable impact on speed and success
By clicking "Access Content" you agree to our Legal Disclaimer and the Lonza Privacy and Cookies Policy.
Latest briefing from the Knowledge Center