The webinar will show how it’s possible to gain a critical advantage in early-phase development by harnessing the power of Artificial Intelligence (AI). It will showcase how predictive AI is used to overcome traditional synthesis challenges, identifying optimal chemical routes that can significantly cut raw material costs and shorten timelines. A case study will highlight the real-world impact of this data-driven approach.
It will also describe how the complex task of solid-form screening can be enhanced by using a powerful AI platform. Machine learning models can even accurately predict and identify the most stable cocrystal forms. Overall, the webinar will provide a clear roadmap for using these AI tools to de-risk programs and accelerate the path to the clinic.
Key Learning Objectives:
- Discover how AI can identify more efficient synthesis pathways
- Learn how machine learning models can predict optimal crystal forms
- Explore the real-world impact of these tools through a detailed case study
Who Should Attend:
- Scientific and Technical Leaders
- Program and Portfolio Managers
- Business Development Managers