Case Study: Harnessing CSP and MicroED to Determine Remdesivir’s Most Stable Polymorph in Just 33 Days

Accurately identifying the most stable polymorph is essential for successful drug development, especially when facing tight R&D timelines and limited material availability. Faced with two similar Remdesivir anhydrates, our team utilized an integrated experimental and AI-driven computational approach to quickly pinpoint the most stable polymorph across varying temperatures, ensuring a reliable drug product development. 

Here’s how we delivered results 2x faster than standard polymorph research:

• Utilized MicroED to determine crystal structures of Form II and, for the first time, of Form IV to explain their similar XRPD patterns and properties. 
• Leveraged AI-powered Crystal Structure Prediction (CSP) platform to predict and recommend Form II as the most stable anhydrate at room and high temperatures, well ahead of traditional timelines.