Accelerated Identification of the Most Stable Remdesivir Polymorph in 33 Days Using an Integrated Experimental and Computational Approach

Blog details
2 min read
Share this:
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. 
Your next success starts here

Recommended articles

Hit Identification – SARM1 Structural Elucidation By Internal Cryo-EM Platform
How XtalPi Utilized MicroED to Tackle Different Polymorphism Challenges
Hit Identification – Novel Hits for GPX4
Application Note: DEL Screening