AI-Powered mPredict™ Co-Crystal Prediction Tool: Recent Advances and Experimental Validation
Webinar
In this webinar, you will learn:
- How the mPredict™ service combines quantum chemistry and machine learning to generate ranked co-former reports from your API's SMILES input
- What's new in mPredict™: improvements to model architecture, a refined library of 600+ carefully selected co-formers, and integrated toxicity estimation
- How our experimental screening capabilities can take your project from in-silico prediction to lab-validated results
- Key findings from a real experimental case study: mPredict™ predictions tested and validated in the lab
Speakers
Daniel Bischof
Merck
Senior Scientist
Daniel is a senior scientist at Merck, specializing in predictive formulation within the excipients product development group.
His work focuses on developing in-silico tools that combine machine learning and computational chemistry for co-crystal prediction.
He holds a Ph.D. in physics from Marburg University, where he researched the growth and optical properties of crystalline organic materials, combining experimental approaches with DFT-based modelling and data science methods.
Axel Becker
Merck
Associate Director
Axel is an associate director and heading the solid-state chemistry laboratory within Site Management Lab Services group at the Darmstadt headquarter site for 10 years. His team works on solid-state selection screenings as well as development and optimization of lab-scale based crystallization processes.
Axel is a Chemical Engineer from background, with strong focus on analytical applications.
Axel has now more than 20 years’ experience in small-molecule solid-state sciences, and he is co-inventor of several solid-state-related patents as well as author of peer-reviewed publications in the field.
Small Molecules Analysis and Quality Control
- Small Molecules Analysis and Quality Control
Duration:1h
Language:English
Session 1:presented September 3, 2026