AI-ENABLED PHARMACEUTICAL COCRYSTAL SCREENING

This white paper from Lonza and the American Chemical Society explains how AI-enabled cocrystal screening can help pharmaceutical companies identify promising solid forms of APIs earlier. By using machine learning to prioritize potential cocrystal candidates, the approach can reduce trial-and-error experiments, improve development efficiency, and support better decisions around drug stability, bioavailability, and manufacturability.

• AI-powered screening: Machine learning helps identify promising API–coformer combinations from large chemical datasets.
• Reduced trial and error: The AI model helps researchers focus laboratory testing on the candidates most likely to succeed.
• Strong predictive performance: The model correctly predicted experimental outcomes in approximately 8 out of 10 cases during validation.
• Secure & data-driven: Lonza processes molecular information within secure infrastructure while using AI to support early decisions on solid-form development.