Model Medicines Publishes Groundbreaking Preprint on AI-Driven Drug Discovery

This preprint, "ChemPrint: An AI-Driven Framework for Enhanced Drug Discovery," showcases the groundbreaking work being conducted by our team, leveraging the power of artificial intelligence to revolutionize the drug discovery process.

Highlights

• Unprecedented Efficiency: ChemPrint, our proprietary AI model, achieved a remarkable 45.5% in vitro hit rate in our oncology program targeting AXL and BRD4, a massive increase over average rates reported by industry leaders like Schrödinger and others.

• Novel Chemical Discoveries: Compounds identified by ChemPrint exhibited substantial chemical novelty, with an average Tanimoto similarity score of 0.32 to their training set, significantly diverging from known compounds and demonstrating ChemPrint's capability to extrapolate beyond traditional benchmarks.

• Innovative Methodology: Our novel train-test splitting methodology, utilizing t-distributed Stochastic Neighbor Embedding (t-SNE), enables our models to navigate uncharted molecular territories accurately.

• Adaptive Molecular Embeddings: ChemPrint employs adaptive molecular embeddings that preserve vital chemical and structural information throughout the AI discovery process, facilitating a more nuanced comprehension of the molecular interactions fundamental to identifying viable therapeutic agents.