Model Medicines, Inc.
Model Medicines is a pharmatech company dedicated to transforming the drug discovery and development industry by leveraging artificial intelligence (AI) and machine learning (ML). Founded in 2019 and based in La Jolla, CA, the company focuses on accelerating the creation of life-changing drugs, with a pipeline of over 90 assets targeting oncology, infectious diseases, gastric, neurological, and weight disorders. Their mission is to develop best-in-class therapeutics efficiently, emphasizing innovation at the intersection of data science, biology, and drug development.
Industries
Nr. of Employees
small (1-50)
Model Medicines, Inc.
La Jolla, California, United States, North America
Products
Preclinical small-molecule candidate portfolio
A portfolio of AI-discovered small-molecule candidates across multiple therapeutic areas with reported discovery metrics and in vitro/in vivo validation results.
Preclinical small-molecule candidate portfolio
A portfolio of AI-discovered small-molecule candidates across multiple therapeutic areas with reported discovery metrics and in vitro/in vivo validation results.
Services
AI-driven lead discovery with in vitro validation
Collaborative discovery engagements that combine generative AI and molecular-embedding models with targeted in vitro cellular assays to generate and validate novel small-molecule candidates against specific targets.
Preclinical development collaborations
Project-based partnerships to advance validated hits through medicinal-chemistry optimization and candidate nomination, including arrangements for independent preclinical validation with external laboratories.
AI-driven lead discovery with in vitro validation
Collaborative discovery engagements that combine generative AI and molecular-embedding models with targeted in vitro cellular assays to generate and validate novel small-molecule candidates against specific targets.
Preclinical development collaborations
Project-based partnerships to advance validated hits through medicinal-chemistry optimization and candidate nomination, including arrangements for independent preclinical validation with external laboratories.
Expertise Areas
- AI-driven small-molecule discovery
- Generative molecular design and large-scale chemical-space exploration
- Graph neural network models for molecular prediction
- Preclinical development and in vivo efficacy demonstration
Key Technologies
- Generative models for small-molecule design
- Geometric/graph neural networks
- Molecular embedding vectors
- Deep learning for toxicity and mutagenicity prediction