AI-Powered ADME model building

Cresset AI ADME is a next-generation, AI-powered model building technology designed to generate highly predictive, confidence-scored ADME(T) and physicochemical property prediction models from proprietary data. It is built for medicinal chemists, computational scientists, and data scientists who need to turn their in-house data collections into reliable predictive tools that accelerate early-stage drug discovery and reduce late-stage failures.

Developed in collaboration with Cresset's Discovery Services team, AI ADME applies Cresset's proprietary patent-pending Superlearner AI technology to construct models that run on servers securely hosted on your corporate infrastructure. These models can be applied to analyze molecules during early-stage discovery, proactively flagging ADME(T) risks before costly downstream investment, and enabling go/no-go decisions in minutes.

Core Capabilities of the Superlearner AI Technology

• Exploits curated proprietary data to build models tailored to your compound collections
• Combines multiple algorithms to achieve superior prediction accuracy compared to any individual model
• Automatically leverages the best-performing models for each ADME(T) and physicochemical property endpoint
• Delivers robust predictive performance even in novel chemical space

Key Benefits for Drug Discovery Teams

• Accelerate discovery by making go/no-go decisions in minutes and avoiding late-stage ADME failures
• Solve ADME challenges efficiently by screening millions of virtual compounds for optimal profiles and optimizing for multiple ADMET endpoints while maintaining target activity
• Explore candidate space effectively — prioritize synthesis efforts and optimize lead compounds to balance potency with ADME properties
• Increase confidence in decisions with uncertainty estimates for every prediction, and identify safety concerns before clinical trials

Confidence Scoring and Trustworthy Predictions

• AI ADME's proprietary Confidence Score correlates reliably with property prediction accuracy
• Confidence scoring increases user trust and drives broader model adoption across discovery teams
• Accurate and customizable ADME parameter prediction supports reliable prioritization of molecules

Customization and Integration

• Generate highly predictive regression and classification models for a variety of ADME(T) and physicochemical properties
• Integrate seamlessly with company workflows and infrastructure via a REST API, enabling frictionless communication with existing molecule discovery platforms

Scalability

• Calculate properties for thousands or millions of compounds using a highly scalable, cloud-native platform
• Evaluate huge virtual libraries that would be impossible to test experimentally

AI ADME is available today through Cresset Discovery Services, where Cresset's experts work collaboratively with your team to discuss ADME modeling needs and define project objectives. Models are deployed on securely hosted corporate infrastructure, supporting compliance with data governance requirements while enabling full integration into existing discovery pipelines.