ADMET Predictor® is a flagship artificial intelligence and machine learning platform designed for scientists involved in drug discovery and chemical risk assessment. It empowers users to design and evaluate high-quality compounds that are safe, effective, novel, and easy to synthesize. The platform provides comprehensive ADMET (absorption, distribution, metabolism, excretion, and toxicity) modeling capabilities, extended with features for data analysis, extensive metabolism predictions, and AI-driven drug design. The software quickly and accurately predicts over 175 properties, including aqueous and biorelevant solubility vs. pH profiles, logD vs. pH curves, pKa, CYP and UGT metabolism outcomes, key toxicity endpoints like Ames mutagenicity and drug-induced liver injury (DILI) mechanisms, and major systemic PK endpoints using integrated high-throughput GastroPlus® PBPK simulations. It integrates market-leading ADMET modeling with AI-driven drug design, data analysis, SAR (Structure-Activity Relationship), and cheminformatics capabilities, supporting scientists across computational chemistry, medicinal chemistry, DMPK (Drug Metabolism and Pharmacokinetics), and safety assessment disciplines. Built using premium data from pharmaceutical companies and innovative molecular and atomic descriptors, ADMET Predictor produces highly accurate custom models. Its enterprise-ready automation, available through REST APIs, Python wrappers, KNIME components, and other data connectors, allows seamless integration of property calculations into third-party informatics platforms such as Certara D360, Schrödinger LiveDesign®, or BIOVIA Pipeline Pilot. The system can run multi-threaded for high-speed property calculation, including predicted sites of metabolism and metabolite trees, without consuming additional licenses.

Features & Benefits

• Extensive Property Prediction
  • Quickly and accurately predicts over 175 ADMET properties crucial for drug discovery and chemical risk assessment.
  • Aqueous and biorelevant solubility vs. pH profiles
  • LogD vs. pH curves and pKa
  • CYP and UGT metabolism outcomes
  • Key toxicity endpoints including Ames mutagenicity and drug-induced liver injury (DILI) mechanisms
  • Major systemic PK endpoints using integrated high-throughput GastroPlus® PBPK simulations
• AI/ML-Driven Drug Design & Modeling
  • Leverages artificial intelligence and machine learning for advanced ADMET modeling, AI-driven drug design, and data analytics.
• Enterprise-Ready Automation & Integration
  • Facilitates seamless integration into existing enterprise workflows and third-party informatics platforms.
  • REST APIs and Python wrappers
  • KNIME components and other data connectors
  • Integration with platforms like Certara D360, Schrödinger LiveDesign®, and BIOVIA Pipeline Pilot
  • Multi-threaded operation for high-speed calculations
• High Accuracy & Confidence
  • Provides reliable predictions based on premium datasets and advanced modeling techniques.
  • Models trained on premium datasets from public and private partner sources
  • Model applicability domain assessments
  • Confidence estimates and regression uncertainty for all models
• Modular & Flexible Design
  • Offers a modular architecture allowing users to purchase and utilize specific functionalities as needed.
  • AI-Driven Drug Design (AIDD)
  • ADMET Modeler™
  • High-throughput pharmacokinetic (HTPK) Simulation
  • MedChem Studio™
  • Metabolism
  • Physicochemical and Biopharmaceutical (PCB)
  • Toxicity
  • Transporters
  • DILIsym® Inputs Module
• Customization & Support
  • Provides tools for tailored analysis and robust customer assistance.
  • Customizable visualization tools including distribution and 2D/3D scatter plots
  • Ability to build or extend machine learning models
  • Excellent customer support