QIP-ADMET

QIP-ADMET™ is an AI-powered ADMET prediction platform developed by Standigm, designed to accelerate pharmaceutical drug discovery by delivering highly accurate and robust predictions of absorption, distribution, metabolism, excretion, and toxicity properties. The tool is built for drug discovery scientists and pharmaceutical R&D teams who require reliable, data-driven insights to make confident decisions throughout the drug development process.

At the core of QIP-ADMET™ is a Quantum-Informed Pretrained (QIP) modelling approach. The platform is trained on extensive and diverse datasets that combine experimental data, in silico quantum mechanical (QM) data, and molecular descriptors, enabling comprehensive and dependable ADMET profiling across a wide range of chemical space.

Key Capabilities

• Accurate ADMET prediction powered by advanced AI models trained on experimental and quantum mechanical data
• Integration of molecular descriptors alongside QM data to enhance model robustness and coverage
• Quantum-informed pretraining methodology that pushes the boundaries of conventional ADMET prediction accuracy
• Comprehensive ADMET insights supporting data-driven decision-making in pharmaceutical development

Why QIP-ADMET™

• Unparalleled accuracy derived from a multi-source training strategy combining real-world experimental results with in silico quantum mechanical simulations
• Robust performance across diverse compound libraries, reducing the risk of late-stage attrition in drug development pipelines
• Designed to facilitate faster, more confident go/no-go decisions during lead optimisation and candidate selection

QIP-ADMET™ is offered by Standigm, a company focused on AI-driven new drug research and development. The platform is accessible via a demo environment and is supported by published whitepapers and scientific papers, reflecting Standigm's commitment to transparency and scientific rigour in AI-based drug discovery tooling.