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Rapid ADME predictions of drug candidates

Enhancing drug development with ADME properties prediction

QikProp is an advanced tool for predicting pharmacokinetic and physicochemical (ADME) properties of small organic molecules based on the full 3D molecular structure.

Approximately 40% of drug candidates fail in clinical trials due to poor ADME (absorption, distribution, metabolism, and excretion) properties, leading to soaring development costs. Early detection of problematic candidates can significantly reduce wasted time and resources.

Accurate ADME prediction, prior to costly experimental procedures like HTS, eliminates unnecessary testing on destined-to-fail compounds. It also refines lead optimization efforts, improving desired compound properties. Incorporating ADME predictions into development generates lead compounds with significantly  higher chances of success in clinical trials.

Key Capabilities

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Wide range of predicted properties

Predicts the widest variety of pharmaceutically relevant properties – octanol/water and water/gas log Ps, log S, log BB, overall CNS activity, Caco-2 and MDCK cell permeabilities, log Khsa for human serum albumin binding, and log IC50 for HERG K+-channel blockage – so that decisions about a molecule’s suitability can be made based on a thorough analysis.

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Accurate ADME properties

Provides equally accurate results in predicting properties for molecules with novel scaffolds as for analogs of well-known drugs.

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Exploring better hits

Rapidly screens compound libraries for hits and filters out candidates with unsuitable ADME properties, identifying and prioritizing the most promising ones. 

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Improving accuracy

Computes over twenty physical descriptors, which can be used to improve predictions by fitting to additional or proprietary experimental data, and to generate alternate QSAR models.

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