ADMET Predictor®
What is the ADMET Predictor® Module?
The ADMET Predictor Module extends the capability of GastroPlus® by enabling you to obtain predictions from the structure of all physicochemical, pharmacokinetic, and CYP metabolism kinetic parameters required for the GastroPlus PBPK simulations. You can now apply discovery PBPK modeling approaches to assist with lead selection and optimization activities! The module uses the same models as our best-in-class ADMET Predictor standalone software.
NEW! CYP metabolism kinetic predictions from chemical structure – quickly create full PBPK models, using the PBPKPlus™ Module, in seconds! With MedChem Designer™, generate CYP metabolite trees!
NEW! Rat-specific QSAR models – intrinsic clearance, plasma protein binding, blood: plasma concentration ratio
For the latest in discovery PBPK and high throughput PK simulations (HTPK), check out these resources below:
[Webinar & Slide Presentation]
[Peer-reviewed Publication]
[Webinar & Slide Presentation]
HTPK: A bridge to Early Development (Mar 2021)
Resources
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Discovery PBPK: How to enhance the expected accuracy of bioavailability predictions for NCEs that are not primarily metabolized
Learn MoreIn this webinar, we will review the accuracy of purely in silico estimates of bioavailability and the chemistry classification of new chemical entity (NCE) molecules that are easier or harder to...
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Physiologically-Based Pharmacokinetic Modeling in Lead Optimization II: “Rational Bioavailability Design” by Global Sensitivity Analysis to Identify Properties Affecting Bioavailability.
Learn MoreWhen medicinal chemists need to improve oral bioavailability (%F) during lead optimization, they systematically modify compound properties mainly based on their own experience and general rules of thumb.
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Physiologically-Based Pharmacokinetic Modeling in Lead Optimization I: Evaluation and Adaptation of GastroPlus to Predict Bioavailability of Medchem Series
Learn MoreWhen medicinal chemists need to improve bioavailability (%F) within a chemical series during lead optimization, they synthesize new series members with systematically modified properties...
