Simulations Plus

This module automates the drug design process by integrating generative chemistry algorithms with HTPK PBPK and ADMET predictions, and can be used for hit discovery, hit-to-lead and lead optimization.

This module predicts whether your molecule is likely to be a substrate or inhibitor for major CYP and UGT enzymes, along with identifying metabolic ‘hot spots’ and generating metabolite trees.

This module contains 24 substrate, inhibitor and Michaelis constant (Km) models to help predict transporter-related drug-drug interactions.

This module offers an array of toxicity models that support you in predicting maximum recommended dose, estrogen and androgen binding, skin sensitivity, respiratory sensitivity, biodegradation, hERG binding, chromosomal aberrations, phospholipidosis, reproductive toxicity, and liver enzyme elevations, and more.

This module offers predictions around pKa, solubility vs. pH, permeability, logD vs. pH, plasma protein binding, microsomal and hepatocyte clearance, and more.

This module automates the task of developing high-quality predictive QSAR/QSPR models from experimental data sets.

This module integrates GastroPlus® PBPK models and ADME property predictions to predict key in vivo endpoints, like Fa%, F%, Cmax, AUC, and T1/2, in mice, rats and humans, while also providing a convenient and rapid dose optimization function.

This module, included at no charge with any purchased ADMET Predictor license, offers tools for data visualization, compound clustering, high-throughput screening analysis, lead identification and prioritization, de novo design, scaffold hopping, lead optimization, and more.