/ Solutions / Drug Research and Development Solutions / ADMET Prediction
ADMET includes drug absorption, distribution, metabolism, excretion and toxicity. One main reason for
drug R&D failures is the efficacy and safety deficiencies which are related largely to ADMET properties.
In the early study of ADMET properties, functional proteins from human or humanized tissues have been
usually used as drug targets. Common research technologies combined with computer simulation are
applied to study the interaction between drugs and targets, revealing biophysical and biochemical
influences in vivo. Prediction of ADMET is an important process in drug design and drug screening.
However, the current experimental methods for ADMET evaluation are still costly and time-consuming. In
order to further improve the accuracy of ADMET property prediction, based on Big Data, Machine
Learning and Deep Learning technologies, MedAI is dedicated to effectively extracting structural features
(including processing small molecule and protein structure) through deep neural network algorithm. It
virtually predicts and evaluates ADMET and other properties of small molecule structures on cell, protein
and disease level. Function modules in the platform enable our clients to conveniently perform several
types of drug-likeness analysis, ADMET endpoints prediction, systematic evaluation and
Input Active Compounds Data
Output & Evaluation (*.pdf, *.csv)
All the obtained data are collected from peer-reviewed publications, public databases through manually
filtering and processing.
Data Set Preparing