Best-in-class AI 

Based on our more than 50 years of combined research experience in AI and drug discovery, we are able to propose and integrate the best-in-class AI algorithms into Drug Engine for 

Target Identification

AI Target Selection

Target Deconvolution

Biomarker prediction

 

Hit Discovery

Ultra-scale Virtual Screening

MoA Elucidation

De Novo Drug Design

 

Hit2Lead Optimization

ADMET Prediction

QSAR Modelling

AI Lead Optimisation

 

01.

Target Identification

You can use Drug Engine's AI algorithms to identify promising drug targets and biomarkers from a knowledge graph that consists of 20 million papers, genes, proteins, drugs, diseases and functional regions and tissues and their 220 million relationships. Drug Engine also provides an intuitive Omics data analysis workflow to deconvolute and discover targets and biomarkers.

02.

Hit Discovery

With our AI algorithms, you can conduct ultra-scale virtual screening and target fishing with a single click, enabling you to discover promising drug hits and elucidate their Mechanism of Actions (MoAs). Drug Engine also provides most advanced de novo drug design algorithms to help you design potent drug hits.

03.

Hit2Lead Optimisation

Partnering with Kode Chemoinformatics, Drug Engine provides accurate ADMET prediction and QSAR modelling tools to help you optimise drug hits. Drug Engine also includes explainable AI algorithms that not only optimise hits but also provide chemical structure insights as a rationale behind the optimisation.