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.