Broadening drug discovery research to
contribute to human health

Value Up your asset and know-hows

How can we value up?

Simultaneous integration of

Exploring Chemical Space

Compound space stratification
based on molecular structure

# Hit-to-Lead

Our company has developed advanced technology to develop novel lead compounds by considering both structural similarity and diversity. We stratify the compound space using hierarchical structural properties from in-house data. This process identifies optimized lead compounds that are similar to drugs in development and generates new compounds with structural diversity and functional similarity, accelerating the path to new therapeutics.

Exploring Genetic Space

Exploring the genetic space
based on multi-omics data

# Drug efficacy# ADME# Toxicity

Our technologies explore the genetic space
by integrating gene expression levels,
epigenetic regulation and proteins levels.
By elucidating the mechanisms of action, we can predict drug efficacy, ADME, and toxicity,
and stratify patients based on biomarkers.

Exploring Disease Space

Exploring disease space
based on biomedical knowledge

# drug repositioning# drug combination

Our technologies assist in understanding diseases by modeling the disease space using clinical data. By exploring how existing drugs can be used for other diseases, we can engage in drug repositioning or develop drug combinations through synergy analysis with other drugs.

DrugVLAB™

Multi-omics and compound data-based AI drug discovery platform

DrugVLABTM is a multi-omics-based AI drug discovery platform, validated by extensive research papers. It precisely explores the chemical space, genetic space, and disease space to accurately select target proteins and candidate compounds.

DrugVLABTM enables explainable and accurate identification of drug candidates, toxicity prediction, and biomarker prediction based on multi-omics and compound data. DrugVLABTM optimize the drug development process using standalone tools validated by extensive research papers, and pre-built packages created by gathering various needs.