ChemMining™ efficiently explores the chemical space, identifying high-efficacy compounds and providing priority rankings utilizing Deep Learning, Network Exploration, and Cheminformatics. Our innovative approach allows for the discovery of compounds with unique scaffolds, enhancing patentability and diversity.

• Used Cases Discovery of hit compounds for small molecule kinase inhibitors. Identification of hit compounds for pharmacological chaperones.

ChemGen™ innovates compound design using protein 3D structures and experimental data. Our Generative AI models create molecules binding to protein pockets. With Network Propagation technology, we efficiently select high-efficacy, drug-like compounds with prioritized precisions.

• Used Cases Optimization of pharmacological chaperone lead compounds. Development of optimal compound formulations.

ChemResponse™ predicts drug responses by analyzing the mechanism of action from various perspectives. Our innovative approach identifies crucial gene interactions and pathways. Also, we simulate the effects of compound perturbations starting from target genes, pinpointing driver genes crucial to the biological mechanisms of the compound.

• Used Cases Interpreting mode of action of compounds. Stratification of samples based on drug responsiveness.

ChemTox™ analyzes in vivo toxicity and side effects based on transcriptome data and compounds structures. We identify crucial toxicophores, predict toxicity via CYP and hERG analysis, and offer insights into six hepatotoxicity mechanisms. Also, we forecast compound side effect frequencies based on molecular structure, similarity, and target protein data.

• Used Cases Prediction of kinase off-target effects.

ChemTune™ utilizes biomedical knowledge networks for knowledge drug repurposing and synergy analysis. Our biomedical knowledge graph connects drug-disease spaces with Protein-Protein Interaction (PPI) networks. Skip-Gram encoder models analyze relationships, and ‘Teleportation’ in random walks ensures unbiased exploration.

• Used Cases Prediction of small molecule inhibitor combinations.

ChemProtac™ elevates the potential of candidate inhibitors by expertly designing tailored PROTAC solutions. By integrating existing assay data with advanced protein structure prediction and docking simulation models, our model refines the search for optimal linkers in the development and evaluation of de novo PROTAC leads.

• Used Cases Explore innovative PROTAC linker designs. Predicting protein inhibition efficacy for existing PROTACs.