Simulate how genetic and drug interventions affect cell states and functions to identify the key genes, pathways, and regulatory mechanisms driving disease phenotypes, accelerating the discovery, prioritization, and validation of candidate targets.
Build virtual cells that respond to genetic, pharmacological, and environmental interventions, simulating state changes, functional responses, and fate transitions across cell types and biological contexts to support cell research and engineering design.
Integrate multicellular, multi-omics, spatial microenvironment, and longitudinal disease data to reconstruct disease states and their progression, understand cell–cell interactions and disease heterogeneity, and predict the systemic impact of different intervention strategies.
Drug Perturbation and Virtual Clinical Trials in the Tumor Microenvironment (TME)
AI-Optimized Directed Differentiation Process for Stem Cells
Genetic Engineering and Functional Optimization of CAR-T Cells
AI-Driven Discovery of Skin Anti-Aging Targets