MindCell
Carbon Crystal Silicon Virtual Cell
A comprehensive multi-modal LLM system for modeling entire cells, enabling phenotype-driven digital cells, animal models, and human simulations for drug screening and validation. We enhance LLM training by using synthetic data generated by a multimodal code translator, where the outputs from specialized AI models serve as the input corpus, allowing for simulations of life at multiple layers:
Carbon Crystal Silicon Virtual Cell Features
Molecular-level modeling
Predicting molecular mechanisms of treatments, such as DNA changes, epigenetic modifications, RNA expressions, protein expressions and modifications, and metabolite changes.
Cell-level modeling
Predicting cell phenotypes and responses to treatments, including processes like cell cycle, division, differentiation, death, senescence, migration, and cell-cell interactions.
Tissue-level modeling
Predicting tissue health status and behaviors in response to treatments, covering processes like tissue regeneration, repair, damage, remodeling, aging, and diseases.
Core Technology
Our proprietary multimodal code translator generates high-fidelity synthetic data, enabling our LLM to understand and simulate biological processes with unprecedented accuracy.
Multimodal LLM
Integrating code, text, and biological data for comprehensive modeling.
Synthetic Data
Enhanced training corpus generated via specialized AI model outputs.
Multi-scale Simulation
Seamless integration of simulation data from molecules to entire organisms.
Applications
Drug Screening
Accelerate discovery with high-throughput virtual validation and toxicity prediction.
Digital Cells
Phenotype-driven modeling of cell behaviors under various conditions.
Human Simulation
Complex system modeling for personalized medicine and treatment optimization.