Artificial Intelligence
Large language models, biological representation learning, and autonomous multi-agent reasoning for medical AI
AI for life sciences. Building the next generation of precision medicine.
Making precision medicine accessible to all. Powered by Biological AI
About GenetrixBio
GenetrixBio is a medical technology company focused on innovation at the intersection of artificial intelligence and life sciences. Powered by biology foundation models and medical AI agents, we combine multi-omics data, medical knowledge, and clinical evidence to build a new generation of intelligent healthcare platforms for complex disease treatment and personalized health management.
Biomedicine
Molecular oncology, disease mechanism dynamics, and interactions between natural bioactive compounds and receptors
Multi-omics Technology
Authoritative clinical guidelines (NCCN/CSCO), real-world medical records, evidence chains, and treatment response evaluation
Trusted by leading global partners
A medical AI platform powered by biology foundation models
Living systems are highly complex. Disease development spans genes, RNA, proteins, cells, tissues, and clinical phenotypes. GenetrixBio is building a new life-science AI platform with biology foundation models as its core capability and medical AI agents as its application engine. By integrating multi-omics data, medical knowledge, clinical evidence, and disease mechanisms, the models learn complex relationships in living systems while AI agents translate predictions into actionable medical solutions. The result is a closed technology loop: understanding biological data → resolving disease mechanisms → supporting intelligent decisions → generating personalized interventions.
Explore the platformBiology Foundation Models
Genomic, transcriptomic, proteomic, metabolomic, pathology imaging, and clinical text data are combined to learn cross-scale biological features and understand disease mechanisms and human states.
AI Agent System
Complex medical questions are decomposed into retrieval, data analysis, mechanism reasoning, and solution evaluation tasks that specialized agents complete together.
Intelligent Medical Solutions
For complex diseases such as cancer, multidimensional patient data, mechanism analysis, decision support, drug matching, and response prediction improve clinical efficiency and precision.
Doctor perspectives across product scenarios
Based on GenetrixBio's product capabilities and representative medical workflows, these perspectives present applications across oncology decision support, health-risk analysis, and drug research.
“Complex cases are easier to organize”
Before a multidisciplinary review, the system can help consolidate medical records, pathology, molecular testing, and treatment history, then organize treatment paths for discussion by evidence source. This reduces repetitive searching and keeps team conversations focused.
Director of Oncology
Medical oncology · OncoCopilot™ / GenoMind AI™ scenario
“Health-risk conversations become more structured”
When examination results, lifestyle factors, and long-term health goals are fragmented, AI health assessment helps me organize risk dimensions and follow-up priorities so nutrition, exercise, and lifestyle guidance is easier to explain.
Director of Health Examination Center
Health management · AI health and risk analysis scenario
“Research hypotheses form faster and remain traceable”
When exploring drug repurposing and cross-indication mechanisms, the system can connect disease pathways, drug mechanisms, and published evidence. This helps the team form hypotheses for validation sooner while preserving a clear evidence trail.
Pharmaceutical Company Executive
Clinical research · Drug repurposing and mechanism research scenario
“Complex cases are easier to organize”
Before a multidisciplinary review, the system can help consolidate medical records, pathology, molecular testing, and treatment history, then organize treatment paths for discussion by evidence source. This reduces repetitive searching and keeps team conversations focused.
Director of Oncology
Medical oncology · OncoCopilot™ / GenoMind AI™ scenario
Core Product Capabilities
Integrate health data into a continuously trackable risk profile
Physical examinations, physiological indicators, health history, lifestyle, genetics, and multi-omics data are combined to identify chronic-disease, metabolic, inflammatory, and aging-related risks. Dynamic tracking and stratified analysis provide an explainable basis for personalized health management.
Connect clinical information, molecular evidence, and treatment pathways
Medical records, pathology, genomics, clinical guidelines, real-world evidence, and trial data support structured case analysis, treatment comparison, drug matching, response prediction, evidence traceability, and multidisciplinary collaboration.
Move from multi-omics aging assessment to stratified intervention
Epigenetic, metabolic, inflammatory, and lifestyle data form a dynamic aging-risk profile. Management is stratified across proactive defense, precision repair, and clinical reinforcement, with ongoing evaluation of intervention outcomes.
Discover new therapeutic opportunities through mechanism reasoning and evidence chains
Cross-scale links among disease pathways, target networks, drug mechanisms, and published evidence support the discovery of new mechanisms and cross-indication candidates, together with dose optimization and end-to-end evidence traceability.
Coordinate multi-target regulation across genes, microenvironment, and metabolism
AI interprets classical formulas, natural bioactive compounds, and supplement mechanisms alongside individual genomic profiles and health status to support combined strategies for the tumor microenvironment and long-term recovery management.
Our Core Team
A globally experienced life-science and AI research team translating leading science into medical AI innovation.
Our team has trained and worked at leading research institutions and published in Nature, Science, Cell, Nature Medicine, Cancer Discovery, and other top international journals.
Multi-omics foundation models for resolving tumor microenvironment heterogeneity and treatment tolerance
Cross-scale understanding of tumor environments and treatment response.
View research
AI-guided repurposing of metabolic inhibitors to overcome immunotherapy resistance in cold tumors
Artificial intelligence for drug repurposing and mechanism validation.
View researchAutonomous deep reasoning maps bioactive phytochemicals across scales to human metabolic checkpoints
Connecting natural compounds with human metabolic mechanisms.
View research