Intertwined Biosciences provides an AI‑native platform that simulates immune cell signaling to identify compounds and genetic targets capable of reprogramming dysfunctional immune cells. By integrating genomic data from disease‑resistant mammals and real‑time experimental feedback, the system prioritizes therapeutic candidates for chronic inflammatory and regenerative applications.
Funding
Funding not disclosed
Founders
Product
Problem
In chronic diseases, immune cells become locked in harmful activation states, causing ongoing tissue damage. Existing therapies do not restore the normal healing functions of these cells, especially in advanced disease stages.
Solution
Intertwined Biosciences leverages an AI‑native platform called the Virtual Immune Cell to model immune cell behavior and predict interventions that can reprogram dysfunctional cells. By mining genomic and functional data from disease‑resistant mammals, the system identifies evolution‑validated compounds and genetic targets that may restore immune homeostasis. The platform iteratively designs in‑silico experiments, conducts literature mining, and updates its models with experimental results, accelerating the discovery of therapeutic candidates aimed at repairing immune function.
Target Audience
Primary customers are biotech and pharmaceutical R&D teams focused on immunology, chronic inflammatory diseases, and regenerative medicine, as well as academic labs seeking computational tools for immune cell reprogramming.
Features
- AI‑driven simulation of immune cell signaling pathways and phenotypic outcomes under diverse perturbations
- Automated literature extraction and knowledge graph construction to incorporate evolutionary insights from resistant species
- Closed‑loop workflow that generates experimental designs, integrates wet‑lab data, and refines predictive models in real time
- Prioritization of small‑molecule, biologic, and gene‑editing interventions based on predicted efficacy and safety
- Scalable cloud infrastructure enabling high‑throughput virtual screening of thousands of candidate interventions