Synlico integrates artificial intelligence, single-cell bioinformatics, and causal cell modeling to advance drug discovery. The company develops a computational platform that identifies causal links between intracellular activities and patient microenvironment responses. This approach enables targeted drug design by predicting how cell modulation alters behavior in patients.
Funding
$3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current drug discovery processes struggle to translate in-vitro and animal model results to human patients due to the disconnect between drug design and the complex heterogeneity of the tumor microenvironment. This leads to trial-and-error screening processes and unpredictable patient responses.
Solution
Synlico is developing an AI-driven computational platform that integrates single-cell bioinformatics and cell engineering to analyze T cell behaviors and their interactions within the tumor microenvironment. The platform identifies causal links between intracellular activities of cells and their responses in the patient's microenvironment, enabling targeted drug design that accounts for patient-specific heterogeneity. By focusing on shared patterns within the microenvironment, Synlico's technology predicts how cell modulation alters behavior in patients, leading to more effective and quantitatively explainable therapies. The integrated approach considers the synergistic effects of multiple factors, enabling cell design targeting multiple microenvironment patterns.
Target Audience
Synlico's primary target audience includes pharmaceutical companies and research institutions involved in drug discovery and development, particularly those focused on targeted therapies and personalized medicine.
Features
- AI-powered platform for identifying causal effects of gene interventions and cell behaviors
- Prediction-based models that consider patient microenvironment heterogeneity
- Integration of single-cell bioinformatics and cell engineering
- Analysis of T cell behaviors and interactions within the tumor microenvironment
- Identification of synergistic effects of multiple factors in drug response