A personal immune digital twin to predict immune trajectories & improve health forecasting
The Problem & Symptoms
Consumers:
Rely on “googling” the internet to learn about their health
Clinicians:
"eyeball” patient data, no AI integration of eHealth Records
Pharma:
focus on blockbuster drugs that only work on 30% of population
Human Immune Digital Twin
The Consumer
Instead of one-by-one “googling” a test result, our software will holistically integrate results, predict changes (~e.g., 6 weeks out), and interpret data.
The Clinicians
Instead of one-by-one “eye-balling” patient results, our software will integrate, analyze, and support scenario forecasting.
Pharma
Instead of designing drugs for the masses, our software will enable patient data to personalize the clinical trial.
Drug Development
Early Stage Drug Discovery
Unlocking High Confidence in Target Identification & Drug Development
Drug Repurposing
Find new applications for existing compounds.
Our Team
Tomas Helikar, PhD
Founder & CEO
10+ years of experience in multi-scale computational modeling, biomedical research, and enterprise software development; Ph.D. in computational biology