Accelerate Clinical Trials with Digital Twins

Nova’s Jinkō platform creates virtual patient “twins” that mirror real patients’ characteristics and treatment responses. As a leading application of digital twins in healthcare, each virtual twin simulates real-world physiology, disease progression, and therapeutic response with precision – enabling faster, smarter, and more cost-effective drug development. 

How Our Digital Twin Technology Works

Data Integration
Combines heterogeneous data sources such as clinical trial data, real-world evidence, molecular profiles, biomarkers, and patient characteristics

Digital Patient Creation
Generates either high-fidelity digital twin patients or synthetic patients, enriched with demographic, disease-specific, and biomarker attributes

Causal Model
Applies biophysical and pharmacological models grounded in the biology of disease and drug mechanisms

Trial Simulation
Runs large-scale simulations of digital patients through trial protocols in minutes

Rethinking Trial Simulations: From Traditional AI to Digital Twins

 

   Feature

  Traditional AI

  Nova’s Causal AI

  Methodology

  Machine Learning

  Transparent QSP, Digital Twins       

  Data Source

  Historical + clinical data

  Works with sparse, varied data

  Strengths

  Handles big data, simulations

  White-box, what-if testing

  Weaknesses

  Data-hungry, black box

  Needs biological insights

  Approval

  Needs proof

  More justifiable

 

Digital Patient Twins, Real-World Impact

Smarter Trial Design
Test unlimited trial scenarios to optimize protocols, identify best responders, and avoid costly late-stage failures

Accelerated, Cost-Efficient Trials
Reduce required sample sizes and trial duration by supplementing or substituting control arms with credible digital twins.

Patient-Centric Insights
Explore rare populations, improve selection, and reduce exposure to ineffective treatments — ethically and efficiently.