Modeling Personalized Disease Dynamics Using Liquid Biopsies for Tailored Treatment Strategies

NU 2025-187

INVENTORS

• Madhav Mani (PI - Northwestern University)
• Sidhartha Goyal* (PI - University of Toronto)
• Spencer Farrell (University of Toronto)

SHORT DESCRIPTION

This technology models disease progression using liquid biopsy data. It predicts individual tumor dynamics to support tailored treatment strategies.

BACKGROUND

Current approaches to monitoring cancer rely on invasive tissue sampling and suffer from limited temporal resolution. Tumor evolution is complex and dynamic, driven by clonal expansion and intra-tumor heterogeneity. These factors create challenges in effectively tracking disease progression and adjusting treatment strategies over time.

ABSTRACT

We developed a computational framework that leverages liquid biopsy-derived biomolecules to model personalized disease dynamics. The technology integrates domain-specific insights within a Bayesian framework to overcome sparse longitudinal data challenges. Laboratory studies have validated individual components, and key performance metrics demonstrate its potential to predict tumor evolution with uncertainty estimates that inform clinical decisions.

DEVELOPMENT STAGE

TRL-4 - Prototype Validated in Lab: Key functions have been demonstrated in controlled laboratory settings using both academic and residential datasets.

APPLICATIONS

• Personalized Oncology Treatment Planning: Uses longitudinal liquid biopsy data to tailor therapies.
• Real-time Tumor Evolution Monitoring: Tracks subclonal dynamics during treatment.
• Predicting Onset of Metastasis: Identifies early signs of tumor spread.
• Extending to Complex Diseases: Applies the approach to microbiome-driven and neurodegenerative disorders.

ADVANTAGES

• Improves Prediction Accuracy: Incorporates domain insights and uncertainty quantification.
• Enhances Treatment Planning: Supports personalized therapy decisions using dynamic data.
• Reduces Invasiveness: Utilizes non-invasive liquid biopsy techniques.
• Maximizes Data Utility: Leverages sparse longitudinal data to capture individual disease trajectories.

IP STATUS

Patent Pending