Cancer patients with apparently similar diagnoses can respond very differently to the same treatment. Precision oncology therefore requires the ability to integrate multiple layers of patient-specific information and translate those data into clinically meaningful treatment decisions.
Oncovask Therapeutics is developing a digital-twin platform for cancer that aims to create computational representations of individual patients and their tumors. The platform is envisioned to integrate clinical information, tumor characteristics, molecular data, treatment history, and relevant biomedical evidence.
Artificial intelligence and predictive modeling can then be used to evaluate how a patient’s disease may respond to different therapeutic strategies, particularly among available FDA-approved treatment options.
We are also exploring virtual-reality technologies as an intuitive interface for visualizing complex patient and tumor information. Our long-term goal is to provide healthcare professionals with a decision-support environment in which tumor biology, therapeutic options, predicted responses, and disease evolution can be evaluated within a patient-specific digital model.
The platform is intended to support—not replace—clinical judgment, helping clinicians interpret increasingly complex oncology data and make more informed personalized-treatment decisions.
Research Focus
- Patient-specific cancer digital twins
- Artificial intelligence and predictive modeling
- Personalized treatment selection
- Integration of clinical and molecular data
- FDA-approved therapy evaluation
- Virtual-reality visualization
- Clinical decision-support technologies