Cancer Treatment Accelerated
Navya enables oncologists and care teams with solutions for rapid evidence-based decision-making and asynchronous tumor boards. The Navya Cancer Data Model creates a case summary derived from patient data, published medical evidence, clinical trial data, and treatment plans from leading cancer experts. Oncologists can reduce by up to 90% the time it takes to arrive at a cancer treatment decision.
Reducing time-to-treatment saves lives!
What We Do
The Navya Cancer Data Model (NCDM) reduces the time, effort, and cost for oncologists and care team members to decide on the optimal cancer treatment plan for each patient.
Leveraging machine learning and artificial intelligence, the NCDM synthesizes structured and unstructured data from a patient's medical record into a concise two-page case summary with links to key reports.
Our proprietary evidence-based engine maps each case summary to the latest outcomes research and relevant clinical trial data. And our experience-based engine facilitates access to treatment plans from leading cancer experts.
Navya's ExpertApp provides real-time access to asynchronous, virtual collaboration between an interdisciplinary group of cancer experts. This ensures consensus-driven treatment guidance for each patient.
Hospitals and physicians can use the Navya ExpertApp to manage their primary patient population, as well as patient referrals sent to them for a 2nd opinion.
Who We Are
The Navya team comprises machine learning technologists, expert oncologists, and clinical analysts determined to use their skills to improve patient outcomes through innovation. Navya is partnered with the world’s best hospitals, academic research institutions, and industry leaders.
What We’ve Accomplished
We have empowered 74,000 patients worldwide by saving experts time and providing patients timely expert opinions. Navya's machine learning system is the first of its kind. We have been granted three patents, and have been selected to present at many world renowned cancer conferences.