There is a critical need for personalized, multi-dimensional diagnostics and treatment guidance that accounts for individual biology, health, and environmental factors, enabling earlier disease detection and more effective, adaptive therapeutic decisions. Nine Diagnostics is accelerating the path to the most effective treatment for the individual patient by actualizing on functional precision medicine. The founding team of clinician, scientists, engineers, innovators, and entrepreneurs came together to tackle some of healthcare's largest problems in developing a breakthrough technology that could help detect diseases earlier, provide rapid feedback on treatment selection and effectiveness, and monitor disease recurrence or treatment resistance.
What is the problem?
Effectively treating complex diseases requires a personalized approach that considers each patient's unique biology, health status, and social and environmental factors. Traditional diagnostics often lack the ability to provide this depth of insight, delaying the detection of disease and impacting treatment effectiveness. The broad impact of complex diseases extends beyond individual patients, straining healthcare systems and limiting outcomes across populations due to incomplete or delayed diagnostics. By addressing these challenges, there is potential to transform disease management, offering more timely, targeted, and effective treatments that improve quality of life and reduce healthcare costs on a larger scale.
What is their solution?
Our pioneering platform technology consists of arrays of carbon nanotube sensors which can uniquely identify a disease-specific spectral profile in response to molecular binding interactions to proteins and metabolites in patient blood serum. The technology has been initially validated for detection of high-grade serous ovarian carcinoma, prediction of IVF pregnancy loss, and differentiation between types of intracranial tumors. Using information including disease diagnosis, disease stage, patient demographics, co-existing diseases, current medications, and social determinants of health, we train machine learning classification models to predict disease states. We envision that our technology can serve as a diagnostics platform for functional precision medicine to measure treatment effectiveness faster, optimizing treatment dosing and frequency faster, identifying novel disease-specific biomarkers, and identifying disease recurrence or treatment resistance.
