Born from a pair of McGill graduates and a trio of their professors, Gray Oncology Solutions is a Montréal-based startup focused on redefining how healthcare systems handle the immense logistical challenges faced on a day-to-day basis. Stemming from their collective expertise in radiation oncology & healthcare logistics, they have a vision of a workflow where each patient’s journey through their cancer treatment is personalized for them, and statistically optimized to provide the best possible clinical outcomes.
Their first step in pursuit of this vision is the development of a platform best described as a “cancer center’s operating system” (grayOS).
The core technology behind this is the creation of the cancer center’s “digital twin”. With this twin, historical data is used to model the future which then informs the present. As the physical state of operations evolves, so too does the twin.
Operationally, this translates to the automated optimization of patient scheduling while explicitly incorporating the complex multi-disciplinary workflow (and existing bottlenecks). The real-time connection enables previously unseen patient engagement allowing their scheduling preferences to be considered, and a Waze for healthcare: an accurate representation of the “traffic” in the center’s waiting rooms.
Once the logistical puzzle has been solved, Gray has no intention of stopping there. grayOS aims to disrupt not only how appointments are scheduled, but also provide a clinical support tool in choosing the optimal treatment. For example, if Treatment A is statistically inferior to Treatment B but could be delivered 7 days sooner, which is ultimately the superior choice? What about a 4 day difference? 2 days? Does this decision change when comparing a 50-year old prostate cancer patient to a 95-year old lung cancer patient? Through the combination of multi-disciplinary clinical data and state-of the-art optimization algorithms, Gray is building a platform to help answer these questions.
