Orbit Health

Almost all Parkinson's Disease patients experience treatment-induced side-effects that are devastating to their daily living. To ensure patients attain the best symptom control, doctors need to personalize treatments frequently. However, currently, doctors can only rely on a snapshot of information to treat their patients making treatment personalization a huge challenge. Harnessing the power of sensors and AI, Orbit offers a device-agnostic AI solution that, for the first time, allows doctors to see how patients respond to each medication, enabling them to effectively tailor treatment regimes

Orbit conducted 7 clinical trials acquiring over 20,000 minutes of high-res clinically labeled free-living data from over 300 patients to offer a clinically relevant AI solution providing insights that correlate with clinical motor states. Our studies had been published in more than 20 international publications. In one of our clinical studies, the doctor was able to restore the patient’s normal function more than 85% of the time with our solution compared to only 60% without. We have done UX/UI research with patients on our solution and 98% of patients felt comfortable using our solution during their daily activities and found handling easy; 93% of patients would like to use our solution every day, and 95% of patients would recommend our solution to other patients.

L-dopa remains the most common drug for keeping PD symptoms at bay. However, motor symptoms fluctuations are almost an inevitable consequence of chronic L-dopa treatment. Patients with these side-effects can fluctuate between a state of uncontrolled movements to a state of stiffness and even freezing of gaits. The fluctuations can occur many times during the day, causing a profound impact on the quality of life of both the patients and their caregivers. Because of this, many family members quit their jobs and stay home to take care of their patients. Motor fluctuations also cause an increasing number of complications including falls, which lead to hospitalizations. As the patient is hugely dependent, care costs increase tremendously with motor fluctuations. To ensure patients attain optimal symptom control, doctors need to personalize treatments frequently. However, currently, there is no continuous and objective way to measure motor symptoms so doctors can’t see how patients are responding to their medications. Treatment is being prescribed based on a snapshot of information -- a one-off, subjective approach -- making treatment personalization a real challenge.

Harnessing the power of sensors and AI, Orbit offers a device-agnostic AI solution (Neptune) that processes passively captured, raw motion data from a single wrist-worn sensor (like Fitbit or Apple Watch) into insightful symptom reports. This enables doctors to see each patient's symptoms in response to each medication, thereby enabling them to effectively tailor treatments to achieve maximum symptom control. With a patient/caregiver-facing app and a physician interface, Orbit provides patients and caregivers with medication reminders as well as a reliable way to track non-motor symptoms. The physician interface provides doctors with unprecedented data points to implement early intervention and the dashboard pulls all the relevant patient information and symptom insights into one view. On the back end, its smart design enables the collaboration of multiple digital medical tools and home-monitoring solutions as well as the collaboration of multidisciplinary healthcare professionals and caregivers to form a holistic care team around a single patient, a feature that is in high-demand for chronic disease management.

The current standard is manual entry of symptom diary by patients on a 30 min basis. This is impractical and unreliable.
PKG and KinesiaU are direct competitors but they don't use our deep learning approach and clinical labelling protocol. Hence, they offer limited clinical relevance for treatment personalization.

Orbit is superior in both clinical relevance and useability; and we are device-agnostic. To date, Orbit conducted 7 clinical trials acquiring over 20,000 minutes of high-res clinically labeled free-living data from over 300 patients to offer a clinically relevant AI solution providing insights that correlate with clinical motor states. The large dataset is acquired via a supervised data collection approach to generate high-quality labels in one-minute intervals. The solution generalizes well and can detect motor states in a free-living setting irrespective of patient activities. Our studies had been published in more than 20 international publications. Most machine learning-based solutions for Parkinson's Disease do not provide results to enable personalized treatment. Orbit’s solution uses deep learning to classify highly granular motion data labeled with clinical expert information. It is capable of detecting motor states irrespective of patients’ activities in a free-living, non-controlled setting, offering a significantly more effective way to evaluate treatment response compared to the current subjective symptom evaluation methods. In one of our clinical studies, the doctor was able to restore the patient’s normal function more than 85% of the time with our solution compared to only 60% without. With only a single wrist-worn sensor, Orbit offers a non-intrusive and convenient way for motion data to be captured passively. We have done UX/UI research with patients on our solution and 98% of patients felt comfortable using our solution during their daily activities and found handling easy; 93% of patients would like to use our solution every day, and 95% of patients would recommend our solution to other patients. We have a highly experienced and multidisciplinary team that has significant industry knowledge, clinical experience, and data science expertise. The team does not only have entrepreneurial experience and understands technologies, but also is equipped with the market knowledge and healthcare expertise necessary for success.

Staffing
Multicenter clinical trial
Regulatory filing and approvals
IP
Marketing
Ops