Pfizer, IBM Sign Digital Health Pact for Parkinson’s DiseaseBy
Pfizer and IBM have formed a research collaboration to develop remote monitoring solutions for use by clinicians to deliver care to patients with Parkinson's disease. The experimental approach will rely on a system of sensors, mobile devices, and machine learning to provide real-time, around-the-clock disease symptom information to clinicians and researchers. The ultimate goal is to obtain a better understanding of a patient's disease progression and medication response to help inform treatment decisions and clinical trial design while also speeding the development of new therapeutic options.
The two companies project that the system will move into initial clinical testing quickly. Pfizer and IBM will convene an external advisory board of patient groups, advocacy organizations, clinicians, and neuroscientists for guidance on the use of technology, medical devices, data management, and research protocols, and to ensure the needs of patients guide the program.
The project is part of IBM's work to advance Internet of Things (IoT) technologies in healthcare. Emory University Hospital is creating an instrumented ICU using IBM’s streaming analytics technology to advance predictive medicine for critical patients in the ICU. The new system will enable clinicians to acquire, analyze and correlate medical data at higher volumes and speed. Neonatal intensive care specialists at The University of Ontario Institute of Technology are relying on the same software to analyze more than 1,000 pieces of unique information per second flowing from sensors and equipment monitoring premature babies, helping caregivers spot the onset of sepsis infections up to 24 hours earlier. Medtronic is working with IBM Watson Health for a cognitive app designed to analyze real-time data from Medtronic devices to help detect important patterns and trends for people with diabetes.
The Pfizer/IBM project is targeting treatments for Parkinson's disease, which require ongoing adjustment to medication depending on the progression of the disease and response of the patient. The collaboration seeks to create a holistic view of a patient's well-being by seeking to accurately measure a variety of health indicators, including motor function, dyskinesia, cognition, sleep and daily activities such as grooming, dressing and eating. Insights from these data could help clinicians understand the effect of a patient's medication as the disease progresses, enabling them to help optimize the patient's treatment regimen as needed. Data generated through the system could also arm researchers with the insights and real-world evidence needed to help accelerate potential new and better therapies.