Research Project 3
Current PD measures are largely limited to the clinic and based on episodic, rater-dependent, categorical scales. The result is that the clinical trials, even early stage ones, require large sample sizes, long durations, and high costs. Moreover, these measures are prone to generating false signals of efficacy in phase 2 trials that are not found in phase 3 and likely generate missed signals of efficacy that are never detected.
In the 21st century new tools are available that can generate objective, frequent, sensitive assessments of PD in real-world settings. These super computing devices, or smartphones, are increasingly ubiquitous and powerful. In March 2015, Apple released ResearchKit, an open-source platform for creating smartphone research studies. At the same time, five smartphone research studies, including one for PD (mPower), were also launched. In seven months, over 70,000 individuals across the country enrolled in these studies.
Through the P20 and related efforts, we have demonstrated that assessments of voice, gait, balance, and bradykinesia conducted on the smartphone can differentiate individuals with PD from those without, correlate with traditional PD assessments, detect response to levodopa, and can be quantified in a novel mobile PD score that correlates with the MDS-UPDRS but can be administered by almost anyone anywhere anytime.In Research Project 3, we will evaluate the next generation smartphone research application (mPower 2.0) against current gold standard clinical measures of PD, assess its ability to generate novel assessments of socialization based on passively collected data, refine the mobile PD score, and improve the replicability and reproducibility of the score using advanced signal processing algorithms and neural networksIn just two years after their large-scale introduction, pharmaceutical companies and academic investigators are already incorporating these devices into their clinical trials. This Research Project will help accelerate these efforts to use smartphones to generate objective, passive and active, frequent real-world assessments of motor and non-motor function in PD.
Research Project 4
New sensing devices can generate objective, frequent, sensitive assessments of PD. However, many devices, like smartphones, require individuals to complete activities. Because PD, unlike colon cancer, for example, has clear external features (e.g., slow gait, frequent sleep interruptions), it is well suited for passive assessment.
In Research Project 4, we will evaluate three leading technologies to assess PD principally (but not exclusively) through passive means. These technologies include wearable sensors that can measure motor and autonomic function, a video analytical tool that can measure elements of the standard PD motor examination, and an “invisible” radio wave sensing tool that can assess the natural history of PD in the home. These three tools will enhance our understanding and generate objective measures of PD that can be used to accelerate therapeutic development and improve care.
The first project will examine a wearable sensor that has embedded accelerometers, gyroscope, and ECG capabilities to assess function inside and outside the clinic. In one of the largest PD sensor studies, we will seek to confirm and extend findings that individuals with PD exhibit distinct diurnal activity patterns from controls (e.g., lie down more, walkless), evaluate autonomic function, and in partnership with the University of Michigan’s Udall Center, explore whether gait function is worse in individuals with a hypocholinergic state.The second project will evaluate a recently developed video analytics tool that applies machine learning algorithms to evaluate motor assessments (e.g., facial expression, finger tapping) that are routinely assessed through the motor portion the MDS-UPDRS to see if these assessments, conducted without an investigator, can differentiate those with PD from those without and correlate with traditional assessments.The third project will evaluate motor and non-motor function of individuals with PD in their homes using a novel radio wave sensing device. This device can assess existing measures (e.g., gait speed, respiratory rate) and novel measures (e.g., path tortuosity, time alone) that will provide novel insights into the disease.