PVA

Update and results – the Patient Voice Analysis study

About a year ago, the PatientsLikeMe Parkinson’s disease (PD) community started something totally different: a study to compare the sound of their voices to their self-reported PD Rating Scale (PDRS) on PatientsLikeMe. It’s called the Patient Voice Analysis (PVA), and we teamed up with you, Max Little, Ph.D. and Sage Bionetworks to get it done. A little bit of background Dr. Little had done some earlier work and compared the voice signals of people who were living with PD to those of people who were not, but we wanted to take that to the next level. With their PDRS, they shared how Parkinson’s was affecting them, and we were able to match their self-reported scores to the sound of their voice. By matching a PDRS to voice samples, we might develop the ability to predict PDRS scores (which takes a few minutes to complete) by using the voice test (which only takes a few seconds). We might also be able to detect more subtle changes in people’s Parkinson’s through their voice than we can through the PDRS. This is what Dr. Little is working toward, and all the voice samples you donated will help make it happen. Community results, starting …

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Open funding for open science to accelerate ALS research: An interview with Prize4Life CEO Shay Rishoni

Just about a year ago, we teamed up with Sage Bionetworks and TED Fellow Dr. Max Little for an ongoing Parkinson’s disease (PD) project called the Patient Voice Analysis (PVA).   The big idea: combine data from two sources – phone-based voice recordings and patient reported data from PatientsLikeMe’s Parkinson’s Disease Rating Scale (PDRS). Then, make the de-identified data sets available to the broader research community on Sage Bionetworks’ cloud-based computational research platform (http://www.synapse.org) to develop new tools to track PD disease progression. We were overwhelmed by the response from the PatientsLikeMe PD community. More than 650 members provided 851 voice samples, and 779 of those were matched to the PDRS symptom data entered.   What’s next for open science? Sage Bionetworks is working with the distributed DREAM community and ALS non-profit Prize4Life on another open science challenge alongside called the ALS Stratification DREAM Challenge. How does it all fit together? The “Fund the Prize” campaign is the first of its kind effort to make the path for accelerating drug development completely open – the patient data is open access, the research is open, global and collaborative, and the funding is crowd-based. The ALS Stratification Challenge, opening in Spring 2015, will …

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PatientsLikeMe and Sage Bionetworks launch open science study for people with Parkinson’s Disease

Companies Partner With TED Fellow Dr. Max Little to Map the Severity of the Disease CAMBRIDGE, Mass.— February 5, 2014—PatientsLikeMe and the nonprofit research organization Sage Bionetworks announced today the launch of a new crowdsourced study to develop voice analysis tools that both researchers and people with Parkinson’s disease (PD) can use to track PD disease progression. In collaboration with TED Fellow Dr. Max Little, the Patient Voice Analysis (PVA) project will for the first time combine­­­ data from two sources: phone-based voice recordings that Dr. Little’s software collects and analyzes to detect markers of PD; and information reported by patients using PatientsLikeMe’s Parkinson’s Disease Rating Scale (PDRS), a tool that documents patients’ answers to questions that measure treatment effectiveness and disease progression. Both sets of data will be analyzed by the PVA team composed of Dr. Little and scientists from PatientsLikeMe and Sage Bionetworks. In later phases of the project, the de-identified data sets will be available to the broader research community on Sage Bionetworks’ cloud-based computational research platform (www.synapse.org). By crowdsourcing the analysis, the PVA team hopes to identify relationships between voice markers (like tremors in speech) and clinical signs of Parkinson’s disease (such as tremors in the …

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