Alzheimer's Drug Discovery Foundation Launches SpeechDx to Generate a Voice Database for Early Detection of Alzheimer's
The Alzheimer's Drug Discovery Foundation's (ADDF) Diagnostic Accelerator (DxA) has launched SpeechDx, a longitudinal study aimed at creating the largest repository of speech and voice data to help accelerate the detection, diagnosis, and monitoring of Alzheimer's disease.
With this initiative, recorded voice samples from the study will be paired with clinical and biomarker data that can be leveraged by academic, biotech, and industry partners to develop algorithms for the creation of new speech biomarkers.
Subtle changes in speech and language patterns can indicate and predict cognitive decline associated with Alzheimer's. Recent technological advancements have enabled speech and voice to act as digital biomarkers for Alzheimer's.
"Speech is a complex cognitive process that contains important information about how your brain is functioning, and scientific evidence shows us speech may hold the key to early, accurate, and non-invasive detection of Alzheimer's disease," said Dr. Howard Fillit, co-founder and chief science officer of the ADDF, in a statement. "This study will help develop and validate voice-based biomarkers, expanding our existing arsenal of neuroimaging, peripheral blood, and digital biomarkers, all of which are crucial to delivering the right drugs to the right patients at the right time."
"To our knowledge, SpeechDx will comprise the largest-in-size and longest-in-duration curated repository of voice and clinical ground truth in dementia research," said Lampros Kourtis>, DxA SpeechDx program manager at Gates Ventures, in a statement. "Our hope is that scientists can use this dataset to train, validate and benchmark algorithms that detect and monitor cognitive decline at early stages of disease development."
This study will span three-years acrossclinical sites at Boston University, Emory University, Barcelona Brain Health Initiative, Barcelonaβeta Brain Research Center (BBRC), and the Ace Alzheimer Center Barcelona. The data will be collected from 2,650 participants with full brain health spectrum from cognitively healthy to early Alzheimer's, and in three languages, including English, Spanish, and Catalan. Study participants will be given handheld tablets with the pre-installed SpeechDx app to capture their voice data. Each participant's voice recordings will be paired with clinical data and harmonized across all sites. This integration of clinical-digital data will serve as a ground point for machine learning. The collected data will be stored via the ADDI's platform, which will function as a digital repository and contain approximately 2,584 hours of voice data for the creation of algorithms for Alzheimer's detection and monitoring.
"Machine learning algorithms are being integrated into every aspect of medical research, but the outputs are only as good as the data they are being built on," said Niranjan Bose, managing director of health and life sciences at Gates Ventures, in a statement. "Implementation and development of the SpeechDx program will streamline the collection of high-quality speech data and ultimately complement the existing array of available biomarkers, including expanding the portfolio of digital tools used to predict and prevent the onset of the disease early on."