The Alzheimer’s Drug Discovery Foundation’s (ADDF) diagnostic accelerator (DxA) has started a longitudinal study, SpeechDx, to create a speech and voice database for accelerating the detection, diagnosis and monitoring of Alzheimer’s disease (AD).
The DxA programme was created in 2018 as a $100m global research initiative to develop affordable and accessible biomarkers for AD diagnosis and treatment.
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Therapies for AD are a growing area of interest and are forecasted to generate $13.7bn in sales in 2030 across eight major markets, according to GlobalData. Additionally, multiple drugs are currently in development for the treatment of the disease.
GlobalData is the parent company of Pharmaceutical Technology.
The SpeechDx study will collect clinical and biomarker data along with the corresponding voice samples. The database is being created with the aim of providing academic, biotech, and industry partners with data to develop algorithms that can identify new speech biomarkers for AD.
“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 ADDF co-founder Dr Howard Fillit in a press release.
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By GlobalData“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.”
The SpeechDx study will collect data from 2,650 participants over three years across five clinical sites in the US, Spain and Australia. The participant pool for the trial would include a spectrum of people ranging from those with good cognitive health to those with early Alzheimer’s.
The voice data will be collected in English, Spanish and Catalan using a pre-installed SpeechDx app through a handheld tablet. The collected data will be accessible to biotech, pharma and research communities to develop speech biomarkers.
