The University of Edinburgh
A multidisciplinary team securely collects and scales clinical data with Boomi, developing speech biomarkers, aiding early detection and monitoring of neurological disorders.
Business goals
In a collaborative effort, The Anne Rowling Regenerative Neurology Clinic at The University of Edinburgh and SpeakUnique, a speech technology start-up, are working to accelerate the diagnosis of neurological conditions such as motor neuron disease, multiple sclerosis, Parkinson’s, and Alzheimer’s.
This research team, comprising clinicians and speech scientists working with people with these conditions, aims to capture rich, longitudinal patient data to uncover insights and develop innovative, scalable clinical tools.
Integration Challenges
Current diagnostic and monitoring tools for neurological disorders are time-consuming, expensive, and invasive. These methods largely depend on in-person procedures and offer limited digital measurement capabilities.
To efficiently gain a complete understanding, analyzing both structured data ( clinical characteristics and test scores) and unstructured data (voice and language) is essential.
This approach presents challenges, including data integration and guaranteeing user-friendly experiences for cognitively impaired individuals in clinical and home environments. It necessitated a specialist partner to develop a scalable platform.
How Boomi Helped
Through its low-code integration and automation platform, Boomi provided the University of Edinburgh with a secure sandbox to rapidly prototype and deploy a voice data collection application. The Boomi Enterprise Platform, hosted inside the university firewall, delivers high availability and low latency, and meets NHS and academic regulatory standards.
Boomi’s Professional Services team integrated the Speak Easy voice data application with existing systems and data sources, while Boomi Flow enables swift creation and management of workflows.
Results
By partnering with Boomi, the Anne Rowling Clinic curated a clinically annotated voice dataset of over 800 participants across four neurological conditions and healthy controls, with plans to scale to larger, remote cohorts. Combined with SpeakUnique’s speech analytics, this data underpins predictive voice biomarkers for early diagnosis and monitoring.
The Boomi Enterprise Platform grants clinical and analytics teams secure, permissioned access within the university firewall for machine learning, analytics, and patient care, enabling transparent workflows as the University of Edinburgh expands research into real-world settings.
