Opportunity Overview
CONTEXT:
The burden and disability associated with chronic respiratory diseases (CRDs) is considerable, often falling on the most vulnerable in societies including those living in low- and middle-income countries such as Brazil. Specifically, the prevalence of chronic obstructive pulmonary disease (COPD) is increasing, and COPD presents a particular health challenge in Brazil where the prevalence in adults exceeds 17%. Most people with COPD in Brazil remain undiagnosed, and therefore untreated, because of limited access to the current diagnostic test called 'spirometry'. Spirometry is not widely, or equitably available in many primary healthcare settings in Brazil - including in Sao Paulo state. Innovative approaches to the diagnosis and management of COPD are therefore urgently required.
THE CHALLENGE WE ADDRESS:
We seek to transform the diagnosis of CRDs in primary care in Sao Paulo state, Brazil. We will do this through the use of vocal biomarkers derived by artificial-intelligence analysis of speech patterns. This technique has shown promise in English and Dutch languages, as a diagnostic and prognostic marker in CRDs, but has not been applied in (Brazilian) Portuguese, nor been deployed in real-life primary care settings where the need for easier tools to diagnose CRDs is greatest.
AIMS and OBJECTIVES:
Our over-arching aim is to develop and test AI-derived vocal biomarkers to support better diagnosis and management of CRDs in Brazil. To do this, we will work as an equitable partnership between the Federal University of Sao Carlos (Brazil) and University College London (UCL), with voice analysis experts at the University of Maastrict (Netherlands). We will:
AIM 1: establish a dataset of voices from individuals with and without CRDs in Brazil.
AIM 2: test the discriminative accuracy of AI-derived vocal biomarkers to distinguish those with CRDs from those with normal lung function.
AIM 3: evaluate the utility of vocal biomarkers in COPD to detect the...
The burden and disability associated with chronic respiratory diseases (CRDs) is considerable, often falling on the most vulnerable in societies including those living in low- and middle-income countries such as Brazil. Specifically, the prevalence of chronic obstructive pulmonary disease (COPD) is increasing, and COPD presents a particular health challenge in Brazil where the prevalence in adults exceeds 17%. Most people with COPD in Brazil remain undiagnosed, and therefore untreated, because of limited access to the current diagnostic test called 'spirometry'. Spirometry is not widely, or equitably available in many primary healthcare settings in Brazil - including in Sao Paulo state. Innovative approaches to the diagnosis and management of COPD are therefore urgently required.
THE CHALLENGE WE ADDRESS:
We seek to transform the diagnosis of CRDs in primary care in Sao Paulo state, Brazil. We will do this through the use of vocal biomarkers derived by artificial-intelligence analysis of speech patterns. This technique has shown promise in English and Dutch languages, as a diagnostic and prognostic marker in CRDs, but has not been applied in (Brazilian) Portuguese, nor been deployed in real-life primary care settings where the need for easier tools to diagnose CRDs is greatest.
AIMS and OBJECTIVES:
Our over-arching aim is to develop and test AI-derived vocal biomarkers to support better diagnosis and management of CRDs in Brazil. To do this, we will work as an equitable partnership between the Federal University of Sao Carlos (Brazil) and University College London (UCL), with voice analysis experts at the University of Maastrict (Netherlands). We will:
AIM 1: establish a dataset of voices from individuals with and without CRDs in Brazil.
AIM 2: test the discriminative accuracy of AI-derived vocal biomarkers to distinguish those with CRDs from those with normal lung function.
AIM 3: evaluate the utility of vocal biomarkers in COPD to detect the...
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Start FreeSolicitation Details
| Issuing agency | ISPF |
|---|---|
| Country | United Kingdom |
| Category | Data & Analytics |
| Published | February 07, 2025 |
| Procurement stage | Active solicitation |
| Closed | Closing date not published |
| Status | Closed — no longer accepting responses |
| Official source | View original notice |
| Last verified | October 10, 2026 |
Source: UK Research and Innovation (UKRI) — Open Government Licence v3.0.
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