Harnessing Local Biomedical Data to Power AI for Precision Medicine
Mozambique is home to rich and underutilized biomedical data — including clinical records, epidemiological reports, and genomic samples. MozBioMed.AI is working closely with MozBioBank, the country’s national biobank initiative, to unlock the potential of these datasets using advanced artificial intelligence tools.
The Project
This initiative focuses on applying machine learning to multi-modal health data collected in Mozambique. We analyze:
- Genomic sequences
- Clinical outcomes
- Epidemiological trends
- Diagnostic test results
Our goal is to identify disease risk patterns, discover biomarkers relevant to African populations, and improve public health planning and precision medicine.
Progress So Far
- Initial datasets analyzed include:
- HIV treatment outcomes
- Cancer genomic profiles
- Ongoing development of AI models to predict disease progression, treatment response, and risk stratification
- Collaborative data governance aligned with ethical standards and data sovereignty principles
Impact
- Supports precision public health by tailoring insights to local populations
- Contributes African data to the global biomedical research ecosystem
- Advances ethical and equitable use of AI in genomics
- Fosters local scientific capacity in bioinformatics and data science
Future Plans
We are expanding this work to incorporate:
- Neglected tropical diseases
- Rare genetic disorders in African populations
- Longitudinal patient data for chronic disease monitoring
In the long term, MozBioMed.AI aims to make AI-ready biomedical datasets available (under secure and ethical frameworks) to boost local innovation and inform global research.
Contact
- 17 Longford Place, Manchester, England, M14 5QQ
- +44 7936 386026
- contact@mozbiomed.co.uk
