AI-Powered Rare Disease Decision Support for Africa
Helping clinicians interpret symptoms and genomic signals to identify rare diseases earlier and guide next clinical steps.
GenRARE supports clinical decision-making. It does not replace diagnosis.
The Challenge with Rare Disease Diagnosis
Rare diseases often present with non-specific, overlapping symptoms, making them difficult to diagnose without specialized tools.
Non-specific symptoms
Symptoms often overlap with common conditions, leading to confusion and misdiagnosis.
Inaccessible tools
Genomic interpretation tools are often expensive or not designed for clinical workflows.
Lack of local support
Clinicians lack decision support tailored specifically to African populations and genetics.
Delayed diagnosis
Diagnosis delays lead to prolonged patient suffering and missed treatment windows.
"We suspect rare diseases, but we don’t have tools to narrow possibilities quickly."
How GenRARE Helps Clinicians
Three core pillars designed to transform clinical uncertainty into actionable insight.
Phenotype–Genotype Intelligence
Combines patient symptoms with deep gene–disease knowledge to map clinical features to potential genetic causes.
Explainable AI Prioritization
Ranks likely rare diseases and, crucially, explains why specific conditions are prioritized to build clinician trust.
Actionable Clinical Pathways
Goes beyond naming a disease by providing referral guidance, confirmatory tests, and connecting to local centers.
Built for Real Healthcare Teams
Designed to support every role in the rare disease diagnosis journey.
Genomics & Labs
- Variant interpretation support
- Case triaging
- Report generation
- Data validation
From Symptoms to Clinical Insight
A streamlined workflow that fits your clinical practice.
Patient Context
Enter age, symptom onset, and observed clinical features.
Genomic Hint
Optional input of known gene variants or genomic data.
AI Analysis
Phenotype–genotype mapping and explainable AI processing.
Clinical Insight
Review top disease hypotheses with confidence levels.
Next Steps
Guidance on confirmatory tests and specialist referrals.
Africa-First by Design
Population-Specific Intelligence
Prioritizes diseases prevalent in African populations.
Robust with Partial Data
Works effectively with incomplete clinical data typical in low-resource environments.
Low-Resource Optimization
Lightweight deployment suitable for diverse connectivity environments.
Responsible & Explainable AI
GenRARE does not provide diagnoses. All outputs are decision-support suggestions designed with clinician oversight in mind. We prioritize transparent model logic, ensuring every suggestion comes with an explanation.
Built by a Multidisciplinary Team
Experts in Medicine, Genomics, and Artificial Intelligence.
Oluwapelumi Samuel Solagbade
Medical Lead / Research Coordinator
Obafemi Awolowo University
Medicine, Informatics, Translational Research
Defines medical problem statements, guides phenotype–genotype mapping, validates biological relevance, leads presentation and outreach.
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Habibullah Shittu Salih
Genomics & Bioinformatics Lead
Abubakar Tafawa Balewa University
RNA-Seq, Variant Annotation, AMR Genomics
Manages data preprocessing, variant calling, and annotation using tools such as VEP, ANNOVAR, ClinVar, gnomAD, and Orphanet.
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Ononlememen Chizoba
AI/ML Engineer
University of Lagos
Machine Learning, Deep Learning, Computer Vision, Data Science
Designs predictive models for variant effect prioritization and phenotype correlation.
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Okeke Johnpaul
Software Engineer / UI–UX Developer
University of Lagos
Full-Stack Development, Visualization, Human-Centered Design
Develops the interactive dashboard for visualization and user-friendly model deployment.
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Fadeyi Bilikis Abiola
Clinical/Software Engineer
University of Lagos
Clinical Insights, Mobile/Software Development
Develops easily accessible mobile app local doctors can reach to improve diagnostics.
LinkedInExperience GenRARE in Action
Advancing rare disease diagnosis in Africa through explainable AI.