Its potential hinges on representative data, inclusive research, and tools that reflect the diversity they aim to serve today. Yet much of global genomics has been shaped by datasets with scant African representation, producing gaps in diagnostics, drug efficacy, and predictive models. Closing those gaps requires focused investment across the continent, from data infrastructure and bioinformatics education to ethical governance and the deliberate application of AI that learns from African genomes, not around them.
In a discussion with Global South Pole, Professor Emile Chimusa, the co-chair of the state of data science for health in Africa, argued that Africa must lead the generation, stewardship, and interpretation of its own genomic data. He said the continent’s strength lies in building broad capacity, practical training in bioinformatics, scalable computing, ethical data-sharing, and AI systems trained on African diversity. For him, reclaiming Africa’s genomic narrative is both a scientific and moral imperative.
“Africa is the homeland of humanity […] all genetic variation found elsewhere in Europe, Asia, America, Oceania, different continents, you [will find] it in Africa. So, to understand human variation in terms of drug response, treatment variations, and the risk variation in the risk of disease or susceptibility of diseases, my view is to actually analyze complex data and the complex genetic variation data [that] is in Africa,” Professor Chimusa said.
To listen to the whole conversation, tune in to the Global South Pole podcast, brought to you by Sputnik Africa.
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