The Drug Dose That Works in London May Be Wrong for Nairobi: The case for Genomic Medicine in Kenya

Every disease affecting a Kenyan community leaves behind a molecular mark. From genes in malaria parasites that confer resistance to artemisinin to cancer variants affecting Kenyan women, who are younger than the global average, we are left with a code to interpret. In an analysis published in Global Health Action (Olopade, 2016), a decade of genomic research involving Sub-Saharan African populations was examined, with Kenya ranking third overall among the most studied populations, accounting for 7.5% of all publications. Fewer than half (46.9%) of the total first authors were from Sub-Saharan Institutions, with the leading disease studies being HIV, Malaria, TB, Cancer, and cardiovascular disease, in that order. Regionally, East Africa ranked third at 24.2%, behind Southern Africa and West Africa.

Kenya is a frequent subject of genomics research, but we have yet to be the leader of it, and this op-ed is a case for changing that. There is a common misconception (perceivably) that genomics is a luxury discipline better left for the West, which couldn’t be further from the truth. Genomics has advanced disease surveillance by enabling the identification, tracking, and analysis of pathogens at the DNA level. Unlike classical epidemiology, which tells us how many people got sick and where, genomics tells us which strain caused the outbreak, how it spread, which populations are likely to suffer more due to genetic vulnerabilities, and which drugs will work best for which individuals.

Data from the published analysis showed that only about one-tenth of the studies addressed non-communicable diseases, a dangerous trend given that Kenya’s disease burden has shifted dramatically from communicable to non-communicable diseases, which account for nearly 4 in 10 deaths. Investing in genomic epidemiology means deliberately directing research towards the actual disease burden that Kenyans face.

First, integrate genomics into the national disease surveillance architecture to enable near-real-time pathogen and variant detection and rapid interpretation of emerging threats through county health systems and KEMRI’s surveillance networks. Second, fund the NCD genomics gap. Much of Kenya’s R&D funding, roughly 100 billion shillings, comes from international sources, with USAID cuts rendering the remaining external donors even more crucial to filling the resulting gap. In July 2025, Japan granted KEMRI KES 3 billion for a high-level biosafety facility to strengthen preparedness for biothreats and future pandemics, and to support disease surveillance, pathogen identification, and the development of diagnostic kits, drugs, and vaccines.

Third, assert data sovereignty by establishing a Kenyan Reference Genome bank. The 2025 Kenyan Reference Genome Initiative involved genome sequencing of 1000 healthy Kenyan adults to reflect the country’s ethnic and geographic diversity and to enable the identification of variants critical to understanding disease risk and drug response. The study also aims to establish a secure Kenya-hosted genomic database with restricted access to ensure data sovereignty and ethical oversight.

A practical starting point for students and early-career researchers is to develop the computational skills needed to analyze data generated by sequencing machines. Healthcare workers need to connect the lab to the bedside since genomic findings are only useful when incorporated into decision-making. They can advocate for pharmacogenomic testing and understanding what a genetic counseling referral looks like. For example, Efavirenz has a standard prescribed dose of 600mg daily, globally uniform, but the CYP2B66 genotype, which impairs efavirenz metabolism, is found at a higher frequency in African populations. This means the drug exposure levels in some patients would be more than double what is recommended, leading to adverse outcomes such as CNS toxicity.

For policymakers and health sector leaders, the question is whether the political will and public funding will follow the call for a country with infrastructure to lead the way in genomics.

AI and machine learning have opened a window that won’t stay open forever. These tools can now prioritize samples for sequencing, predict viral evolution related to resistance, virulence, or antigenic drift, and detect anomalous transmission patterns in real time. However, they are only as good as the data they are trained on. The underrepresentation of African populations in genomic datasets has major implications for the clinical care, therapeutics, and diagnostics developed in non-African settings when applied to African populations. This creates the right opportunity to develop a locally grounded National Genomics Strategy that establishes a tradition for Kenyan scientists, institutions, and researchers to build on.

Every Kenyan carries a version of the most sophisticated instruction manual ever written: the human genome, which is highly genetically diverse. We have the potential to discover novel variants that are critical to understanding disease risk, treatment response, and human biology. A decade since Olopade’s analysis, infrastructure has grown, the talent pipeline is in place, and what remains is commitment. From universities to take up bioinformatics seriously, hospitals to connect findings with patient care, the government to increase research funding, including NCD genomics alongside infectious disease, and scientists to publish research with Kenyan data first.

References: Building local capacity for genomics research in Africa: recommendations from analysis of publications in Sub-Saharan Africa from 2004 to 2013 — PMC

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