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In Vivo Modeling of the Morbid Human Genome using Danio rerio
Published on: August 24, 2013
Model-based clinical utility of pharmacogenetic testing and its potential population impact on the use of essential
Tinashe Adrian Mazhindu1,2, Zedias Chikwambi1, Kevin V Grimes3
1African Institute of Biomedical Sciences and Technology, Harare, Zimbabwe.
Introduction:
Pharmacogenomic-related adverse drug reactions and treatment failure contribute to global morbidity. Evidence for PGx-guided therapy in sub-Saharan Africa remains limited with few implementation studies. This study evaluated the potential clinical utility and projected population-level impact of pharmacogenomic testing in Zimbabwe.
Methodology:
A cross-sectional analysis used the Zimbabwe Essential Medicines List, DPWG guidelines, Zimbabwean genotype/phenotype data, and locally approved Summary of Product Characteristics. For the actionable gene-drug pairs identified, the number needed to genotype values were calculated from DPWG-defined absolute risk reduction and local genotype-phenotype frequencies. Potential clinical utility was assessed using the Clinical Implication Score framework and compared with Dutch population data.
Results:
Among 308 medicines screened, 30 (9.7%) contained actionable pharmacogenomic biomarkers, corresponding to 38 gene-drug pairs, all classified as vital or essential medicines. Lower NNG values were observed for UGT1A1-atazanavir (5), UGT1A1-irinotecan (9), CYP2B6-efavirenz (26), and CYP2C9-phenytoin (25), whereas 61% of gene-drug pairs had NNG values > 1,000 compared with 47% in the Dutch population. Overall, 81.6% of PGx recommendations were concordant across populations, while 21.1% were reclassified, primarily due to differences in local genetic profiles and the limited inclusion of PGx information in the Zimbabwean SmPCs, with 42% lacking PGx information compared with 24% in the Dutch dataset.
Conclusion:
Many essential medicines in Zimbabwe have actionable pharmacogenomic biomarkers, but gaps in local genomic guidance remain. Strengthening local evidence generation and PGx implementation is essential.
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