BACKGROUND

Pharmacogenomics research is currently revolutionizing treatment optimization by discovering molecular markers. Medicines are the cornerstone of treatment for both acute and chronic diseases. Pharmacogenomics associated treatment response varies from 20% to 95%, resulting in from lack of efficacy to serious toxicity. Pharmacogenomics has emerged as a useful tool for therapy optimization and plays a bigger role in clinical care going forward. However, in Africa, in particular in Ethiopia, such studies are scanty and not generalizing. Therefore, the objective of this review was to outline such studies, generating comprehensive evidence and identify studied variants' association with treatment responses in Ethiopian patients.

METHODS

The Joanna Briggs Institute's updated 2020 methodological guidelines for conducting and guidance for scoping reviews were used. We meticulously adhered to the systemic review reporting items checklist and scoping review meta-analyses extension.

RESULTS

Two hundred twenty-nine possibly relevant studies were searched. These include: 64, 54, 21, 48 and 42 from PubMed, Scopus, Google Scholar, EMBASE, and manual search, respectively. Seventy-seven duplicate studies were removed. Thirty-nine papers were rejected with justification, whereas 58 studies were qualified for full-text screening. Finally 19 studies were examined. The primary pharmacogene that was found to have a significant influence on the pharmacokinetics of efavirenz was CYP2B6. Drug-induced liver injury has frequently identified toxicity among studied medications.

CONCLUSION AND FUTURE PERSPECTIVES

Pharmacogenomics studies in Ethiopian populations are less abundant. The studies conducted focused on infectious diseases, specifically on HAART commonly efavirenz and backbone first-line anti-tuberculosis drugs. There is a high need for further pharmacogenomics research to verify the discrepancies among the studies and for guiding precision medicine. Systematic review and meta-analysis are also recommended for pooled effects of different parameters in pharmacogenomics studies.