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The translation of pharmacogenomic insights into clinical practice faces a significant barrier stemming from the lack of knowledge and guidance within healthcare institutions for prioritizing genetic tests and drug-gene interactions. To address this critical challenge, we provide a single, simple, user-friendly, and comprehensive electronic database of all important drug-gene interactions (n =421) with summaries of clinical recommendations per association as classified into our simple triple classification system (A, B, or C) depending on their clinical relevance (https://c1abo933.caspio.com/dp/ d81f70009de6d5055c2a44a5a970 ). The database can be looked at as a roadmap for healthcare providers in health care settings facilitating practicing pharmacogenomics in their institutions. To present how the database can be effectively utilized, we utilized the longitudinal prescribing data from across different UK health care institutions (the UKBB dataset) for ~ 230,000 participants to identify the most frequently prescribed drugs in the UK and linking them with our database. This enabled us to uncover the most frequently used drugs in the UK which have genotype-guided clinical recommendations. Then, we show, using a scoring approach, which specific drug-gene interactions should be prioritized over others in any given health care institution using an example from our analyzed UKBB data. Generally, we propose the genetic testing of 114 key genes covering all significant drug-gene associations. However, we specifically recommend prioritization of genetic testing for CYP2D6 and G6PD genes, acknowledging that they are involved in ~ 30% of all important drug-gene associations. This paper holds profound promise for advancing clinical practice and patient care.
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Mustapha Cherkaoui‐Malki (2025) studied this question.
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