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Background and Importance Adverse drug reactions are a major and largely preventable source of harm. Risk reflects the interplay of genotype with age, comorbidities, concomitant therapies, and route of administration. Pharmacogenomics can anticipate non-response and toxicity, informing drug choice, dose, and monitoring. In hospitals, pharmacists are pivotal in translating this evidence into timely, evidence-based decisions. Yet bedside adoption is hindered by non-uniform reporting, inconsistent diplotype-to-phenotype mapping, and limited interoperability with electronic health records (EHRs).Aim and Objectives To set out a pragmatic framework that makes pharmacogenetic results actionable within clinical decision support (CDS) in hospital pharmacy, and to prioritise high-impact gene–drug pairs for immediate implementation.Material and Methods We synthesised guidance from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG), alongside regulatory sources from the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). The framework covers: (i) uniform reporting; (ii) curated diplotype-to-phenotype translation; (iii) computable artefacts using Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) and Logical Observation Identifiers Names and Codes (LOINC); and (iv) linkage to Computerised Physician Order Entry (CPOE). Exemplar use-cases were selected by clinical impact and feasibility in acute care.Results We outline CDS rules and pharmacist actions for five priority pairs:CYP2C19–clopidogrel: in poor/intermediate metabolisers, prefer prasugrel or ticagrelor after percutaneous coronary intervention.HLA–B*57:01–abacavir: pre–treatment testing; contraindicated if positive.CYP2D6–codeine: avoid in ultra–rapid metabolisers and in paediatric or postpartum patients; favour non–prodrug analgesics.DPYD–fluoropyrimidines: avoid or start at reduced dose with close monitoring.SLCO1B1–statins: use lower dose or alternative agents in carriers at higher myopathy risk.Embedding results as FHIR/LOINC resources makes genetic data queryable at order time, enabling real-time contextual alerts, dose suggestions, and monitoring pathways; this confers immediate operational relevance for the hospital pharmacist.Conclusion and Relevance A concise, standards-based pathway can convert static pharmacogenetic reports into pharmacist-mediated, real-time CDS at the bedside. Starting with a small set of high-yield gene–drug pairs delivers tangible safety gains while building the infrastructure for broader panels. Implementation should align with analytical quality (ISO 15189), informed consent, and data protection (GDPR), and be supported by reimbursement, interoperability, and ongoing training–priorities also recognised at the European Association of Hospital Pharmacists.Conflict of Interest No conflict of interest