Adverse drug reactions (ADRs) are an unintentional result of pharmaceutical therapy for some patients. They can have a substantial effect on patient mortality and morbidity, with the capacity to inflict large cost and resource implications on the health services. Many of these reactions could be likely avoidable with genetic testing, which has been acknowledged by worldwide medicine agencies and implemented for a handful of drugs. This thesis applies an economic model to assess the cost-utility of a multi-gene panel test to avoid adverse drug reactions, using a combination of cost-effective genes contained within a panel test. This technology profiles a patient’s genetic susceptibility to ADRs and may have the ability to limit lifetime adverse drug reactions, saving on cost accumulation and improving patient health. A decision-analytic framework was adopted to determine the cost-utility of several gene panel combinations. This involved combining the cost and QALY outcomes of previous economic evaluations for single-gene testing to avoid adverse drug reactions and estimating the cost-utility of single-gene testing for associations lacking economic evidence. Using the base-case scenario (ICER/QALY <£20,000, cost of test £30) on a multi-gene panel including 14 drug-gene associations, multi-gene panel testing was found to be cost-effective in patients eligible for carbamazepine (HLA-A*31:01), abacavir (HLA-B*57:01), mercaptopurine (TPMT), Clopidogrel (CYP2C19), warfarin (CYP2C9), phenytoin (HLA-B*15:02) and irinotecan (UGT1A1). This panel resulted in a cost-saving of £35 and a QALY gain of 0.0077. This evidence suggests that prospectively testing using a panel test of genes within and beyond the HLA family (and returning the incidental findings for pre-emptive use) is a cost-effective method to avoid adverse drug reactions in the relevant disease groups.