The broad availability of genetic information and technologies heralds an era when practitioners will utilise genomic testing to individualise patients’ care. Pharmacogenomics uses a spectrum of approaches to explore the association of genetic variation with drug efficacy or toxicity. Investigators have described a broad array of genetic polymorphisms that confer inter-individual differences in drug response. Pharmacogenomics offers the potential to improve drug effectiveness, reduce adverse drug reactions and provide cost-effective care. However, it has had little impact on current clinical practice and the economic implications of pharmacogenomics remain unclear.
Assessing the incremental cost effectiveness of a pharmacogenomic strategy involves examination of factors associated with the genotype of interest, the genomic test, the disease state and the treatment. A pharmacogenomic strategy is likely to be cost effective when: (i) the polymorphism under consideration is prevalent in the population and has a high degree of penetrance; (ii) genetic testing is highly sensitive and specific, and less costly alternative tests that could be used to individualise therapy are not readily available; (iii) the disease state involves outcomes with significant morbidity or mortality if left untreated; and (iv) the treatment involves significant outcomes and/or costs that can be impacted by genotype-individualised therapy.
We foresee pharmacogenomic applications being particularly relevant for drugs: with a narrow therapeutic index or a high degree of variability in inter-individual response; where there are limitations in current methods for monitoring their adverse effects and treatment responses; and where there are few alternative treatment options. Because of the characteristics of chemotherapeutic agents and the severity of clinical outcomes in cancer, oncology appears to be one of the most appropriate disease areas for the application of pharmacogenomics.
We have developed a framework which can assist researchers, pharmacists, physicians, and policy makers in evaluating the implications of specific strategies, and identifying when formal cost-effectiveness analyses should be conducted to quantitatively evaluate the benefits of pharmacogenomics.
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This research was funded by a grant from the Seattle Veteran’s Administration Medical Center funded by the Robert Wood Johnson Clinical Scholar’s Program and by a Health Outcomes Research Starter Grant funded by the PhRMA Foundation. The authors have no conflicts of interest relevant to the content of this review.
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