Abstract:
Personalized medicine refers to using individual patient characteristics including phenotype and genotype, to tailor the therapeutic strategy. This approach seeks to challenge the “one-size-fits-all” method to patient management. In the bargain, it reduces adverse drug reactions, improves compliance, and reduces the economic burden of disease management. Traditionally, as extrapolated from usage in oncology, the term applied to using genomic, metabolomic, and epigenomic data in selecting medications; however, even simpler data such as clinical phenotype can aid therapeutic decision making. Autoimmune diseases provide many such data points, owing to the multi-organ nature of clinical manifestations as well as the availability of a wide variety of tests for antibodies as well as cytokines. Rheumatologists already use personalization intuitively, based on various factors such as organ involvement, comorbidities, fertility concerns, and costs. However, in a literature search, few studies look at tailoring treatment regimens to individual characteristics. Building coherent databases can help in better analysis of data and answering locally relevant questions in the future.