Abstract
AbstractPsoriasis is a complex, heterogeneous condition arising from a combination of genetic, environmental, and immunological factors. Although many treatments exist for psoriasis, the heterogenous nature of the patients' response to treatment makes it difficult to predict whether a treatment will be effective for every individual patient or aspect of psoriasis. Precision medicine, otherwise known as personalized medicine, is a novel approach to improve clinical outcome in psoriasis, curb the risk of developing adverse events, and predict which treatment options will be effective for each patient. Here, we discuss several aspects of precision medicine related to psoriasis, including application of ‐omics technologies and clinical parameters to identify disease biomarkers and predict therapy outcomes; identification of predictors of psoriatic arthritis and other comorbidities; implementation of a personalized care model using mobile apps and telemedicine; and the development of machine learning algorithms that provide automated recommendations for providers and patients. These topics form the basis of the future of personalized medicine in psoriatic disease.
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