For many oncological conditions, the application of timely and patient-tailored targeted therapies, or precision medicine, is a major therapeutic development that has provided considerable clinical benefit. However, despite the application of increasingly sophisticated technologies, alongside advanced bioinformatic and machine-learning algorithms, this success is yet to be replicated for the rheumatic diseases. In rheumatoid arthritis, for example, despite an array of targeted biologic and conventional therapeutics, treatment choice remains largely based on trial and error. The concept of the 'precision gap' for rheumatic disease can help us to identify factors that underpin the slow progress towards the discovery and adoption of precision-medicine approaches for rheumatic disease. In a rheumatic disease such as rheumatoid arthritis, it is possible to identify four themes that have slowed progress, solutions to which should help to close the precision gap. These themes relate to our fundamental understanding of disease pathogenesis, how we determine treatment response, confounders of treatment outcomes and trial design.
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