Purpose of review: Precision medicine is the tailoring of medical care to subcategories of disease. In pediatric rheumatology, these subcategories must first be defined by their specific molecular immunological profiles, and then the effects of growth and puberty, developmental immunological changes, and differences in treatment options and adherence considered when designing therapeutic strategies. In the present review, we summarize the unmet needs in pediatric rheumatology before such precision medical care can be effectively delivered to affected patients.
Recent findings: The current clinical classification of pediatric rheumatic diseases does not provide all the information necessary for prognostication and accurate therapeutic selection. Many studies have highlighted the molecular differences between disease subcategories and the dissimilarities in the molecular manifestations of the same disease between patients. Harnessing such discoveries by collaborating with various research networks and laboratories is required to interrogate the multifactorial nature of rheumatic diseases in a holistic manner.
Summary: Integration of big data sets generated from well defined pediatric cohorts with rheumatic diseases using different high-dimensional technological platforms will help to elucidate the underlying disease mechanisms. Distilling these data will be necessary for accurate disease stratification and will have a positive impact on prognosis and treatment choice.