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This database and the analytic pipeline were incorporated into a web-based portal allowing users to interact and upload their own data for comparison.Results: Here, we described EPIC with examples of its potential by exploring the evolution of some representative immune subsets over the full gradient of ages.Disclosure of Interest None Declared Introduction: An atlas of the developing immune system is key to understanding its normal maturation and identifying disease-associated cell subsets.

This results in issues of fragmentation by focusing on individual cell subsets and lack the ability to transverse the whole developmental gradient from neonatal to adult age.The predicted outcome was clinical inactive disease for 6 or more months starting within one year of the diagnosis in patients who did not receive early biologic agents or triple DMARD therapy.Models were developed in 200 random splits of 75% of the cohort, and tested on the remaining 25% of subjects, calculating expected and observed frequencies of remission and c-index values.Quality control was performed before dimensional reduction and clustering to identify the cell subsets using our in-house analysis and visualisation pipeline.

Their frequencies across the ages were presented as 3-D frequency histograms to create the immune landscape.

Compared to 5% of subjects identified by JIA category alone, the model identified 14% of the cohort as having a low chance of remission (0.70), it identified three times more subjects with low chance of remission than JIA category alone, and it may serve as a benchmark for judging the value added by future biomarkers.



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