PROJECT SUMMARY/ABSTRACT Here we propose a Systems Biology Core (SBC) for the Accelerating Medicines Partnerships in Autoimmune and Immune-Mediated Diseases (AMP AIM). The AMP AIM will use high dimensional molecular and cellular assays to define the key cell states, pathways, and molecular components of tissue inflammation and damage by examining patient tissue and blood samples. Ultimately, we seek to define the components of tissue inflammation in autoimmune and inflammatory diseases including psoriatic spectrum diseases (PSD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Sjogren’s syndrome (SS), and other related conditions. AMP RA/SLE initiated this process by querying 106 single cells in inflamed RA synovial and SLE nephritis tissue samples using multimodal strategies; it defined key cell states in tissue inflammation, including T peripheral helper T cells (Tph), GZMK+ CD8+ T cells, HLA-DR+THY1+ fibroblasts, and autoimmune- associated B cells (ABCs). Now, to understand how these and emerging cell-states function and interact to cause disease, it will be essential to obtain high dimensional data on patient sample data across a spectrum of diseases and disease sub-phenotypes. These data may capture the cellular states; the spatial localization of cell states, proteins and transcripts; histological features; and other tissue parameters. A powerful and skilled team that is able to define strategies to analyze this data, integrate multiple modalities of data, and integrate results from across a diverse set of diseases and tissues will be essential to the success of this program. We build from our experience leading the Systems Biology Group within the Accelerating Medicines Partnerships Rheumatoid Arthritis and Systemic Lupus Erythematosus (AMP RA/SLE). We have built a team that is skilled at analysis of diverse modalities and computational biology. We have specific experience and expertise in inflammatory diseases. Here we propose to: (1) Develop Tools and Technology to analyze high dimensional cellular and molecular data. This includes optimizing existing bioinformatics and computational tools. It also includes developing new computational and statistical methods to integrate high dimensional data manifestation of disease. (2) Enable collaboration throughout the network and facilitate systems level analysis. We envision that this is an integrated activity with the network, where we will devise and ultimately create an integrated model of tissue inflammation across diseases to define features that drive clinical disease. This will require the development of new statistical and computational methods. It will also require tight collaboration within the network including data synchronization, storage, sharing, and clinical data integration. In addition, we will engage the network by offering consultation, technical support and training in high dimensional data analysis. .