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The objective of the current study is to set in silico models based on systems biology and investigate the optimal treat-to-target strategy for Still\u2019s disease as a proof-of-concept of the modeling approach.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Molecular characteristics of Still\u2019s disease and data on biological inhibitors of interleukin (IL)-1 (anakinra, canakinumab), IL-6 (tocilizumab, sarilumab), and glucocorticoids as well as conventional disease-modifying anti-rheumatic drugs (DMARDs, methotrexate) were used to construct\n                      <jats:italic>in silico<\/jats:italic>\n                      mechanisms of action (MoA) models by means of Therapeutic Performance Mapping System (TPMS) technology. TPMS combines artificial neuronal networks, sampling-based methods, and artificial intelligence. Model outcomes were validated with published expression data from sJIA patients.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Biologicals demonstrated more pathophysiology-directed efficiency than non-biological drugs. IL-1 blockade mainly acts on proteins implicated in the innate immune system, while IL-6 signaling blockade has a weaker effect on innate immunity and rather affects adaptive immune mechanisms. The MoA models showed that in the autoinflammatory\/systemic phases of Still\u2019s disease, in which the innate immunity plays a pivotal role, the IL-1\u03b2-neutralizing antibody canakinumab is more efficient than the IL-6 receptor-inhibiting antibody tocilizumab. MoA models reproduced 67% of the information obtained from expression data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Systems biology-based modeling supported the preferred use of biologics as an immunomodulatory treatment strategy for Still\u2019s disease. Our results reinforce the role for IL-1 blockade on innate immunity regulation, which is critical in systemic autoinflammatory diseases. This further encourages early use on Still\u2019s disease IL-1 blockade to prevent the development of disease or drug-related complications. Further analysis at the clinical level will validate the findings and help determining the timeframe of the window of opportunity for canakinumab treatment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13075-021-02507-w","type":"journal-article","created":{"date-parts":[[2021,4,23]],"date-time":"2021-04-23T02:02:32Z","timestamp":1619143352000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Application of systems biology-based in silico tools to optimize treatment strategy identification in Still\u2019s disease"],"prefix":"10.1186","volume":"23","author":[{"given":"Cristina","family":"Seg\u00fa-Verg\u00e9s","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mireia","family":"Coma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Kessel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Serge","family":"Smeets","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dirk","family":"Foell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7107-327X","authenticated-orcid":false,"given":"Anna","family":"Aldea","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,4,23]]},"reference":[{"issue":"4","key":"2507_CR1","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1016\/j.berh.2018.02.002","volume":"31","author":"M Pardeo","year":"2017","unstructured":"Pardeo M, Bracaglia C, De Benedetti F. 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