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Systems pharmacology approaches have the potential to provide mechanistic frameworks with which to predict and understand how drugs modulate biological systems. Here, we combine network modeling of the fibroblast signaling network with 36 unique drug\u2010target interactions from DrugBank to predict drugs that modulate fibroblast phenotype and fibrosis. Galunisertib was predicted to decrease collagen and \u03b1\u2010SMA expression, which we validated in human cardiac fibroblasts. In vivo fibrosis data from the literature validated predictions for 10 drugs. Further, the model was used to identify network mechanisms by which these drugs work. Arsenic trioxide was predicted to induce fibrosis by AP1\u2010driven TGF\u03b2 expression and MMP2\u2010driven TGF\u03b2 activation. Entresto (valsartan\/sacubitril) was predicted to suppress fibrosis by valsartan suppression of ERK signaling and sacubitril enhancement of PKG activity, both of which decreased Smad3 activity. Overall, this study provides a framework for integrating drug\u2010target mechanisms with logic\u2010based network models, which can drive further studies both in cardiac fibrosis and other conditions.<\/jats:p>","DOI":"10.1002\/psp4.12599","type":"journal-article","created":{"date-parts":[[2021,2,11]],"date-time":"2021-02-11T23:30:25Z","timestamp":1613086225000},"page":"377-388","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Network model\u2010based screen for FDA\u2010approved drugs affecting cardiac fibrosis"],"prefix":"10.1002","volume":"10","author":[{"given":"Angela C.","family":"Zeigler","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering University of Virginia Charlottesville Virginia USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anirudha S.","family":"Chandrabhatla","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering 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