Advanced thyroid cancer patients have limited treatment options and rarely result in a cure of the disease [1]. The most challenging patient groups to treat are radioiodine refractory, poorly differentiated and anaplastic thyroid cancer patients in specific. These tumors are often inoperable and resistant to conventional therapy. Therefore, these patients are in unmet need for novel treatment options. Targeting cancer with single drugs has generally not been successful in the past years. Tumors often show initial response to treatment, but eventually progress on treatment. In thyroid cancer, Lenvatinib, an oral multi kinase inhibitor, has demonstrated improvements in progression free survival but not overall survival [2]. Therefore, it is highly anticipated that the solution is combination therapy by targeting tumors simultaneously from several angles, in a synergistic manner. In the context of REPO4EU, thyroid cancer is one of the model diseases to test the hypotheses of network medicine using repurposable drugs [3]. Highly interconnected thyroid cancer modules have been constructed in silico based on systematic literature searches containing next generation sequencing (NGS) data and drug-target databases. Consequently, in vitro validation is currently being performed in thyroid cancer cell lines to validate drug repurposing compounds and identify synergistic combination therapies. To ultimately test the concept of network pharmacology based drugs repurposing in vivo, a proof of concept clinical trial is planned. Furthermore, to efficiently stratify patients in the clinic that might be amendable towards a drug repurposing approach, REPO4EU will attempt to use AI to identify patients that will not respond to radioiodine therapy. The current study aims to validate network medicine based drug repurposing in thyroid cancer, and several topics regarding the goals of REPO4EU in thyroid cancer are discussed.