BACKGROUND: Effective drugs for tendinopathy are lacking, resulting in significant morbidity and re-tearing rate after operation. Applying systems biology to identify new applications for current pharmaceuticals can decrease the duration, expenses, and likelihood of failure associated with the development of new drugs. METHODS: We identify tendinopathy signature genes employing a transcriptomics database encompassing 154 clinical tendon samples. We then proposed a systems biology based drug prediction strategy that encompassed multiplex transcriptional drug prediction, systematic review assessment, deep learning based efficacy prediction and Mendelian randomization (MR). Finally, we evaluated the effects of drug target using gene knockout mice. RESULTS: We demonstrate that sirolimus is a repurposable drug for tendinopathy, supported by: 1) Sirolimus achieves top ranking in drug-gene signature-based multiplex transcriptional drug efficacy prediction, 2) Consistent evidence from systematic review substantiates the efficacy of sirolimus in the management of tendinopathy, 3) Genetic prediction indicates that plasma proteins inhibited by mTOR (the target of sirolimus) are associated with increased tendinopathy risk. The effectiveness of sirolimus is further corroborated through in vivo testing utilizing tendon tissue-specific mTOR gene knockout mice. Integrative pathway enrichment analysis suggests that mTOR inhibition can regulate heterotopic ossification-related pathways to ameliorate clinical tendinopathy. CONCLUSIONS: Our study assimilates knowledge of system-level responses to identify potential drugs for tendinopathy, and suggests sirolimus as a viable candidate. A systems biology approach could expedite the repurposing of drugs for human diseases that do not have well-defined targets.