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In this study, we proposed a novel drug reposition framework based on cosine similarity called “TReD” (Transcriptome-informed Reversal Distance) that embeds the disease signatures and drug response profiles into a high-dimensional normed space to quantify the reversal potential of candidate drugs in a disease-related cell-based screening.