Inhibition of oncogenes and reactivation of tumor suppressors are well-established goals in anticancer drug development. Unfortunately many oncogenes and tumor suppressors are not classically druggable, in that they lack a targetable enzymatic activity and associated binding pockets that small molecule drugs can be directed to. This is especially relevant for transcription factors, which have long been thought to be undruggable. To address this gap, we have developed and described CRAFTT, a broadly applicable computational drug-repositioning approach for targeting transcription factors. CRAFTT combines transcription factor target gene sets with drug-induced expression profiling to identify small molecules that can perturb transcription factor activity. Network analysis is then used to derive a modulation index (MI) and prioritize predictions.