Most candidate anti-bacterials are identified on the basis of their whole cell anti-bacterial activity. A critical bottleneck in the early discovery of novel anti-bacterials is tracking the structure activity relationship (SAR) of the novel compounds synthesized during the hit to lead and lead optimization stage. It is often very difficult for medicinal chemists to visualize if the novel compounds synthesized for understanding SAR of a particular scaffold have similar molecular mechanism of action (MoA) as that of the initial hit. The elucidation of the molecular MoA of bioactive inhibitors is critical. Here, a new strategy and routine assay for MoA de-convolution, using a microfluidic platform for transcriptional profiling of bacterial response to inhibitors with whole cell activity has been presented. First a reference transcriptome compendium of Mycobacterial response to various clinical and investigational drugs was built. Using feature reduction, it was demonstrated that subsets of biomarker genes representative of the whole genome are sufficient for MoA classification and deconvolution in a medium-throughput microfluidic format ultimately leading to a cost effective and rapid tool for routine antibacterial drug-discovery programs.