The rise of antibiotic resistance in Gram-negative bacteria has become a global crisis and rapid detection of antibiotic resistance has never been more important. The Gram-negative bacterium Burkholderia pseudomallei, the causative agent of the often fatal infectious disease melioidosis, is intrinsically resistant to many antibiotics. Emergence of antibiotic resistance during treatment was once thought to be rare; however, we have begun identifying more cases as new molecular mechanisms are uncovered. Melioidosis treatment lasts up to six-months, providing B. pseudomallei with ample time to develop drug resistance. Trimethoprim-sulfamethoxazole (SXT), meropenem and doxycycline (DOX) are all important antibiotics used in treatment, with acquired resistance to these drugs being conferred by altered expression of resistance-nodulation-cell division (RND) efflux pumps AmrAB-OprA, BpeAB-OprB and BpeEF-OprC. These three efflux systems are upregulated when mutations occur in their associated repressor genes. Here, we developed a rapid triplex qPCR assay targeting the transporter genes amrB, bpeB and bpeF of these three efflux pumps. The triplex assay was tested on RNA extracted from six B. pseudomallei clinical isogenic pairs cultured from confirmed melioidosis patients, where the latter strain of each pair had mutations in at least one efflux pump regulator and was resistant to either SXT or DOX or had decreased susceptibility to meropenem. The triplex assay accurately detected efflux pump upregulation between clinical isogenic pairs where mutations in repressor genes had occurred. We further verified the triplex assay on seven laboratory-generated B. pseudomallei mutants that possessed efflux pump repressor mutations. This study is the first to provide a specific and robust triplex assay that can be used to detect efflux pump upregulation for detecting the emergence of DOX, SXT and meropenem resistance in B. pseudomallei. The development of molecular assays targeting antibiotic resistance mechanisms provides an exciting opportunity for clinicians to more rapidly identify potential treatment failure in near real-time, enabling informed alteration of treatment during an infection, more personalised treatment, better antibiotic stewardship and improved patient outcomes.