ObjectivesThis study aimed to examine the efficacy of whole genome sequencing (WGS) in accurately predicting susceptibility profiles, potentially eliminating the need for conventional phenotypic drug susceptibility testing (pDST) for first-line antituberculosis drugs in routine tuberculosis (TB) diagnosis. MethodsOver the period of 2017-2020, 1114 Mycobacterium tuberculosis complex isolates were collected with DST conducted using the MGIT960 system and WGS performed for predicting drug resistance profiles. In addition, we implemented a new algorithm with an updated WGS workflow, omitting pan-susceptible strains from pDST. ResultsResults showed that out of 1075 analysed isolates, WGS based genotypic sensitivity predictions for isoniazid, rifampicin, ethambutol, and pyrazinamide were 100% (95% CI: 99.6%-100%), 100% (95% CI: 99.62%-100%), 99.8% (95% CI: 99.26%-99.94%), and 100% (95% CI: 99.63%-100%), respectively. In contrast, the WGS based genotypic resistance prediction, was 98.85% (95% CI: 93.77%-99.79%) for isoniazid, 94.74% (95% CI: 82.71%-98.54%) for rifampicin, 86.96% (95% CI: 67.87%-95.46%) for ethambutol, and 75.7% (95% CI: 59.9%-86.63%) for pyrazinamide. Moreover, WGS enabled the implementation of a new testing algorithm, that made unnecessary to perform pDST in 954 of all 1075 samples (88.7%) and in 890 of 901 pan-susceptible samples (98.8%). ConclusionIntegrating WGS into TB management offers significant potential to replace phenotypic drug susceptibility testing especially for problematic drugs like pyrazinamide and ethambutol, potentially improving treatment outcomes.