Quantitative nuclear magnetic resonance (qNMR), as a primary approach used to characterize SI (International System of Units)-traceable organic compounds, is based on the proportionality of intensities from analyte and standard, which implies a fundamental requirement that the peaks to be used for quantitation are isolated from impurities. Therefore, sufficient dispersion or a data analysis method has to be used to enable isolation of the peaks for quantitation of impurities. This technique offers many metrological advantages, though significant challenges associated with factors such as calibration reference materials, experimental parameter optimization and isolation of quantitative peaks must be considered to ensure confidence in the results. This review focuses on the development of advanced qNMR methods (including combined qNMR methods), especially those that enhance measurement selectivity and mitigate biases associated with chemical interferences, aiming to satisfy this requirement. For this aim, in recent years, different advanced qNMR approaches have been developed to remove interferences spatially, mathematically, spectroscopically, etc. The principles, advantages, challenges and future prospects of these approaches are introduced in this review. These advanced approaches aim to improve qNMR accuracy for analytes with molecular weight up to ~6000 g/mol. The approaches are aimed at removing potential systematic errors in qNMR to improve its trueness and its application as primary metrolgical method and routine analysis method.