The study of lipids can be traced back to the 19th century but, with recent advancements in analytical chemistry and biomolecular research the importance of lipids in biochemical processes and function continues to expand. This is especially true in the area of human disease progression where lipids are shown to provide important information on disease inception and progression. MS based lipidomics can be subdivided into qualitative and quantitative analysis. The quantitative analysis of lipids typically employs more rigorously developed methodology and the use of authentic standards to provide concentration information on specific lipid species. majority of research in this area has been focused on developing improved high resolution, information rich and comprehensive methods, which typically results in analysis times in the 15-30 minute time scale. However, these timescales mean that the application of LC-MS-based lipid phenotyping studies on large epidemiological cohorts and human sample biobanks can be limited by resource constraints. A sub 4-minute microbore LC-ion mobility-accurate mass MS (LC-IMS-MS) method has been developed for the rapid, profiling of lipids in biological fluids and tissues. The method was scaled directly from a conventional, 12 min, LC-MS analysis maintaining the chromatographic performance and lipid class separation observed in the longer methodology. A 75% saving in mobile phase consumption and analysis time was achieved by employing this microbore high throughput methodology, with the capability of detecting in-excess of 5,500 lipid features from a human plasma sample. The incorporation of ion mobility into the LC-MS analysis resulted in the generation of superior quality MS and MS/MS spectral data as well as enhanced resolution in IMS dimension based on lipid class. The rapid methodology was applied to the analysis of a pilot set of commercially sourced breast cancer plasma samples. The assay was capable of differentiating healthy control samples from diseased using multivariate statistical analysis based on their lipid phenotypes. The data showed phosphatidylcholines, triglycerides, diglycerides exhibited lower expression and phosphatidylserine showed increased expression in the breast cancer samples compared to healthy subjects.