With the rapid progress in plasma proteomics and the ability to quantify proteins in a high throughput setting. The list of potential biomarkers is continuously expanded. To validate these biomarkers and show their potential as clinical tools for patient stratification, there is a need for improved sampling strategies. With recent understandings of the uniqueness amongst patients at a proteome level it has become evident that a lot of these potential biomarkers rely on longitudinal sampling. This is where microsampling has its biggest potential. Due to its non-invasive nature and good sample stability, microsampling allows for more frequent sample collection than conventional blood draws as well as a good tool for reaching a large population. In this study, we have collected paired plasma samples and Mitra tips from a cohort of 70 heart failure patients. With NT-proBNP being a highly interesting biomarker in heart failure studies, we have analyzed all paired samples using the Roche cobas assay targeting NT-proBNP. Additionally, all samples have been analyzed through data-independent acquisition (DIA) using both a SCIEX ZenoTOF 7600 and a Bruker timsTOF Pro 2, to further characterize the samples. All data processing of the MS results was done using DIA-NN followed by targeted data assessment using Skyline. The results from the Roche cobas measurements and the DIA analysis will be presented and highlight the possibility of using microsampling for patient stratification. The data proves how microsampling can be a useful asset for the future of precision medicine, where disease biomarkers can be assessed in a high throughput manner with a very limited patient burden. This way of screening for disease can improve the chances of early discovery of diseases while minimizing the cost of sampling.