Updated project metadata. Robust, reliable quantification of large sample cohorts is often essential for meaningful clinical or pharmaceutical proteomics investigations, but it is technically challenging. When analyzing very large numbers of samples, isotope labeling approaches may suffer from substantial batch effects; and even with label-free methods, it becomes evident that low-abundance proteins are not reliably measured due to missing data peaks. The MS1-based quantitative proteomics pipeline, IonStar, was designed to address these challenges. To demonstrate the capability of IonStar to achieve highly reproducible and robust proteomics quantification in large sample cohorts, we applied IonStar to proteomics investigation in serum samples collected from 60 human subjects with moderate acute respiratory distress syndrome (ARDS).