Hector V Ramos, Krystle P Cobian, Jayashri Srinivasan, Christina A Christie, Catherine M Crespi, Teresa Seeman
Investigating the relationship between participation in the building infrastructure leading to diversity (BUILD) initiative and intent to pursue a science career: A cross-sectional analysis
Evaluation and program planning
liquid chromatographymass spectrometry lcms widely used identification quantification nglycans monoclonal antibodies mabs owing high sensitivity accuracy however resourceintensive nature necessitates development rapid costeffective orthogonal analysis approaches study aims develop online method utilizing extreme gradient boosting xgboost machine learning ml algorithm real time quantification instantpc labelled nglycans liquid chromatography lc fluorescence detector fld lcfld profile preprocessed baseline correction noise reduction prior fed machine learning ml algorithm algorithm successfully tested commercial inhouse developed mabs validated using lcms quantification reference lcfldml model predicted values par lcms values root mean square error 05 r2 095 average errors using ml model 180 reduced minimum 28 40 origin 15 manual 107 based integration respectively approach reduces data analysis time per sample 70 5 min 15 min thereby offering time resource efficient orthogonality lcms quantification nglycans mabs