The insidious growth of pancreatic cancer is a major factor contributing to its lethality. Only 10-15% of pancreatic cancers are resectable by the time they are detected. Early detection of pancreatic cancer through routine screening is clearly an unmet clinical need. Here we have applied neural network analysis to 1H magnetic resonance spectra of human plasma samples to differentiate between healthy subjects (control), subjects with benign lesions, and subjects with pancreatic ductal adenocarcinoma (PDAC). Our data support developing a neural-network approach to identify PDAC from 1H MRS of plasma samples.