Abstract Clinical proteomics studies often involve multiple investigators located at different physical locations necessitating a centralized platform for joint access to data and other information pertinent to the study. To help communicate pathology targets of interests from remote researchers to the on-site technical team, the Pathology Directed Mass Spectrometry (PDMS) web application was developed. PDMS was designed to be a secure, online digital pathology platform specifically configured for down-stream mass spectrometry imaging (MSI) analysis. Hosting ultra-high resolution digital microscopy images of stained serial tissue sections, PDMS allows researchers to zoom into their samples to review and annotate specific areas for analysis. Once finalized, annotated images are exported from PDMS for MSI targeting. Built for HTML5 browsers, PDMS was deployed in a secure LAMP (Linux, Apache, MySQL, PHP) environment, utilizing a Javascript visualization engine and server-side conversion tools. In a pathology directed mass spectrometry profiling experiment, two sections of a tissue specimen are collected, one on a mass spectrometry target and one that is stained for histological evaluation. A pathologist annotates a digital microscopy image to indicate areas of interest for mass spectral analysis. The annotated image is then merged with an image of the unstained section and after appropriate sample preparation, mass spectra are collected from the annotated areas. A major advantage to this type of analysis is that it is high throughput and is conducive to downstream biostatistical analysis for biomarker discovery. The PDMS software has been successfully used in the molecular differentiation of histological patterns in stage I pulmonary carcinomas as part of a joint collaboration with Memorial Sloan Kettering Cancer Center. Image annotation was carried out remotely prior to mass spectral analysis in house. Statistical analyses of the mass spectral data resulted in over 85% classification accuracies in differentiating histological tumor subtypes within individual pulmonary carcinoma patient samples. Citation Format: Erin H. Seeley, R. Ryan Dunkerley, Andre L. Moreira, Robert J. Downey, Greg W. Kilby. A novel web interface to facilitate pathology directed mass spectrometry. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1823. doi:10.1158/1538-7445.AM2015-1823