By engineering a tightly controlled, automated process similar to a semiconductor line, we solved the issue of noise and looked into the proteome.
Modern proteomics-based biomarker discovery is a complicated process with many steps including sample acquisition and storage, laboratory processing, and data collection on a wide variety of possible detection instruments. As with most complicated processes, proteomics is subject to the introduction of noise, both biological and technical, at any of these steps. Historically, most hypothesis-generating proteomics efforts have failed because the introduced technical noise outweighs the true biological biomarker signal.
Dr. Hillis and Dr. Agus, Applied Proteomics' founders, realized that to fully enable successful proteomics-based biomarkers discovery, the noise problem needed to be resolved and this would only be possible by treating the system as an industrial process rather than as an academic experiment. The complicated steps (and potential noise sources) were defined, measured, and controlled using a proprietary command-and-control toolset: Applied Proteomics' Workflow Management System (WMS). More than a simple LIMS, the WMS not only records experimental details, it allows for real-time feedback and process modification to ensure that the minimal noise possible is introduced into any given experimental workflow and analysis. In effect, the WMS allows Applied Proteomics to constantly search for and improve on the key factors that determine good data.
This video clip demonstrates the power of Applied Proteomics' Workflow Management System at helping to keep track of the huge number of processing steps required to prepare a proteomic sample for LCMS measurement. The video starts with a zoomed in view of the sample processing graph where the highlighted green box refers to the LCMS measurement of the proteomic sample after preparation. At this level, just a few of the upstream processing steps, reagents, and pieces of instrumentation that enabled the final LCMS measurement are visible, represented by the other boxes. The dependencies between these steps are shown by the arrows. The video then zooms out to show the entire processing graph, illustrating the complexity of the sample preparation process. Finally, the video zooms into a centrifugation step in the middle of the process demonstrating how easily one can explore the complex processing graph using Applied Proteomics' touch-based software.