Technology Bundle ID: TAB-2731

Use of Detector Response Curves to Optimize Settings for Mass Spectrometry

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Licensing Contact:
Primary Inventors: 
Brian Gurbaxani (CDC)
Co-Inventors: 
Vincent Emanuele (CDC)
Development Stage: 
Pre-Clinical (in vitro)
Development Status: 

In vitro data available

Institute or Center: 
CDC

This CDC developed optimization technology allows one to characterize the behavior of the coefficient of variation (CV) for a range of mass spectrometer machine settings. Surface-enhanced laser desorption/ionization (SELDI) and matrix-assisted laser desorption/ionization (MALDI) are used for the early detection of numerous diseases, for example cervical cancer . A critical step in the analytical process is the optimization of experiment and machine settings to ensure the best possible reproducibility of results, as measured by the CV. The high cost of this procedure includes man hours spent optimizing the machine, opportunity cost, materials used, and spent biological samples used in the optimization process.

This technology can be used to optimize the CV with the following advantages over conventional methods: 1) no need to use biological samples, 2) fewer materials are consumed in the process, 3) improved CV and thus more reproducible results, 4) fewer man hours required to find ideal machine settings, and 5) potential full-automation of the process of optimizing CV. This idea is beneficial to all scientists and clinicians that use MALDI/SELDI for biomarker discovery and clinical diagnostics. Further, manufacturers of MALDI/SELDI mass spectrometer devices would find incorporation of this technology quite beneficial.

Applications:
  • MALDI/SELDI mass spectrometer calibration improvement
  • Biomarker discovery studies
  • Quality control techniques
  • Automated coefficient of variation (CV) optimization of mass spectrometer devices
Advantages:
  • Lower resource input requirement
  • Increased cost efficiency
  • Simplifies SELDI/MALDI setup, reducing technician man-hours and need for extensive training
  • Improves experimental optimization providing greater reproducibility
  • Potential for automation of CV optimization

Patents

PCT Application PCT/US2011/055376
Filed on 2011-10-07
US Application 13/575,317
Filed on 2012-07-26
US Application 61/390,910
Filed on 2010-10-07

Publications

Emanuele VA 2nd, Gurbaxani BM.
PMID 20942945
Emanuele VA 2nd, et al.
PMID 23152765

Updated

Jan 20, 2014

Data Source: 
tts