Adjunct Associate Professor
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Nathan Dodder, Ph.D., is an analytical chemist specializing in applications related to environmental and public health. He is a Research Scientist at the San Diego State University Research Foundation, and works in the SDSU GSPH Environmental Health Laboratory. His expertise includes: 1) analytical method development for the quantification of contaminants, metabolites, and protein biomarkers by chromatography/mass spectrometry; 2) non-targeted mass spectrometry for the identification of unexpected environmental contaminants; 3) environmental survey design to assess the occurrence and fate of contaminants in abiotic and biotic matrices; 4) implementation of quality assurance / quality control procedures for chemical analyses; and 5) scientific software development, including tools for mass spectral interpretation and mass spectral libraries, automated quality control validation, and data analysis and visualization.
Prior research includes:
- Establishment of non-targeted mass spectrometry as a viable method for discovering unknown contaminants in the environment.
- Exploration of the occurrence and fate of polybrominated diphenyl ether (PBDE) flame retardants in the environment. This work was part of the initial research that lead to the eventual restrictions on commercial PBDE production and use.
- Management of quality assurance/quality control and data analysis components of large-scale inter-agency environmental contaminant monitoring surveys.
- Development of mass spectrometry-based reference analytical methods for the standardization of clinical metabolite biomarkers.
- Establishment of liquid chromatography/multiple-reaction-monitoring mass spectrometry as a method for protein biomarker quantification.
- Development of custom software for environmental and proteomics projects. This software is used to 1) set up quantitative multiple-reaction-monitoring methods for protein biomarkers, 2) to organize and share mass spectral libraries of novel environmental contaminants, and 3) perform statistical analyses in a documented and reproducible manner.