SBIR Phase I: Computational platform to infer putative causative pathways of pathology using spatial omics data

Sygnamap, Inc., San Antonio TX

Investigators

Abstract

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to improve clinical outcomes and quality of life for kidney disease. This technology will help identify biomarkers and enable new personalized treatments to improve efficacy and reduce harmful side effects. The innovation will leverage new enhancements in visualizing molecules in biological samples and will improve scientific understanding of complex diseases. The proposed project will leverage the power of the emerging field of spatial omics to build a novel computational platform. Multi-omics technology at a spatial level is changing our understanding of complex conditions, such as cancer and metabolic diseases. These technologies are important to better understand heterogeneity of normal organ structure and changes during the development of complex chronic metabolic diseases and cancers. Mass spectrometry-based platforms have led multi-omic spatial applications, but quantifying the output of mass spectrometry imaging remains a challenge. The research objectives are to correlate and optimize localization of molecules with pathologic features and identify key biochemical pathways that drive disease development. The methods will include computational pathology, mass spectrometry imaging, and artificial intelligence/ machine learning approaches. The anticipated technical results will be development of technologies that convert semi-quantitative output to rigorous, quantitative results for identification of pathways driving disease development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.