San Francisco, CA, Oct. 29, 2018 (GLOBE NEWSWIRE) -- 3Scan, Inc. (3Scan), the world’s leading 3D tissue imaging company has been awarded a Phase I Small Business Innovation Research (SBIR) grant from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). This grant (R43DK120281) will fund detailed exploration of kidney anatomy in an effort to better understand renal function and disease.
3Scan aims to combine automation, workflow innovation, and microscopy to transform formerly laborious pathology processes into robust and reproducible data. Leveraging a new and proprietary imaging platform, 3Scan will study renal glomeruli. These microscopic 3D structures are the critical components of normal functioning kidneys and are frequently implicated in chronic kidney disease. 3Scan's technology produces 3D reconstructions of hundreds of serial sections at single-cell resolution while allowing on-demand access to each serial section. This will provide researchers with unprecedented detail of how cells maintain the various complicated structures that are implicated in kidney disease. It will also equip 3Scan to further interrogate samples using molecular analysis such as genome and RNA transcript sequencing.
“We're excited for this chance to apply our expertise in automation engineering, histotechnology, and computer vision to such an important and immediate challenge.” - Christopher Rhodes, Principal Investigator, 3Scan
“Kidney disease is an enormous problem in the United States. It is notoriously difficult to study, and this slows down research that could improve detection and treatment.” said Christopher Rhodes, Principal Investigator. “We're excited for this chance to apply our expertise in automation engineering, histotechnology, and computer vision to such an important and immediate challenge.”
This research project, “Automated sectioning, imaging, and extraction of renal glomeruli for single-cell analysis”, will be supported by the National Institute Of Diabetes And Digestive And Kidney Diseases of the National Institutes of Health under Award Number R43DK120281. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes
3Scan combines automation, machine learning and computer vision to extract spatial data from tissue samples to create a 3D understanding of biology. We were founded on the belief that if we could reinvent and automat the histology workflow, it would lead to medical innovation and improve clinical outcomes. Our diverse group of talented engineers and scientists work to revolutionize the histology workflow through novel tools and systems that aid in decision support. The results are detailed 3D representations of anatomical structures, as well as quantitative analysis in the emerging field of volumetric pathology. www.3Scan.com