Pinaki Sarder Ph.D
Associate Professor MD-Med
Quantitative Health
University of Florida at Gainesville
Title: Digital Pathology Meets Spatial Omics - II: Data Integration in Scale & Toward Disease Outcome Prediction
Abstract: This talk will revisit our earlier discussion on parallel advancements of two emerging fields in biomedical sciences, computational pathology and spatial-omics. Our group leverages computational image analysis tools and best engineering practices to integrate spatial-omics datasets with associated histology images to draw meaningful conclusions. We work to fundamentally understand cell type and cell state compositions and underlying quantitative morphometric features at multiple scales from transcripts to tissue microanatomy. This work is part of our ongoing efforts within the Human Biomolecular Atlas Program (HuBMAP), a consortium spanning 42 sites, focused on creating an atlas of the human body at the cellular level using spatial technologies. I will next discuss the detection and segmentation of multiple cell types and cell states as well as tissue microanatomy exclusively appreciated on brightfield histology images. Furthermore, I'll explore several use-case studies of these tools including use in chronic kidney disease trajectory prediction, relevant to the NIH Kidney Precision Medicine Project (KPMP) consortium, as well as applications in kidney transplant allograft survival prediction. Additionally, I will demonstrate our cloud-based, open-source distributed software systems (FUSION Functional Unit State IdentificatiON in Whole Slide Images, accessible at http://fusion.hubmapconsortium.org/, and CompRePS Computational Renal Pathology Suite, accessible at https://athena.rc.ufl.edu/). These systems are designed to conduct various computational image analysis tasks related to digital pathology, starting with the analysis of brightfield histology images and extending to the integration of histology with spatial-omics data. We'll conclude by discussing our vision on foundational modeling of chronicity in a data centric fashion via leveraging the strengths of CompRePS and FUSION.
Bio: Pinaki Sarder is currently an associate professor of AI in the Section of Quantitative Health of the Department of Medicine as well as the Associate Director for Imaging in the Intelligent Critical Care Center at the University of Florida (UF). Before joining UF, he was an associate professor in the Departments of Pathology & Anatomical Sciences and Biomedical Engineering at the University at Buffalo (UB), where he was at the center of building the computationally enabled graduate program Computational Cell Biology, Anatomy, and Pathology. Prior to UB, he completed post-doctoral training at Mallinckrodt Institute of Radiology at the Washington University in St. Louis (WUSTL) School of Medicine. He received his B.Tech. degree in electrical engineering from the Indian Institute of Technology, Kanpur, in 2003, and M.Sc. and Ph.D. degrees in electrical engineering from WUSTL, in 2010. Dr. Sarder serves on the editorial board of the Journal of the American Society of Nephrology (JASN), is the Associate Editor of IEEE Journal of Biomedical Health Informatics, and a senior member of IEEE. He serves as research co-lead for ASN’s Augmented Intelligence and Digital Health Task Force. He was a recipient of the UB’s Exceptional Scholars – Young Investigator Award in 2018. His research interests include computational fusion of diverse spatial omics data while focusing on diabetic kidney disease. Dr. Sarder’s research is funded by National Institutes of Health, Kidney Precision Medicine Project (KPMP) Consortium, and Human Biomolecular Atlas Project (HubMAP) Consortium.