Celldom, Inc. — Department of Health and Human Services SBIR Phase I: 300

Description

ABSTRACT Cancer patients often relapse because their tumors contain drug resistant cellswhich though initially present at small fractionsbecome enriched during treatment to yield incurable tumorsTraditional approaches to isolate and study drug resistant cells can require months of labor intensive workwhich is both costand timeprohibitive during the early stages of drug developmentSingle cell array technologies are well suited for measuring functional cellular propertieshoweverexisting market offerings cannot achieve the massive scales required to identify rare drug resistant cells that are present at frequencies as low asi edrug resistant cell for everytodrug sensitive cellsAlthough the latest single cell genomic techniques can achieve the required throughputthey do not allow for identification of subclones with functional properties of interesti eresistance to a drugCelldom aims to solve this problem by developing a single cell analysis workflow that combines image based phenotyping and gene expression analysis at scales of up tosingle cells organized in a standard well plate footprintAt these scalesit is possible for drug companies and clinicians to pinpoint better lead candidates with more attractive resistance profiles and provide improved clinical outcomesBuilding on a recently completed Phase I projectin which we demonstrated the phenotyping capabilitiesspecificallythe ability to organize and track single cell clones over multiple daysherewe propose to add RNA seq capabilities to realize a comprehensive `multi omicsandapossingle cell analysis platform with high resolution live cell imagingOur collective workstream is described in the following two specific aimsIn Aimwe will synthesize an array of DNA barcodes inside Celldomandapos s microfluidic chipsshow that the barcodes can capture human AML cell lysatesdemonstrate cDNA synthesisand retrieve molecules for NGSIn Aimwe will capture a mixture of murine NIHTand human AML cells in single cell per trap formatidentify the species of trapped cell with imagingthen demonstrate the scRNA seq workflowSuccessful completion of this Phase I study will de risk our platform by proving the principle that we can conduct both drug resistance testing and genomic analysis at the scale of tens of thousands of single cells per chipIn Phase IIwe will optimize the platform for launchfirst as drug discovery research tool for academic and industrial customersand later as a companion diagnostic for evaluating clinical therapies NARRATIVE Drug resistant cells in a patient tumor are often present at frequencies as low asdrug resistant cell for everytodrug sensitive cellshowever existing technologies are unable to perform the multi parameter measurements needed to identify these rare cells and measure the gene expression pathways enabling their resistanceIn this SBIR proposalwe will develop the first platform that can rapidly identify the rare drug resistant cells through a multi day drug screen and measure the single colony gene expression profiles that enable their resistanceThrough this approachwe will provide our customers with a platform that leads to the development of better drugs and improved clinical outcomes