GENECENTRIX INC. — Department of Health and Human Services SBIR Phase I: NLM

Description

Project Summary A strong consensus has emerged over the past years in the pharmaceutical industry that the drug target focused drug discovery approach to which the industry has subscribed almost entirely since the s has been a failure Accordingly over the past few years the majority of Randamp D in the drug discovery and development space has been re allocated to support alternative approaches notably phenotypic screening to discover new drugs This shift represents a new and growing business opportunity for new big data science and technology products such as those developed by the applicant organization GeneCentrix In common phenotypic screens a chemical library is first screened against cells e g HeLa cells and a search is then undertaken for the primary molecular target of the most active compound This search known as target deconvolution is challenging and is a rate limiting step in the success of the screen Accordingly new technologies have been developed for target deconvolution Specifically target specific arrays of drug like chemical probes are increasingly being used in phenotypic screens e g Novartis MOA box the NIH s MIPE platform etc GeneCentrix is pioneering the development of an information product that can enhance phenotypic screens that use these target specific arrays Specifically the off targets of the target specific compounds polypharmacology in the array are currently not taken into account in analyzing the results of the phenotypic screen In addition the expression level of drug targets in the cell line used in the phenotype screen is very likely a predictive variable in target deconvolution but is also not taken into account Therefore we propose two aims to adapt our technology for the purpose of re ranking phenotype screen results generation of off target annotation polypharmacologic profiles for all compounds in a standard target specific array integration of the polypharmacologic profile with expression data of the targets and re ranking of targets by this combined score We will then validate the performance of our technology versus standard analysis of screening results for a test set of phenotypic screens an improvement of in sensitivity associated with an equal or greater accuracy as measured by area under the receiver operating curve AUC will be considered sufficient validation to pursue technical and commercial feasibility of the product in a Phase II application Project Narrative Big pharma early drug discovery is moving towards use of phenotypic discovery methods as opposed to target specific methods and towards use of target specific compounds in phenotypic screening Integration of polypharmacologic target affinity data and gene expression data for those targets into the output of phenotypic screens that use target specific compound libraries for target deconvolution will enhance the value of these screens allowing for more accurate deconvolution of the mechanism of action of chemical probes emerging from phenotypic screens This project thus harnesses extensive and diverse big biomedical data and translates it into knowledge of sufficient integrity to be packaged as a viable commercial product