Genomenon, Inc. — Department of Health and Human Services SBIR Phase I: 172

Description

PROJECT SUMMARY Accurate and efficient interpretation of genomic variants for clinical decision making is predicated on ready access to useful information in the medical literatureThe sheer number of potentially relevant articles that must be examined during this curation process poses a major challenge in ensuring the accuracy and reproducibility of clinical variant interpretation as it is time consuming and the results highly user dependentTo this endwe have developed the Mastermind Genomic Search Enginea commercial database that automatically organizes diseasegene and variant information from the medical literature by systematically indexing millions of scientific articlesIn direct comparison to manually developed databases of genetic variantswe have achieved greater thanconcordance and accurately identified andgtmore variants with an average offold more references demonstrating the effectiveness of our automated approachCurrentlyMastermind is used by overvariant scientists indifferent countries to more quickly curate literature for genetic variants in clinical settingsIn response to feedback from ClinGen curators and othersthe present proposal seeks to create a framework to facilitate literature curation and clinical variant interpretation activities within Mastermind byprioritizing relevant references and external database entries containing content meaningful to variant classification guidelinesassembling this information into amicropublicationtext format with codified data fields including population frequenciescomputational predictionsreference citations and relevant sentence fragments with conclusive contentallowing users to manually reviewalter and augment pre populated entries andproviding a platform to share and continuously update this information with other variant scientists in the Mastermind community and elsewhereDeveloping tools that allow for collaborative curation in real time at the point of interaction with source materiali eindividual articleswill mitigate reproducibility challenges plaguing other large scale crowd sourced projectsIn contrast to genetic variant databases of user submitted classification information and associated datathe present proposal seeks to create enhanced curation tools to fill such variant databases with more accurate and reproducible data and in a way that would promote dramatic scaling of variant curation activities including those undertaken by groups like ClinVarTo test this approachwe will work with industry partners engaged in variant curation activities todetermine the requisite data fieldsintegrate external database informationtest the accuracy and relevance of results and the overall efficacy of the approach using hundreds of manually curated genetic variantsandsolicit and incorporate feedback from our development partners to iterate and refine the software features for the greatest effectWithin the $ B genome sequencing software marketthere is significant commercial potential and scientific merit in bringing more automated techniques of data analysis to large scale genome sequencing variant interpretation as described in this proposalWord countLine countPROJECT NARRATIVE Successful completion of the present project will contribute to the public health mission of the NIH by promoting more widespread adoption of genome sequencing by making the interpretation of genome variant data more accuratereproducible and cost effective in clinical and research laboratoriesThe community of users that can benefit from this work include geneticistsoncologistspathologistsresearchers and patientsTwo sentences