SBIR/STTR Research Award

Micropublications for Automating Genome Sequence Variant Interpretation from Medical Literature

Award identifier ad4ced0027d22331ccceb89d1a3a0fbe1e955d0f470a1afb55144e4f03dba37cAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$152,946

Program and phase

SBIR · Phase I

Award year

2019

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Genomenon, Inc.
Proposal award date
2019-05-01
Contract end date
2020-04-30
UEI
Z1NLALZ88SE1
Solicitation number
PA18-574
Topic code
172

Research abstract

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

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2017–2021). Reported award amounts total $3,572,109. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Department of Health and Human Services

Agency intelligence

Department of Health and Human Services

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