SBIR-STTR Award

Serendipitous Search System Using Lateral Analogy to Match Potential Solutions to Unmet Needs:Feasibility Study Based on Screening Approved Drugs for Repurposing
Award last edited on: 2/20/2023

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$1,490,747
Award Phase
2
Solicitation Topic Code
EI
Principal Investigator
Brian Sager

Company Information

Leonardo Innovations Inc

101 Jefferson Drive
Menlo Park, CA 94025
   (650) 224-4508
   N/A
   www.da-vinci-inventions.com~www.omnity.io
Location: Single
Congr. District: 15
County: San Mateo

Phase I

Contract Number: 1248901
Start Date: 1/1/2013    Completed: 12/31/2013
Phase I year
2013
Phase I Amount
$180,000
This Small Business Innovation Research (SBIR) Phase I project is focused on the development of novel methods for ideation and innovation through the discovery of lateral connections in otherwise unconnected knowledge networks. In many fields of human knowledge and activity, a common feature is that information content is expanding at such a rate that finding relevant results to searches for solutions is becoming increasingly difficult. A further problem is that even the high quality material is expanding at such a rate that most disciplines are rapidly forming sub-disciplines. As fields continue to both expand both at the top levels in terms of overall amount of knowledge, and to expand at the more granular levels by fragmentation into ever more numerous subfields, each of which may develop its own journals, conferences and even terminology, impenetrable to the outsider. It's becoming impossible to stay current. Yet much of creativity occurs, and indeed a great many of the world?s great inventions have occurred, precisely at the intersections between different fields. The central objective of this Phase I project will be to determine the utility of a parsable ontology for supporting ideation and innovation by connecting diverse knowledge domains. The broader impact/commercial potential of this project spans multiple fields and markets, including but not limited to pharmaceuticals, medical devices, materials science, semiconductor devices, chemical processing, legal discovery, patent analyses, and financial analytics. In each of these fields, there is often an increase in 'silo-ing' of different knowledge domains, with the development of access and language barriers in between them, presenting clear challenges to academia and industry. As this situation worsens, there is need of ever better ways to organize, translate and present information to users, and to find solutions to users' problems (their 'unmet needs'). What is needed, and not yet offered by any competitor, is an exploration system giving searchers a strong serendipitous element with a maximum likelihood of results having come from a diverse, unexpected, and potentially provocative source. This will break down silos by providing a rapid, relevant means for knowledge-transfer between different disciplines to facilitate the ready spread of awareness of a potential solution from one field to another, fostering interdisciplinary innovation. The initial customer focus will be on particular corporate clients with a heavy investment in R&D activities and a high probability of internal silo-ing of knowledge, such as pharmaceutical companies

Phase II

Contract Number: 1430780
Start Date: 12/1/2014    Completed: 11/30/2016
Phase II year
2015
(last award dollars: 2018)
Phase II Amount
$1,310,747

The broader impact/commercial potential of this project is to accelerate the paceof research and development to enable more rapid deployment of technologiesinto commercial / industrial contexts. In many fields, information is expanding atsuch an exponential rate that finding relevant results to technical knowledgesearches is increasingly difficult. Further, content is expanding so fast that mostfields are rapidly forming sub-disciplines, leading to the ?silo-ing? of differentknowledge sub-domains, a clear challenge to both academia and industry. Weneed ever better ways to organize and present information to users. There aredisadvantages of the current search engines, mostly relating to excessivesimilarity in search results. Further, while these engines present informationrelating to a known search target, they are less effective at presentingunexpected results for information that a user has never heard of but that wouldbe useful. What is therefore needed is an exploration system giving searchers astrong serendipitous element with a maximum likelihood of results from diverse,unexpected, and potentially provocative sources. This will break down silos byproviding a rapid, relevant means for knowledge-transfer between differentdisciplines, fostering interdisciplinary innovation. This system has been designedto provide a means for systematic, automated discovery.This Small Business Innovation Research (SBIR) Phase 2 project is focused onoptimizing and scaling a serendipitous document search system for repurposingtechnologies by analogy into lateral fields. Both by sub-parsing discrete contentinto ontologically separable entities, such as capability, characteristic, andcomposition, and by comparatively assessing certain of these attributes betweensuch entities, the attribute relatedness of these entities can be used to drive theirself-assembly into related attribute networks. This approach provides asignificant value proposition for drug repurposing, which is the current focus ofthis project. To scale the pair-wise comparison and network assembly of millionsof documents, a map-reduce based text-processing framework will be developedso that massively parallel computations can be carried out in a time- and costefficientmanner. A distributed search engine technology will be deployed toenable rapid querying of the emerging document relationship network. A series ofmachine learning algorithms will then be used to determine potentially hiddenstructural architectural features within the document relationship network.Machine learning will elucidate the nature of the relationships in drug networksthrough analyses of inter-node relationships and sub-graph motifs (termed?innovation motifs?). Documents including U.S. patents and scientific papers willbe processed in the system.