SBIR-STTR Award

Classification and Coding of Adverse Drug Reactions
Award last edited on: 7/7/08

Sponsored Program
SBIR
Awarding Agency
NIH : NIGMS
Total Award Amount
$831,468
Award Phase
2
Solicitation Topic Code
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Principal Investigator
James C Ong

Company Information

Belmont Research Inc

84 Sherman Street
Cambridge, MA 02140
   (617) 868-6878
   info@belmont.com
   www.belmont.com
Location: Single
Congr. District: 07
County: Middlesex

Phase I

Contract Number: 1R43GM050591-01A1
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
1995
Phase I Amount
$100,000
We will develop new software tools for recording and classifying free-text descriptions of adverse reactions to new medical therapies. A major challenge is finding ways to accommodate the conflicting requirements of universality of coverage and uniformity of coding. A three-step model is proposed: extraction of linguistic terms, classification into an intermediate language vocabulary, and selection of codes from a codelist. The extraction step applies document retrieval techniques to assist the medical coder in the selection of relevant terms. Term subsets are classified into an intermediate language based upon the Unified Medical Language System (UMLS) Metathesaurus of the National Library of Medicine. Customizable coding modules can then be used to map intermediate language terms into output codes. In collaboration with experts in drug development and thesaurus construction, Phase I will evaluate the utility of this model, with particular focus upon the divergent goals of universality and uniformity. Phase II will produce a full software prototype and will explore integration with new document-retrieval-based approaches for increased automation.National Institute of General Medical Sciences (NIGMS)

Phase II

Contract Number: 2R44GM050591-02
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
1997
(last award dollars: 1998)
Phase II Amount
$731,468

The goal of this research is to develop new software tools for recording and classifying free-text descriptions of adverse reactions to new medical therapies. A major challenge is finding ways to accommodate the conflicting requirements of universality of coverage and uniformity of coding. A three-step model is proposed: extraction of linguistic terms, classification into an intermediate language vocabulary, and selection of codes from a codelist. The extraction step applies document retrieval techniques to assist the medical coder in the selection of relevant terms. Term subsets are classified into an intermediate language based upon the Unified Medical Language System (UMLS) Metathesaurus of the National Library of Medicine. Customizable coding modules can then be used to map intermediate language terms into output codes. In collaboration with experts in drug development and thesaurus construction, Phase I will evaluate the utility of this model, with particular focus upon the divergent goals of universality and uniformity. Phase II will produce a full software prototype and will explore integration with new document-retrieval-based approaches for increased automation. The major anticipated health-related contribution of this research is an enhanced ability to capture and analyze the all-important free-text information related to the safety profile of new therapies. PROPOSED COMMERCIAL APPLICATION: Improved techniques for capturing adverse reaction information in a form suitable for retrieval and analysis will have widespread appeal to organizations engaged in clinical testing of new therapies, including both pharmaceutical companies and academic and Government research centers. The founders of Belmont Research Inc. have a strong track record in the development, commercialization, and distribution of commercial software to support biomedical applications