SBIR Phase I: SAAS-based Mass Spectrometry Data Processing for Antibody Therapeutics for COVID-19 and Other Diseases

  • Funded by National Science Foundation (NSF)
  • Total publications:0 publications

Grant number: 2029972

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2020
    2021
  • Known Financial Commitments (USD)

    $256,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Robert Smith
  • Research Location

    United States of America
  • Lead Research Institution

    Prime Labs Inc
  • Research Priority Alignment

    N/A
  • Research Category

    Therapeutics research, development and implementation

  • Research Subcategory

    Pre-clinical studies

  • Special Interest Tags

    Innovation

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be the increased likelihood of effective and affordable new antibody therapy development for COVID-19 and other diseases. Current software is time-intensive to advance antibody therapy development. The proposed software will provide rapid, accurate information about the function and safety of putative therapies, enabling faster deployment.

This SBIR Phase I project will develop novel algorithms and interfaces for enhancing antibody analysis via mass spectrometry. The research will expand capacity and accuracy for detecting, characterizing, and quantifying antibody glycans, disulfide bonds, and impurities by capturing information from experimental metadata, sample preparation, instrument parameters, and instrument output and creating models for prediction of possible structures supported by the data. The proposed project aims to increase the quantity of antibody subunits that can be accurately detected and quantified. This process will take tenfold less time than current methods through the use of novel algorithms, customizable automatable processes, and integrated reporting tools.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.