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Accelerating Gene Therapy and Editing with Advanced MS-Based Data Analysis for Nonstandard and Hybrid Nucleotide Sequences

Accelerating Gene Therapy and Editing with Advanced MS-Based Data Analysis for Nonstandard and Hybrid Nucleotide Sequences
通过基于 MS 的高级数据分析加速非标准和混合核苷酸序列的基因治疗和编辑
批准号:
10699241
负责人:
George Hall Johnson
金额:
$86.06万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-05 至 2025-06-30

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PROJECT SUMMARY / ABSTRACT Title: Accelerating Gene Therapy and Editing with Advanced MS-Based Data Analysis for Nonstandard and Hybrid Nucleotide Sequences This project seeks to improve reliability and speed up the development of life-saving and life-enhancing oligonucleotide-based therapeutics and magnify the positive impact of biomedical research and education worldwide, leading to a quantum leap in our understanding of the molecular and cellular pathways and mechanisms involved in healthy and diseased biological systems. Direct sequencing via high-resolution mass spectrometry is an essential assay in the development and QA/ manufacturing of these therapeutics but manual intervention in the data analysis pipeline due to inadequate software has caused a bottleneck in the process of getting these life-saving therapeutics to those in need. Similarly, in-depth characterization of RNA and their modifications needed for improving biomarker identification is hindered in the RNA research community. To address these challenges, semi-automated direct sequencing of oligonucleotides by mass spectrometry will be implemented and delivered on MassMatrix’s high-throughput, enterprise cloud platform (mmCloud). Enhancements to MassMatrix’s oligonucleotide sequencing engine will be made for characterizing nonstandard, hybrid and conjugate oligonucleotides. A unified data repository on mmCloud will enable assay comparisons, knowledge capture and management, and collaboration within and across research teams. Together, these aims are expected to improve the reliability and accuracy of results as well as to significantly reduce the oligonucleotide characterization bottleneck for the pharmaceutical industry and the research community. Deeper understanding and better decision making will follow, both having a potentially dramatic positive impact on downstream processes and resource deployment, including improved drug safety, efficacy and availability of life- saving and enhancing therapeutics.
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Accelerating Site-specific Characterization of Protein Therapeutics with Novel Machine Learning Methods
  • 批准号:
    9927740
  • 项目类别:
  • 资助金额:
    $48.53万
  • 财政年份:
    2019
  • 负责人:
    George Hall Johnson
  • 依托单位:
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