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SAMPLE PREPARATION; The Achilles Heel of Mass Spectrometry Based Diagnostics II. Project Summary. LC-MS provides superior data in clinical diagnostics relative to immunoassays, but it is slow and costly. As the old saying goes, time is money. The technique must become simpler, faster, and less expensive to displace older, less accurate immunological assay (IA) methods. The focus of this proposal is to make LC-MS analytics more competitive in clinical diagnostics by increasing throughput 10 fold with existing instrumentation. The objective in Phase I was to use analyte sequestering transport particles (ASTPs) to circumvent the above limitations by i) structure specifically sequestering analytes of interest, ii) separating them from non-analytes within a min, ii) rapidly transferring them to an MS, and iv) enabling the MS to identify all analytes of interest in less than 60 sec. This was achieved by preparing 2 megadalton (mDa) ASTPs that sequester analytes at their surface; elevating their effective Mw to 2 mDa and allowing them to be purified by mobile affinity sorbent chromatography (MASC) in 60 sec. Thermal or solvent dissociation was used to recover analytes for ESI-MS or LDTD-MS wells. This proposal has four specific aims. One is to complete manufacturing protocols for antibody and protein A/G based ASTP products that capture, resolve, and transport analytes to MS or fluorescence instruments in research, big pharma, and CRO laboratories. The second is to integrate the above ASTP products into miniature membrane laboratories (MemLabs); producing point-of-collection products that extract plasma from a drop of blood and prepare samples in situ for biomarker detection. The third aim was to evaluate and optimize the release and detection of analytes from ASTPs via LDTD-MS, MALDI-MS, and ESI-MS. The fourth specific aim is to adapt ASTP technology to multiplexed drug testing and the analysis of protein i) primary structure, ii) post-translational modifications, and iii) conformation.
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The PROTEOMETER; A Continuous Upstream Process Monitoring Engine
  • 批准号:
    10208908
  • 项目类别:
  • 资助金额:
    $73.82万
  • 财政年份:
    2020
  • 负责人:
    Jinhee Kim
  • 依托单位:
The PROTEOMETER; A Continuous Upstream Process Monitoring Engine
  • 批准号:
    10005833
  • 项目类别:
  • 资助金额:
    $68.97万
  • 财政年份:
    2020
  • 负责人:
    Jinhee Kim
  • 依托单位:
海外基金