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Thermo Fisher Scientific Introduces New Low-Flow HPLC Columns for Proteomic Research

µPAC™ Neo HPLC Columns
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Thermo Fisher Scientific is providing proteomics and biopharmaceutical research laboratories with a new line of low-flow HPLC columns that improve separation performance and stability of biologically complex samples.

Using a unique micro-pillar separation structure, the Thermo Scientific μPAC Neo HPLC Columns enable researchers to investigate proteomics samples in greater detail, from accurate identification of peptides to determination of protein quantities, discovery of disease biomarkers and post-translational modifications.

The newest addition to the portfolio is the μPAC Neo low-load trapping column which is ideally suited for the smallest samples sizes in single-cell proteomics separations and features built-in nanoViper connections to the Vanquish Neo UHPLC systems for ease of use and reduced risk of errors. Users of all μPAC Neo columns benefit from excellent column reproducibility, allowing for more reliable data interpretation and confidence in their results.

The full μPAC Neo column portfolio offers:

  • 50 cm μPAC Neo column for routine proteomics
  • 110 cm μPAC Neo column for comprehensive proteomics
  • 50 cm μPAC Neo low-load column for single-cell proteomics
  • μPAC Neo low-load trapping column to support single-cell proteomics separations

μPAC Neo columns are manufactured by micromachined etching of silicon wafers, resulting in highly reproducible separation paths. For proteomics researchers, this provides higher column-to-column consistency and longer column lifetimes compared to packed-bed columns, allowing for more robust development and validation of methods and easier study of larger sample batches.

Key Applications:

Proteomics and biopharmaceutical research


  • Unique column technology that delivers optimal sample coverage and improved protein identification
  • Extra-high resolution separations of highest complexity samples
  • Excellent column reproducibility for more reliable data interpretation
  • Long column lifetimes to reduce the number of column exchanges and increase system uptime