Apex SEC columns

Apex SEC columns

  • Reproducible performance < 10% CV
  • Sample volume 0.1-1.0 mL
  • Available with SEC and multi-mode resins
  • Validated in culture, plasma, urine, serum & CSF
  • Compatible with Ascent and Summit

Apex 4B

Apex 6B

Apex MM

Apex MM

Apex mini MM

Apex mini

Apex SEC plates

  • Get the same results as Apex SEC columns in a plate format.
  • Compatible with the Summit instrument
Apex 4B plate

Apex 4B

Apex 6B

Apex SEC Working Principle

Size-exclusion chromatography (SEC) gently separates extracellular vesicles (EVs) by size as a sample passes through a column packed with porous beads. Large particles that cannot enter the pores elute first, while smaller molecules (e.g., secreted proteins) enter the pores and travel a longer path, causing them to elute later. This creates a key trade-off: smaller pore sizes increase EV yield but allow more contaminants to co-elute, whereas larger pores improve purity by retaining more mid-sized impurities but reduce EV recovery.

Apex 6B

Apex 4B

Apex MM for lipoprotein depletion

By combining SEC with a multi-mode (MM) resin that uses hydrophobic interaction and ion-exchange to selectively bind and remove lipoproteins and other soluble contaminants, Apex MM columns enhance EV purity.

Sample TypeAnalysis TypeRecommended Column
Plasma, Serum, or Cell Culture Media (with FBS/Lipoproteins)Single Particle (e.g. NTA/Nanoflow)Apex MM
Targeted Assays (e.g. ELISA/WB/ONI/Leprechaun)Apex 4B
Untargeted Assays (e.g. Proteomics)Apex MM
Cell Culture Media (Serum-free Media)Most applicationsApex 6B
CSF
Urine

How do I apply Apex SEC columns to my research?

Quickly identify the optimal SEC column for your workflow. This tool guides selection based on sample type and downstream analysis, helping you choose from Apex MM, Apex 4B, and Apex 6B columns. Built with expert input, the table distills technical guidance into an easy-to-use reference.

Integration note: Apex SEC columns work with the Ascent instrument for improved reproducibility and throughput. Apex SEC plates are designed for full automation on the Summit instrument.

Apex Column Reproducibility

Pairing the Apex SEC columns with the Ascent and Summit instruments further minimizes variability in EV elution across columns.

EV elution profile of 8 Apex 6B columns, which are optimized for consistent drip speed. CV (EV yield) =4.3%
Column formatColumnPlatemini
Column typeMM / 4B / 6B4B / 6BMM
Input sample volume0.5 - 1.0 mL0.5 - 1.0 mL0.1 - 0.3 mL
Column volume9.0 mL9.0 mL3.0 mL
Column reproducibility10% CV
Sample typesplasma, serum, urine, CSF, cell culture media
Resin types4% or 6 % cross linked agarose beads, cross linked agarose plus multi-mode
Exclusion limit35 nm or 20 nm

Technical information

There are Apex columns for your different sample types and volumes.

Discuss your isolation needs with our scientific team

Latest Apex Application Notes

SEC vs UC
Can SEC be a scalable and more reproducible alternative to ultracentrifugation?

Can SEC be a scalable and more reproducible alternative to ultracentrifugation?

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Advancing Plasma-Derived Extracellular Vesicle Analysis Through High-Purity Isolation and Particle-Specific Quantification

Advancing Plasma-Derived Extracellular Vesicle Analysis Through High-Purity Isolation and Particle-Specific Quantification

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Drip speed matters: Enhance EV isolation reproducibility with Apex columns and validate using the Atlas ELISA

Drip speed matters: Enhance EV isolation reproducibility with Apex columns and validate using the Atlas ELISA

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Optimizing extracellular vesicle isolation: Why Apex MM columns outperform conventional SEC columns for isolating EVs from plasma or serum

Optimizing extracellular vesicle isolation: Why Apex MM columns outperform conventional SEC columns for isolating EVs from plasma or serum

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Why is SEC becoming the most widely used EV isolation technique?

Why is SEC becoming the most widely used EV isolation technique?

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References

This study introduces a plate-based SEC workflow for reproducible, automated, high-throughput extracellular vesicle isolation from plasma and other biofluids.

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The authors adapted size exclusion chromatography (SEC) into a 24-well plate format, where each resin-packed well functions as an individual SEC column. Using EV markers CD63 and CD81, along with albumin as a marker of free-protein contamination, they optimized separation conditions and demonstrated that the workflow can be automated using liquid-handling platforms. This approach addresses a major bottleneck in EV biomarker research by enabling scalable, reproducible EV isolation across large sample sets, with the potential to process hundreds of samples per day for biomarker discovery and diagnostic applications.

This study presents a standardized framework for assessing the efficiency and purity of different extracellular vesicle (EV) isolation techniques.

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The authors utilized ultrasensitive single-molecule array (Simoa) assays to quantify three key EV transmembrane proteins-CD9, CD63, and CD81- while measuring albumin levels as a marker of free protein contamination. By applying this approach to plasma and cerebrospinal fluid (CSF), they systematically compared commonly used isolation methods, including ultracentrifugation, precipitation, and size exclusion chromatography (SEC). The results highlight SEC as a superior method for maintaining both yield and purity, particularly when optimized with custom column parameters. This study provides a valuable, reproducible strategy for improving EV isolation, aiding biomarker discovery and translational research in EV-based diagnostics.

This study presents an advanced method for isolating extracellular vesicles (EVs) from plasma by minimizing contamination from free proteins and lipoproteins, which traditionally complicate EV purification.

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The researchers developed a digital ELISA assay targeting ApoB-100, a key lipoprotein marker, and integrated it with existing assays for albumin and EV-associated tetraspanins. They systematically evaluated various size exclusion chromatography (SEC) resins and developed a novel approach, Tri-Mode Chromatography (TMC), to enhance EV purity while maintaining yield. The study highlights the advantages of TMC in reducing co-isolated contaminants and improving the reliability of EV-based biomarker discovery, particularly for proteomics applications.

This study addresses the challenge of measuring α-synuclein, a key protein associated with Parkinson’s disease (PD), within extracellular vesicles (EVs) isolated from plasma.

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Given the difficulty of distinguishing EV-associated proteins from free plasma proteins, the researchers developed a method combining optimized size-exclusion chromatography (SEC) for EV isolation with a protease protection assay and ultrasensitive digital ELISA (Simoa) measurements. Their analysis revealed that only a small fraction of total plasma α-synuclein is contained within EVs, but its phosphorylated form (pSer129), a marker of PD pathology, is enriched within EVs compared to free plasma protein. Applying this method to patient samples, they observed subtle but significant differences in EV α-synuclein and pSer129 levels between PD, Lewy body dementia (LBD), and control groups. This work establishes a robust framework for studying EV-contained neurodegenerative biomarkers and highlights the potential of EV-based diagnostics for neurodegenerative diseases.

This study presents a systematic approach for identifying neuron-derived extracellular vesicle (EV) markers, facilitating the selective isolation of neuron-specific EVs from cerebrospinal fluid (CSF) and plasma.

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Researchers developed a framework that integrates gene expression data with EV proteomics to identify transmembrane proteins unique to neurons. They optimized high-purity EV isolation by combining multiple purification techniques, including size exclusion chromatography (SEC), density gradient centrifugation (DGC), and Mixed Mode Resin (MMR) Slurry, to effectively remove free proteins and lipoprotein contaminants while preserving EV integrity. Through proteomic analysis, they identified NRXN3 as a robust neuron-specific EV marker and validated its presence using ultrasensitive immunoassays. By optimizing immuno-isolation protocols, the study provides a foundation for isolating neuron-derived EVs, enabling their use in biomarker discovery for neurological diseases. This methodology offers a scalable strategy for isolating cell type-specific EVs, expanding potential applications in liquid biopsy and neurodegenerative disease diagnostics.