Getting Off to a Good Start - Isocratic method development
Presentations | 2020 | Agilent TechnologiesInstrumentation
Isocratic high-performance liquid chromatography remains a fundamental technique for routine analyses in pharmaceutical, environmental, and food testing laboratories. Its constant mobile phase composition eliminates baseline drift and re-equilibration delays, supporting reproducible and transferable methods across different instruments.
This article outlines a systematic workflow for designing and optimizing isocratic HPLC methods. It covers theoretical foundations of resolution and band broadening, strategies for column and mobile phase selection, practical tips for minimizing extracolumn dispersion, and guidelines for robust method development.
The fundamental resolution equation, Rs =(√N/4)·(α−1)/α·k/(1+k), highlights selectivity as the most influential factor. Increasing plate count, optimizing retention factor, and selecting the appropriate bonded phase all contribute to separation performance. The van Deemter relationship guides the choice of flow velocity to balance longitudinal diffusion and mass transfer effects.
Superficially porous (core-shell) particles deliver higher efficiency at lower backpressure compared to fully porous columns, enabling faster analyses without UHPLC systems. Reducing extracolumn volume via shorter capillaries and smaller detector flow cells can improve plate number by up to 83% for early eluting compounds. Sample solvent strength and injection volume directly affect peak shape; using a diluent weaker than the mobile phase and minimal injection volumes ensures sharp peaks and high sensitivity.
Organic modifier selection influences elution strength and peak shape. Acetonitrile offers a wide UV window and stronger elution, while methanol provides better peak shape for basic compounds. Adjusting mobile phase pH exploits ionization of analytes and silanol groups to fine-tune retention and selectivity. High-pH stable Poroshell HPH columns extend the usable pH range to 11 for basic analytes.
Scouting gradients serve as a rapid first step to estimate optimal isocratic conditions. An empirical equation based on void time and average retention can predict effective isocratic % organic.
Evaluating multiple bonded phases early in development identifies the best selectivity for challenging separations. Polar-embedded Bonus RP columns and phenyl-hexyl chemistries can resolve closely related isomers and positional analogs more effectively than C18 phases alone.
System optimization practices include using Quick Connect fittings to minimize dead volume, employing solvent bottle caps with venting valves for safe solvent handling, and ensuring proper column connections to avoid peak splitting or tailing.
Emerging developments include AI-driven method scouting, further miniaturization into microflow and nanoflow isocratic formats, and new hybrid stationary phases offering tailored multi-mode interactions. Integration with high-resolution mass spectrometry for complex sample matrices and high-pH workflows for basic drug analysis will expand application areas.
A structured approach to isocratic HPLC development—combining scouting gradients, column chemistry screening, mobile phase optimization, and system dispersion control—yields robust and efficient methods adaptable to diverse analytical challenges.
HPLC
IndustriesManufacturerAgilent Technologies
Summary
Significance of the Topic
Isocratic high-performance liquid chromatography remains a fundamental technique for routine analyses in pharmaceutical, environmental, and food testing laboratories. Its constant mobile phase composition eliminates baseline drift and re-equilibration delays, supporting reproducible and transferable methods across different instruments.
Objectives and Article Overview
This article outlines a systematic workflow for designing and optimizing isocratic HPLC methods. It covers theoretical foundations of resolution and band broadening, strategies for column and mobile phase selection, practical tips for minimizing extracolumn dispersion, and guidelines for robust method development.
Methodology and Instrumentation
- Instrumentation: Agilent 1290 Infinity LC System with low-dispersion rack, InfinityLab Poroshell columns, diode array detector, temperature-controlled autosampler and column compartment.
- Column chemistries: Poroshell 120 EC-C18, SB-C18, HPH-C18, Bonus RP, Phenyl-Hexyl, HILIC, and a range of chiral stationary phases.
- Scouting gradient: 5–95% organic over 10 minutes on a 4.6×100 mm column, 0.4 mL/min, low pH buffering.
- Sample variables: solvent strength matched to or weaker than mobile phase, injection volumes from 0.5 to 16 μL to evaluate peak shape and efficiency.
Main Results and Discussion
The fundamental resolution equation, Rs =(√N/4)·(α−1)/α·k/(1+k), highlights selectivity as the most influential factor. Increasing plate count, optimizing retention factor, and selecting the appropriate bonded phase all contribute to separation performance. The van Deemter relationship guides the choice of flow velocity to balance longitudinal diffusion and mass transfer effects.
Superficially porous (core-shell) particles deliver higher efficiency at lower backpressure compared to fully porous columns, enabling faster analyses without UHPLC systems. Reducing extracolumn volume via shorter capillaries and smaller detector flow cells can improve plate number by up to 83% for early eluting compounds. Sample solvent strength and injection volume directly affect peak shape; using a diluent weaker than the mobile phase and minimal injection volumes ensures sharp peaks and high sensitivity.
Organic modifier selection influences elution strength and peak shape. Acetonitrile offers a wide UV window and stronger elution, while methanol provides better peak shape for basic compounds. Adjusting mobile phase pH exploits ionization of analytes and silanol groups to fine-tune retention and selectivity. High-pH stable Poroshell HPH columns extend the usable pH range to 11 for basic analytes.
Scouting gradients serve as a rapid first step to estimate optimal isocratic conditions. An empirical equation based on void time and average retention can predict effective isocratic % organic.
Evaluating multiple bonded phases early in development identifies the best selectivity for challenging separations. Polar-embedded Bonus RP columns and phenyl-hexyl chemistries can resolve closely related isomers and positional analogs more effectively than C18 phases alone.
System optimization practices include using Quick Connect fittings to minimize dead volume, employing solvent bottle caps with venting valves for safe solvent handling, and ensuring proper column connections to avoid peak splitting or tailing.
Benefits and Practical Applications of the Method
- Fast and reproducible QC assays with stable baselines and no re-equilibration delays.
- Methods transferable between HPLC and UHPLC platforms without retention shifts.
- Reduced solvent consumption and waste through isocratic operation.
- Enhanced resolution of structurally similar compounds by exploiting alternative stationary phase selectivity.
Future Trends and Potential Applications
Emerging developments include AI-driven method scouting, further miniaturization into microflow and nanoflow isocratic formats, and new hybrid stationary phases offering tailored multi-mode interactions. Integration with high-resolution mass spectrometry for complex sample matrices and high-pH workflows for basic drug analysis will expand application areas.
Conclusion
A structured approach to isocratic HPLC development—combining scouting gradients, column chemistry screening, mobile phase optimization, and system dispersion control—yields robust and efficient methods adaptable to diverse analytical challenges.
Reference
- Snyder LR, Kirkland JJ, Dolan JW. Introduction to Modern Liquid Chromatography. 3rd ed. John Wiley & Sons; 2010.
- Mack AE, Evans JR, Long WJ. Fast Analysis of Illicit Drug Residues on Currency using Agilent Poroshell 120. Agilent Technologies Application Note 5990-6345EN; 2010.
- Dolan JW. Making the Most of a Gradient Scouting Run. LCGC North America. 2013;31(1).
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