AI-Driven Optimization of HILIC Methods for Enhanced Nucleoside Separation

Importance of the Topic

The hydrophilic interaction liquid chromatography HILIC technique offers high retention and selectivity for polar analytes combined with enhanced sensitivity when coupled to mass spectrometry However adoption remains limited due to complex mobile phase preparation long equilibration times and a steep learning curve Software supported method development addresses these challenges by streamlining gradient selection and improving user confidence in HILIC applications

Objectives and Study Overview

This study demonstrates the use of Shimadzu Method Development software to optimize HILIC conditions for the separation of nucleosides A systematic evaluation of four HILIC column chemistries and multiple mobile phase formulations was performed followed by software driven gradient optimization to enhance resolution and reduce analysis time

Instrumental Setup

• System Nexera X2 Method Scouting System
• Detector PDA detector SPD M40 with detection at 265 nm
• Columns Shim pack Velox HILIC pure silica Shim pack GIS HILIC diol Shim pack GIST Amide carbamoyl Shim pack GIST NH2 amino phase

Methodology

• Analyte mixture Nucleoside standard from Sigma Aldrich
• Mobile phase A acetonitrile Mobile phase B prepared by blending water with formic acid 10 ammonium formate 200 or sodium hydroxide 100 to yield pH 2 3.5 7 and 8
• Scouting stage 42 isocratic runs at water contents of 5 10 and 15 alongside each pH condition
• Ranking based on number of peaks resolution sum and overall evaluation value
• Gradient optimization iterative refinement of initial parameters with model building to propose improved gradients
• Final gradient profile 9 at 0.67 min rising to 28 at 7.22 min then 30 at 7.23 dropping back to 9 at 10.23 to 18.22 min flow rate 0.6 ml min column temperature 40 C injection volume 1 ul

Main Results and Discussion

• Bare silica column delivered the highest peak count and was selected for optimization
• Software driven gradient refinement reduced analysis time by approximately 1.5 minutes compared with manual parameter variation
• Optimized method achieved improved peak resolution and reproducibility

Benefits and Practical Applications

• Accelerates method development by minimizing experimental iterations
• Enhances confidence in applying HILIC for polar compound analysis
• Applicable to pharmaceutical environmental and biochemical laboratories for QA QC and research workflows

Future Trends and Applications

• Integration of artificial intelligence for predictive method suggestions
• Adoption of faster gradient profiling and system miniaturization
• Extension to broader classes of polar and biomolecule analytes
• Cloud based platforms for collaborative method development and data sharing

Conclusion

Shimadzu Method Development software significantly simplifies HILIC method optimization by systematically evaluating column chemistries and mobile phases and by proposing efficient gradient profiles The approach yields faster analysis times improved resolution and supports broader adoption of HILIC techniques in analytical laboratories

References

• Buszewski B Noga S Hydrophilic interaction liquid chromatography HILIC a powerful separation technique Anal Bioanal Chem 2012