Efficient Scouting of Chiral Separation Conditions Using LabSolutions MD
Applications | 2023 | ShimadzuInstrumentation
Supercritical fluid chromatography (SFC) enables rapid chiral separations with lower viscosity and higher diffusivity than liquid chromatography, reducing analysis time and organic solvent consumption and thus lowering environmental and operational costs.
This study aimed to streamline method development for the chiral separation of three model analytes—chlormezanone (neutral), flurbiprofen (acidic), and disopyramide (basic)—by combining the Nexera UC chiral screening system with LabSolutions MD software to automate and accelerate the optimization of stationary phases, mobile phase modifiers, and additives.
A total of 42 analytical conditions were screened by pairing six CHIRALPAK columns (IA-3 to IF-3) with seven modifiers (methanol, acetonitrile, ethanol, 2-propanol, acetone, 0.1% formic acid in methanol, 0.1% ammonium formate in methanol).
Key analytical parameters included a CO2-based mobile phase A, modifier-based mobile phase B, flow rate of 3.0 mL/min, temperature at 40°C, backpressure of 10 MPa, and gradient elution from 20% to 40% modifier and back.
LabSolutions MD generated and executed the screening schedule, automatically collected chromatograms, and ranked conditions based on a composite score combining resolution and peak count.
The optimal separation for chlormezanone was achieved using methanol as a modifier on the CHIRALPAK IC-3 column, as identified by the highest software score.
Flurbiprofen exhibited good peak shapes without additional additives owing to the inherently slightly acidic CO2 mobile phase, while acidic additives further fine-tuned separations when needed.
Disopyramide required basic additives (ammonium formate) to prevent peak tailing by masking secondary interactions, leading to improved resolution and peak symmetry.
The automated workflow significantly reduces manual intervention and expertise requirements for scouting chiral separations, enabling rapid identification of optimal conditions.
Lower consumption of organic solvents and the use of CO2 reduce operational costs and environmental impact.
The approach can be extended to preparative SFC to accelerate chiral purification in pharmaceutical development.
Integration of machine learning to predict optimal column-modifier-additive combinations without extensive screening.
Expansion of green chemistry by testing novel biodegradable or less toxic modifiers and additives.
Development of high-throughput preparative SFC platforms for scalable chiral purification.
The combination of the Nexera UC chiral screening system and LabSolutions MD software delivers a powerful, automated approach for efficient method development of chiral separations, offering time savings, cost reductions, and improved data consistency compared to manual HPLC scouting workflows.
SFC, Software
IndustriesOther
ManufacturerShimadzu
Summary
Significance of the Topic
Supercritical fluid chromatography (SFC) enables rapid chiral separations with lower viscosity and higher diffusivity than liquid chromatography, reducing analysis time and organic solvent consumption and thus lowering environmental and operational costs.
Objectives and Study Overview
This study aimed to streamline method development for the chiral separation of three model analytes—chlormezanone (neutral), flurbiprofen (acidic), and disopyramide (basic)—by combining the Nexera UC chiral screening system with LabSolutions MD software to automate and accelerate the optimization of stationary phases, mobile phase modifiers, and additives.
Methodology
A total of 42 analytical conditions were screened by pairing six CHIRALPAK columns (IA-3 to IF-3) with seven modifiers (methanol, acetonitrile, ethanol, 2-propanol, acetone, 0.1% formic acid in methanol, 0.1% ammonium formate in methanol).
Key analytical parameters included a CO2-based mobile phase A, modifier-based mobile phase B, flow rate of 3.0 mL/min, temperature at 40°C, backpressure of 10 MPa, and gradient elution from 20% to 40% modifier and back.
LabSolutions MD generated and executed the screening schedule, automatically collected chromatograms, and ranked conditions based on a composite score combining resolution and peak count.
Instrumentation Used
- Nexera UC Chiral Screening System with solvent and column switching valves
- CHIRALPAK® IA-3, IB-3, IC-3, ID-3, IE-3, IF-3 columns (100 mm × 3.0 mm, 3 µm)
- Shimadzu LabSolutions MD software for method development
- PDA detector monitoring at 220 nm, 245 nm, and 260 nm
Main Results and Discussion
The optimal separation for chlormezanone was achieved using methanol as a modifier on the CHIRALPAK IC-3 column, as identified by the highest software score.
Flurbiprofen exhibited good peak shapes without additional additives owing to the inherently slightly acidic CO2 mobile phase, while acidic additives further fine-tuned separations when needed.
Disopyramide required basic additives (ammonium formate) to prevent peak tailing by masking secondary interactions, leading to improved resolution and peak symmetry.
Benefits and Practical Applications
The automated workflow significantly reduces manual intervention and expertise requirements for scouting chiral separations, enabling rapid identification of optimal conditions.
Lower consumption of organic solvents and the use of CO2 reduce operational costs and environmental impact.
The approach can be extended to preparative SFC to accelerate chiral purification in pharmaceutical development.
Future Trends and Potential Applications
Integration of machine learning to predict optimal column-modifier-additive combinations without extensive screening.
Expansion of green chemistry by testing novel biodegradable or less toxic modifiers and additives.
Development of high-throughput preparative SFC platforms for scalable chiral purification.
Conclusion
The combination of the Nexera UC chiral screening system and LabSolutions MD software delivers a powerful, automated approach for efficient method development of chiral separations, offering time savings, cost reductions, and improved data consistency compared to manual HPLC scouting workflows.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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