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Simulated Moving Bed (SMB) inline sampling

Technical notes | 2020 | KNAUERInstrumentation
HPLC
Industries
Manufacturer
KNAUER

Summary

Importance of the Topic


The development of Simulated Moving Bed (SMB) chromatography methods is crucial for continuous, high-throughput separations in pharmaceutical and fine-chemical industries. Inline sampling provides real-time concentration data from multiple points in the SMB circuit, facilitating rapid method optimization and improving overall process efficiency.

Objectives and Study Overview


  • Implement an inline sampling valve in a lab-scale SMB system.
  • Optimize the separation of paracetamol and caffeine.
  • Obtain concentration profiles in all four SMB zones to guide method refinement.

Methodology and Instrumentation


An AZURA lab SMB system was configured in a 2:2:2:2 zone arrangement using eight Eurospher II C8 columns (150 × 8 mm, 15 µm). A manual 6-port, 2-position sampling valve with a defined loop was installed before column 1. The system operated with a 0.2 mL/min feed (1 g/L caffeine, 6 g/L paracetamol) and 4 mL/min eluent flow at ambient temperature. After reaching steady state (ten cycles, 18.8 min cycle time), samples were taken mid-switch at 0.5 and 1.5 min intervals.

Main Results and Discussion


Inline sampling revealed zone-specific concentration profiles: zone 1 was enriched in paracetamol, zone 4 concentrated caffeine, while zones 2 and 3 contained mixed streams. The absence of raffinate in zones 1 and 2 and the lack of extract in zone 3 indicate incomplete separation. Enhanced flow rates in zones 2 and 3 or increased feed flow could improve partition efficiency and boost productivity.

Benefits and Practical Applications


  • Minimal sample volume requirements tied to the loop size.
  • Fast, multi-point monitoring within a single cycle.
  • Targeted insights into each SMB zone for method adjustments.
  • Applicable to continuous purification of active pharmaceutical ingredients.

Future Trends and Applications


Integration of automated inline sampling with process control software and real-time detectors (e.g., UV, MS) will enable closed-loop SMB optimization. Scaling to pilot and production levels with advanced analytics will support process intensification and continuous manufacturing strategies.

Conclusion


Inline sampling significantly accelerates SMB method development by delivering detailed, zone-resolved concentration data with minimal sample volume. This approach streamlines optimization steps and can be extended to diverse continuous chromatographic processes.

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