Streamlining of Preparative Purification Work by Nexera ASAPrep

Significance of the Topic

Preparative liquid chromatography (prep LC) is essential to remove impurities produced during compound synthesis. Traditional workflows demand expert knowledge and extensive optimization, limiting throughput and reproducibility. The development of an automated scale-up system improves efficiency and consistency in reversed-phase purification operations.

Study Objectives and Overview

This work introduces the Nexera ASAPrep system, designed to streamline preparative purification. Key goals include automatic assessment of sample purification difficulty, generation of optimal preparative conditions, and reduction of manual intervention. The system performance was demonstrated using three model mixtures containing vanillin, indomethacin, and bifonazole with their related impurities.

Methodology and Instrumentation

• Screening Analyses: Two rapid 2-minute HPLC runs under acidic and basic mobile phases using Nexera ASAPrep analytical system and Shim-pack Scepter C18 column (50×3.0 mm, 3 μm). UV-PDA detection (190–800 nm) and ESI/APCI mass spectrometry (m/z 150–1000) supported peak purity assessment.
• Automatic Scale-Up Algorithm: The software evaluates peak separation and spectral purity to assign a difficulty level (green, yellow, red) and recommends the initial preparative gradient.
• Preparative Purification: Nexera ASAPrep preparative system with Shim-pack Scepter C18 column (150×20 mm, 5 μm). Injection volumes scaled 250-fold, using tailored gradients derived from screening results under appropriate acidic (0.1% formic acid) or basic (ammonium hydrogen carbonate) conditions.

Main Results and Discussion

• Automatic Difficulty Assessment: All three mixtures were correctly classified: vanillin and indomethacin under acidic conditions (green judgments) and bifonazole under basic conditions (green judgment). The system highlighted potential co-elution risks and spectral purity issues for more challenging samples.
• Preparative Chromatograms: Scaled-up runs achieved improved resolution of target compounds from impurities compared to analytical screening. The selected mobile phase conditions correlated with compound acidity or basicity, validating the algorithm.
• Workflow Efficiency: Automated conditioning and gradient setup reduced manual method development steps, enabling consistent prep LC runs regardless of operator experience.

Benefits and Practical Applications

• Reduced Dependence on Expert Users: The intuitive interface and auto-conditioning function allow less experienced operators to perform prep LC tasks.
• Increased Throughput: Eliminating separate analytical method optimization accelerates sample processing and decision-making.
• Enhanced Reproducibility: The algorithmic approach standardizes gradient selection and difficulty evaluation, minimizing human error.

Future Trends and Potential Uses

Advancements may include integration of machine learning to refine difficulty predictions, expansion to other chromatographic modes (e.g., normal phase or HILIC), and direct coupling with automated sample preparation. Real-time monitoring and feedback loops could further optimize purification yields and purities across diverse synthetic workflows.

Conclusion

The Nexera ASAPrep system demonstrates a fully automated route from analytical screening to preparative purification in reversed-phase LC. By automatically determining sample difficulty and generating optimized gradients, the platform streamlines workflow, reduces expert intervention, and improves consistency. This approach has broad applications in medicinal chemistry, quality control, and industrial process development.