Introducing Multifactorial Peak Crossover in Analytical and Preparative Chromatography via Computer-Assisted Modeling

Area of Science:

• Analytical Chemistry
• Chromatography
• Pharmaceutical Science

Background:

• Pharmaceutical processes often yield complex mixtures difficult to separate chromatographically.
• Existing methods struggle with coelutions and low purification productivity, necessitating innovative solutions.

Purpose of the Study:

• To introduce a practical technique, multifactorial peak crossover (MPC), for resolving challenging pharmaceutical separations.
• To enhance chromatographic productivity and enable sensitive impurity detection.

Main Methods:

• Utilized computer-assisted chromatographic modeling to map separation landscapes and identify peak crossover points.
• Generated multifactorial peak crossover diagrams based on column temperature and mobile phase gradients.
• Validated the technique in reversed-phase and ion-exchange chromatography (RPLC and IEC) against experimental data.

Main Results:

• Successfully switched the elution order of target analytes, avoiding coelution spaces.
• Achieved significant productivity increases through shorter cycle times and higher sample loading.
• Demonstrated improved signal-to-noise ratios for ppb-level detection of metabolites and potential genotoxic impurities (PGIs).

Conclusions:

• Multifactorial peak crossover (MPC) chromatography offers a powerful approach to optimize pharmaceutical purification.
• This technique accelerates the development of analytical and preparative separations.
• MPC facilitates efficient isolation, characterization, and quantitation of drug substances and impurities.