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Webinar

Introducing a New Technique to Enable Chromatographic Separation Using Computer-assisted Modelling

November 17, 2020

Multicomponent mixtures from pharmaceutical processes are difficult to resolve. How do we better address challenging coelutions?

Imad Haidar Ahmad and colleagues at Merck present multifactorial peak crossover (MPC) – a new technique to quickly isolate peaks of interest. Using computer-assisted chromatographic modelling, the separation landscape is mapped and conditions that change peak-elution orders are found. Peaks of interest can be quickly shifted to convenient areas of the chromatogram, dramatically reducing the time spent to develop productive separations.

Join us to learn how Imad and colleagues:

  • Map the separation landscape with computer-assisted modelling
  • Identify areas of peak-order crossover
  • Improve signal-to-noise ratios and detect low-level components using MPC

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Modern pharmaceutical processes can often lead to multicomponent mixtures of closely related species that are difficult to resolve chromatographically, even worse in preparative scale settings. Despite recent improvements in column technology and instrumentation, there remains an urgent need for creating innovative approaches that address challenging coelutions of a critical pair and lack of chromatographic productivity of purification methods.

Computer-assisted modeling using ACD/LC Simulator software has been introduced in our labs as an initial analytical framework to isolation and purification workflows enabling rapid increase of scale-up productivity of target pharmaceuticals in multicomponent mixtures.

Introducing multifactorial peak crossover (MPC) to enable separation in analytical and preparative chromatography via computer-assisted modeling

Introducing multifactorial peak crossover (MPC) to enable separation in analytical and preparative chromatography via computer-assisted modeling (ACD/LC Simulator)

Imad A. Haidar Ahmad and Erik L. Regalado

Modern pharmaceutical processes can often lead to multicomponent mixtures of closely related species that are difficult to resolve chromatographically, even worst in preparative scale settings. Despite recent improvements in column technology and instrumentation, there remains an urgent need for creating innovative approaches that address challenging coelutions of a critical pair and lack of chromatographic productivity of purification methods. Computer-assisted modeling using ACD/LC Simulator software has been introduced in our labs as an initial analytical framework to isolation and purification workflows enabling rapid increase of scale-up productivity of target pharmaceuticals in multicomponent mixtures. This allows to achieve dramatic increase in productivity while minimizing solvent consumption and hazardous waste. Herein, we overcome these challenges by introducing a simple and practical technique named multifactorial peak crossover (MPC) via computer-assisted chromatographic modeling. The approach outlined here focuses on mapping the separation landscape of pharmaceutical mixtures to quickly identify spaces of peak coelution crossings which enables us to conveniently switch the elution order of target analytes. Diverse examples of peak crossover diagrams as a function of column temperature, mobile phase gradient or a multifactorial combination in reversed phase and ion exchange chromatography (RPLC and IEC) modes are generated using ACD/LC Simulator software and corroborated with experimental data match (overall relative standard deviation of retention times below 1%). MPC chromatography dramatically reduces the time spent developing productive analytical and preparative scale separations. In addition, we illustrate how this new MPC concept can be used to gain substantial improvements of signal-to-noise ratio enabling straightforward ppb detection of low-level target components with direct impact in the quantitation of metabolites and potential genotoxic impurities (PGIs). These innovations are of paramount importance in order to facilitate efficient isolation, characterization and quantitation of drug substances in the development of new medicines.1,2

(1) Haidar Ahmad, I. A.; Shchurik, V.; Nowak, T.; Mann, B. F.; Regalado, E. L. Anal. Chem. 2020, 92, 13443-13451.
(2) Bennett, R.; Haidar Ahmad, I. A.; DaSilva, J.; Figus, M.; Hullen, K.; Tsay, F.-R.; Makarov, A. A.; Mann, B. F.; Regalado, E. L. Org. Process Res. Dev. 2019, 23, 2678-2684.

Presenter

Imad Haidar-Ahmad

Imad Haidar-Ahmad is an Associate Principal Scientist at Merck, where he works on method development. He formerly worked at Novartis and received his PhD from Florida State University in 2011.

Host

Charis Lam

Charis Lam is a Marketing Communications Specialist for ACD/Labs, specializing in chromatography and mass-spectrometry products. She holds a degree in Pharmaceutical Chemistry from the University of Toronto.