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Tirapelle M, Chia DN, Duanmu F, Besenhard MO, Mazzei L, Sorensen E. In-silico method development and optimization of on-line comprehensive two-dimensional liquid chromatography via a shortcut model. J Chromatogr A 2024; 1721:464818. [PMID: 38564929 DOI: 10.1016/j.chroma.2024.464818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/04/2024]
Abstract
Comprehensive two-dimensional liquid chromatography (LCxLC) represents a valuable alternative to conventional single column, or one-dimensional, liquid chromatography (1D-LC) for resolving multiple components in a complex mixture in a short time. However, developing LCxLC methods with trial-and-error experiments is challenging and time-consuming, which is why the technique is not dominant despite its significant potential. This work presents a novel shortcut model to in-silico predicting retention time and peak width within an RPLCxRPLC separation system (i.e., LCxLC systems that use reversed-phase columns (RPLC) in both separation dimensions). Our computationally effective model uses the hydrophobic-subtraction model (HSM) to predict retention and considers limitations due to the sample volume, undersampling and the maximum pressure drop. The shortcut model is used in a two-step strategy for sample-dependent optimization of RPLCxRPLC separation systems. In the first step, the Kendall's correlation coefficient of all possible combinations of available columns is evaluated, and the best column pair is selected accordingly. In the second step, the optimal values of design variables, flow rate, pH and sample loop volume, are obtained via multi-objective stochastic optimization. The strategy is applied to method development for the separation of 8, 12 and 16 component mixtures. It is shown that the proposed strategy provides an easy way to accelerate method development for full-comprehensive 2D-LC systems as it does not require any experimental campaign and an entire optimization run can take less than two minutes.
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Affiliation(s)
- Monica Tirapelle
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Dian Ning Chia
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Fanyi Duanmu
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Maximilian O Besenhard
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Luca Mazzei
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Eva Sorensen
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
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Manheim J, Singh AN, Aggarwal P, Aldine FN, Haidar Ahmad IA. An improved workflow for the development of MS-compatible liquid chromatography assay purity and purification methods by using automated LC Screening instrumentation and in silico modeling. Anal Bioanal Chem 2024; 416:1269-1279. [PMID: 38225399 DOI: 10.1007/s00216-023-05118-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024]
Abstract
The development of liquid chromatography UV and mass spectrometry (LC-UV-MS) assays in pharmaceutical analysis is pivotal to improve quality control by providing critical information about drug purity, stability, and presence and identity of byproducts and impurities. Analytical method development of these assays is time-consuming, which often causes it to become a bottle neck in drug development and poses a challenge for process chemists to quickly improve the chemistry. In this study, a systematic and efficient workflow was designed to develop purity assay and purification methods for a wide range of compounds including peptides, proteins, and small molecules with MS-compatible mobile phases (MP) by using automated LC screening instrumentation and in silico modeling tools. Initial LC MPs and chromatography column screening experiments enabled quick identification of conditions which provided the best resolution in the vicinity of the target compounds, which is further optimized using computer-assisted modeling (LC Simulator from ACD/Labs). The experimental retention times were in good agreement with the predicted retention times from LC Simulator (ΔtR < 7%). This workflow presents a practical workflow to significantly expedite the time needed to develop optimized LC-UV-MS methods, allowing for a facile, automatic method optimization and reducing the amount of manual work involved in developing new methods during drug development.
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Affiliation(s)
- Jeremy Manheim
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA.
| | - Andrew N Singh
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA
| | - Pankaj Aggarwal
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA
| | - Fatima Naser Aldine
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA
| | - Imad A Haidar Ahmad
- Analytical Research and Development, MRL, Merck & Co., Inc., Rahway, NJ, 07065, USA
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Tirapelle M, Besenhard MO, Mazzei L, Zhou J, Hartzell SA, Sorensen E. Predicting sample injection profiles in liquid chromatography: A modelling approach based on residence time distributions. J Chromatogr A 2023; 1708:464363. [PMID: 37729739 DOI: 10.1016/j.chroma.2023.464363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/15/2023] [Accepted: 09/04/2023] [Indexed: 09/22/2023]
Abstract
The pharmaceutical and bio-pharmaceutical industries rely on simulations of liquid chromatographic processes for method development and to reduce experimental cost. The use of incorrect injection profiles as inlet boundary condition for these simulations may, however, lead to inaccurate results. This study presents a novel modelling approach for accurate prediction of injection profiles for liquid chromatographic columns. The model uses the residence time distribution theory and accounts for the residence time of the sample through the injection loop, connecting tubes and heat exchangers that exist upstream of the actual chromatographic column, between the injection point and the column inlet. To validate the model, we compare simulation results with experimental injection profiles taken from the literature for 20 operating conditions. The average errors in the predictions of the mean and variance of the injection profiles result to be 8.98% and 8.52%, respectively. The model, which is based on fundamental equations and actual hardware details, accurately predicts the injection profile for a range of sample volumes and sample loop-filling levels without the need of calibration. The proposed modelling approach can help to improve the quality of in-silico simulation and optimization for analytical chromatography.
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Affiliation(s)
- Monica Tirapelle
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK.
| | - Maximilian O Besenhard
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Luca Mazzei
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
| | - Jinsheng Zhou
- Eli Lilly and Company, 893 Delaware St, Indianapolis, 46225, USA
| | - Scott A Hartzell
- Eli Lilly and Company, 893 Delaware St, Indianapolis, 46225, USA
| | - Eva Sorensen
- Department of Chemical Engineering, University College London, Torrington Place, London, WC1E 7JE, UK
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Lucas Tenório CJ, Assunção Ferreira MR, Lira Soares LA. Recent advances on preparative LC approaches for polyphenol separation and purification: Their sources and main activities. Trends Food Sci Technol 2022. [DOI: 10.1016/j.tifs.2022.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Júnior JVC, Muniz VM, de Almeida VCR, de Souza FS, Aragão CFS. An HPLC method for simultaneous quantification of metformin and ferulic acid in solid dosage forms. J Sep Sci 2022; 45:3866-3873. [PMID: 36057131 DOI: 10.1002/jssc.202200373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 08/17/2022] [Accepted: 08/18/2022] [Indexed: 11/08/2022]
Abstract
Metformin is one of the most commonly used drugs in the world for the treatment of type 2 diabetes, while ferulic acid is a molecule that stands out for its antioxidant potential. Recent studies demonstrate hypoglycemic synergy between these molecules. The objective of this study is to develop and validate an analytical methodology by HPLC for the simultaneous quantification of these drugs in pharmaceutical formulations. The method used a octadecylsilane column and a mobile phase composed of 6 mM sodium lauryl sulfate in 15 mM phosphate buffer:acetonitrile (65:35). Ferulic acid and metformin were monitored at 232 nm, with mobile phase flow rate at 1 mL/min and oven temperature at 40°C. The method was linear in the range of 5 to 25 μg/mL for both molecules. In the presence of degradation products satisfactory selectivity were achieved. Accuracy values were close to 100% and standard deviations in precision were less than 2%. In the robustness evaluation, the proposed variations did not interfere with the quantification. Therefore, it is concluded that the present method can be safely applied to the quality control of ferulic acid and metformin raw materials, as well as when they are combined in pharmaceutical formulations. This article is protected by copyright. All rights reserved.
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Affiliation(s)
| | - Vanessa Morais Muniz
- Pharmaceutical Sciences Department, Paraíba Federal University, João Pessoa, 58051-970, Brasil
| | | | - Fábio Santos de Souza
- Pharmaceutical Sciences Department, Paraíba Federal University, João Pessoa, 58051-970, Brasil
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Clarke C, Kontoravdi C. Editorial overview: Mechanistic and data-driven modelling of biopharmaceutical manufacturing processes. Curr Opin Chem Eng 2022. [DOI: 10.1016/j.coche.2022.100844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Liapikos T, Zisi C, Kodra D, Kademoglou K, Diamantidou D, Begou O, Pappa-Louisi A, Theodoridis G. Quantitative Structure Retention Relationship (QSRR) Modelling for Analytes’ Retention Prediction in LC-HRMS by Applying Different Machine Learning Algorithms and Evaluating Their Performance. J Chromatogr B Analyt Technol Biomed Life Sci 2022; 1191:123132. [DOI: 10.1016/j.jchromb.2022.123132] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 01/12/2022] [Accepted: 01/16/2022] [Indexed: 12/26/2022]
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