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Bos TS, Boelrijk J, Molenaar SRA, van ’t Veer B, Niezen LE, van Herwerden D, Samanipour S, Stoll DR, Forré P, Ensing B, Somsen GW, Pirok BWJ. Chemometric Strategies for Fully Automated Interpretive Method Development in Liquid Chromatography. Anal Chem 2022; 94:16060-16068. [DOI: 10.1021/acs.analchem.2c03160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Tijmen S. Bos
- Division of Bioanalytical Chemistry, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HVAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Jim Boelrijk
- AMLab, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
- AI4Science Lab, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Stef R. A. Molenaar
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Brian van ’t Veer
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Leon E. Niezen
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Denice van Herwerden
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Saer Samanipour
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Dwight R. Stoll
- Department of Chemistry, Gustavus Adolphus College, Saint Peter, 56082Minnesota, United States
| | - Patrick Forré
- AMLab, Informatics Institute, University of Amsterdam, Science Park 904, 1098 XHAmsterdam, The Netherlands
- AI4Science Lab, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Bernd Ensing
- AI4Science Lab, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Computational Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Govert W. Somsen
- Division of Bioanalytical Chemistry, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1085, 1081HVAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
| | - Bob W. J. Pirok
- Analytical Chemistry Group, Van’t Hoff Institute for Molecular Sciences, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Science Park 904, 1098XHAmsterdam, The Netherlands
- AI4Science Lab, University of Amsterdam, Science Park 904, 1098XHAmsterdam, The Netherlands
- Department of Chemistry, Gustavus Adolphus College, Saint Peter, 56082Minnesota, United States
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Hybrid data-intelligence algorithms for the simulation of thymoquinone in HPLC method development. JOURNAL OF THE IRANIAN CHEMICAL SOCIETY 2021. [DOI: 10.1007/s13738-020-02124-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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3
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Stojanović J, Krmar J, Protić A, Svrkota B, Đajić N, Otašević B. Experimental design in HPLC separation of pharmaceuticals. ARHIV ZA FARMACIJU 2021. [DOI: 10.5937/arhfarm71-32480] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Design of Experiments (DoE) is an indispensable tool in contemporary drug analysis as it simultaneously balances a number of chromatographic parameters to ensure optimal separation in High Pressure Liquid Chromatography (HPLC). This manuscript briefly outlines the theoretical background of the DOE and provides step-by-step instruction for its implementation in HPLC pharmaceutical practice. It particularly discusses the classification of various design types and their possibilities to rationalize the different stages of HPLC method development workflow, such as the selection of the most influential factors, factors optimization and assessment of the method robustness. Additionally, the application of the DOE-based Analytical Quality by Design (AQbD) concept in the LC method development has been summarized. Recent achievements in the use of DOE in the development of stability-indicating LC and hyphenated LC-MS methods have also been briefly reported. Performing of Quantitative structure retention relationship (QSRR) study enhanced with DOE-based data collection was recomended as a future perspective in description of retention in HPLC system.
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den Uijl MJ, Schoenmakers PJ, Pirok BWJ, van Bommel MR. Recent applications of retention modelling in liquid chromatography. J Sep Sci 2020; 44:88-114. [PMID: 33058527 PMCID: PMC7821232 DOI: 10.1002/jssc.202000905] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 10/02/2020] [Accepted: 10/12/2020] [Indexed: 11/18/2022]
Abstract
Recent applications of retention modelling in liquid chromatography (2015–2020) are comprehensively reviewed. The fundamentals of the field, which date back much longer, are summarized. Retention modeling is used in retention‐mechanism studies, for determining physical parameters, such as lipophilicity, and for various more‐practical purposes, including method development and optimization, method transfer, and stationary‐phase characterization and comparison. The review focusses on the effects of mobile‐phase composition on retention, but other variables and novel models to describe their effects are also considered. The five most‐common models are addressed in detail, i.e. the log‐linear (linear‐solvent‐strength) model, the quadratic model, the log–log (adsorption) model, the mixed‐mode model, and the Neue–Kuss model. Isocratic and gradient‐elution methods are considered for determining model parameters and the evaluation and validation of fitted models is discussed. Strategies in which retention models are applied for developing and optimizing one‐ and two‐dimensional liquid chromatographic separations are discussed. The review culminates in some overall conclusions and several concrete recommendations.
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Affiliation(s)
- Mimi J den Uijl
- Analytical Chemistry Group, van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Peter J Schoenmakers
- Analytical Chemistry Group, van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Bob W J Pirok
- Analytical Chemistry Group, van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Maarten R van Bommel
- Analytical Chemistry Group, van 't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, The Netherlands.,Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands.,University of Amsterdam, Faculty of Humanities, Conservation and Restoration of Cultural Heritage, Amsterdam, The Netherlands
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5
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Advanced chromatographic technique for performance simulation of anti-Alzheimer agent: an ensemble machine learning approach. SN APPLIED SCIENCES 2020. [DOI: 10.1007/s42452-020-03690-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
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6
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Bos TS, Knol WC, Molenaar SR, Niezen LE, Schoenmakers PJ, Somsen GW, Pirok BW. Recent applications of chemometrics in one- and two-dimensional chromatography. J Sep Sci 2020; 43:1678-1727. [PMID: 32096604 PMCID: PMC7317490 DOI: 10.1002/jssc.202000011] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 02/20/2020] [Accepted: 02/21/2020] [Indexed: 12/28/2022]
Abstract
The proliferation of increasingly more sophisticated analytical separation systems, often incorporating increasingly more powerful detection techniques, such as high-resolution mass spectrometry, causes an urgent need for highly efficient data-analysis and optimization strategies. This is especially true for comprehensive two-dimensional chromatography applied to the separation of very complex samples. In this contribution, the requirement for chemometric tools is explained and the latest developments in approaches for (pre-)processing and analyzing data arising from one- and two-dimensional chromatography systems are reviewed. The final part of this review focuses on the application of chemometrics for method development and optimization.
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Affiliation(s)
- Tijmen S. Bos
- Division of Bioanalytical ChemistryAmsterdam Institute for Molecules, Medicines and SystemsVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Wouter C. Knol
- Analytical Chemistry Groupvan ’t Hoff Institute for Molecular Sciences, Faculty of ScienceUniversity of AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Stef R.A. Molenaar
- Analytical Chemistry Groupvan ’t Hoff Institute for Molecular Sciences, Faculty of ScienceUniversity of AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Leon E. Niezen
- Analytical Chemistry Groupvan ’t Hoff Institute for Molecular Sciences, Faculty of ScienceUniversity of AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Peter J. Schoenmakers
- Analytical Chemistry Groupvan ’t Hoff Institute for Molecular Sciences, Faculty of ScienceUniversity of AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Govert W. Somsen
- Division of Bioanalytical ChemistryAmsterdam Institute for Molecules, Medicines and SystemsVrije Universiteit AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
| | - Bob W.J. Pirok
- Analytical Chemistry Groupvan ’t Hoff Institute for Molecular Sciences, Faculty of ScienceUniversity of AmsterdamAmsterdamThe Netherlands
- Centre for Analytical Sciences Amsterdam (CASA)AmsterdamThe Netherlands
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Pirok BWJ, Molenaar SRA, Roca LS, Schoenmakers PJ. Peak-Tracking Algorithm for Use in Automated Interpretive Method-Development Tools in Liquid Chromatography. Anal Chem 2018; 90:14011-14019. [PMID: 30396266 PMCID: PMC6282104 DOI: 10.1021/acs.analchem.8b03929] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
![]()
A peak-tracking algorithm
for chromatograms recorded using liquid
chromatography and mass spectrometry was developed. Peaks are tracked
across chromatograms using the spectrometric information, the statistical
moments of the chromatographic peaks, and the relative retention.
The algorithm can be applied to pair chromatographic peaks in two
very different chromatograms, obtained for different samples using
different methods. A fast version of the algorithm was specifically
tailored to process chromatograms obtained during method development
or optimization, where a few similar mobile-phase-composition gradients
(same eluent components, but different ranges and programming rates)
are applied to the same sample for the purpose of obtaining model
parameters to describe the retention of sample components. Due to
the relative similarity between chromatograms, time-saving preselection
protocols can be used to locate a candidate peak in another chromatogram.
The algorithm was applied to two different samples featuring isomers.
The automatically tracked peaks and the resulting retention parameters
generally yielded prediction errors of less than 1%.
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Affiliation(s)
- Bob W J Pirok
- van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands.,TI-COAST , Science Park 904 , 1098 XH Amsterdam , The Netherlands
| | - Stef R A Molenaar
- van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands
| | - Liana S Roca
- van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands
| | - Peter J Schoenmakers
- van 't Hoff Institute for Molecular Sciences, Analytical Chemistry Group , University of Amsterdam , Science Park 904 , 1098 XH Amsterdam , The Netherlands
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Shojaeimehr T, Rahimpour F. Retention time modeling of short-chain aliphatic acids in aqueous ion-exclusion chromatography systems under several conditions using computational intelligence methods (artificial neural network and adaptive neuro-fuzzy inference system). J LIQ CHROMATOGR R T 2018. [DOI: 10.1080/10826076.2018.1518846] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Tahereh Shojaeimehr
- Biotechnology Research Lab., Chemical Engineering Department, Faculty of Petroleum and Chemical Engineering, Razi University, Kermanshah, Iran
| | - Farshad Rahimpour
- Biotechnology Research Lab., Chemical Engineering Department, Faculty of Petroleum and Chemical Engineering, Razi University, Kermanshah, Iran
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D'Archivio AA, Di Donato F, Foschi M, Maggi MA, Ruggieri F. UHPLC Analysis of Saffron ( Crocus sativus L.): Optimization of Separation Using Chemometrics and Detection of Minor Crocetin Esters. Molecules 2018; 23:molecules23081851. [PMID: 30044436 PMCID: PMC6222919 DOI: 10.3390/molecules23081851] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 07/20/2018] [Accepted: 07/22/2018] [Indexed: 02/06/2023] Open
Abstract
Ultra-high performance liquid chromatography (UHPLC) coupled with diode array detection (DAD) was applied to improve separation and detection of mono- and bis-glucosyl esters of crocetin (crocins), the main red-colored constituents of saffron (Crocus sativus L.), and other polar components. Response surface methodology (RSM) was used to optimise the chromatographic resolution on the Kinetex C18 (Phenomenex) column taking into account of the combined effect of the column temperature, the eluent flow rate and the slope of a linear eluent concentration gradient. A three-level full-factorial design of experiments was adopted to identify suitable combinations of the above factors. The influence of the separation conditions on the resolutions of 22 adjacent peaks was simultaneously modelled by a multi-layer artificial neural network (ANN) in which a bit string representation was used to identify the target analytes. The chromatogram collected under the optimal separation conditions revealed a higher number of crocetin esters than those already characterised by means of mass-spectrometry data and usually detected by HPLC. Ultra-high performance liquid chromatography analyses carried out on the novel Luna Omega Polar C18 (Phenomenex) column confirmed the large number of crocetin derivatives. Further work is in progress to acquire mass-spectrometry data and to clarify the chemical structure to the newly found saffron components.
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Affiliation(s)
- Angelo Antonio D'Archivio
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67100 L'Aquila, Italy.
| | - Francesca Di Donato
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67100 L'Aquila, Italy.
| | - Martina Foschi
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67100 L'Aquila, Italy.
| | | | - Fabrizio Ruggieri
- Dipartimento di Scienze Fisiche e Chimiche, Università degli Studi dell'Aquila, Via Vetoio, 67100 L'Aquila, Italy.
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Safari M, Yamini Y, Mani-Varnosfaderani A, Asiabi H. Synthesis of Fe3O4@PPy–MWCNT nanocomposite and its application for extraction of ultra-trace amounts of PAHs from various samples. JOURNAL OF THE IRANIAN CHEMICAL SOCIETY 2016. [DOI: 10.1007/s13738-016-1012-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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12
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Mikulášek K, Jaroň KS, Kulhánek P, Bittová M, Havliš J. Sequence-dependent separation of trinucleotides by ion-interaction reversed-phase liquid chromatography-A structure-retention study assisted by soft-modelling and molecular dynamics. J Chromatogr A 2016; 1469:88-95. [PMID: 27692640 DOI: 10.1016/j.chroma.2016.09.060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 09/22/2016] [Accepted: 09/24/2016] [Indexed: 10/21/2022]
Abstract
We studied sequence-dependent retention properties of synthetic 5'-terminal phosphate absent trinucleotides containing adenine, guanine and thymine through reversed-phase liquid chromatography (RPLC) and QSRR modelling. We investigated the influence of separation conditions, namely mobile phase composition (ion interaction agent content, pH and organic constituent content), on sequence-dependent separation by means of ion-interaction RPLC (II-RPLC) using two types of models: experimental design-artificial neural networks (ED-ANN), and linear regression based on molecular dynamics data. The aim was to determine those properties of the above-mentioned analytes responsible for the retention dependence of the sequence. Our results show that there is a deterministic relation between sequence and II-RPLC retention properties of the studied trinucleotides. Further, we can conclude that the higher the content of ion-interaction agent in the mobile phase, the more prominent these properties are. We also show that if we approximate the polar component of solvation energy in QSRR by the electrostatic work in transferring molecules from vacuum to water, and the non-polar component by the solvent accessible surface area, these parameters best describe the retention properties of trinucleotides. There are some exceptions to this finding, namely sequences 5'-NAN-3', 5'-ANN-3', 5'-TGN-3', 5'-NTA-3'and 5'-NGA-3' (N stands for generic nucleotide). Their role is still unknown, but since linear regression including these specific constellations showed a higher observable variance coverage than the model with only the basic descriptors, we may assume that solvent-analyte interactions are responsible for the exceptional behaviour of 5'-NAN-3' & 5'-ANN-3' trinucleotides and some intramolecular interactions of neighbouring nucleobases for 5'-TGN-3', 5'-NTA-3'and 5'-NGA-3' trinucleotides.
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Affiliation(s)
- Kamil Mikulášek
- Masaryk University, Faculty of Science, Department of Chemistry, Kamenice 5, 62500 Brno, Czech Republic; Masaryk University, CEITEC - Central European Institute of Technology, Kamenice 5, 62500 Brno, Czech Republic
| | - Kamil S Jaroň
- Academy of Sciences of the Czech Republic, Institute of Vertebrate Biology, Květná 8, 603 65 Brno, Czech Republic
| | - Petr Kulhánek
- Masaryk University, CEITEC - Central European Institute of Technology, Kamenice 5, 62500 Brno, Czech Republic; Masaryk University, Faculty of Science, National Centre of Biomolecular Research, Kamenice 5, 62500 Brno, Czech Republic
| | - Miroslava Bittová
- Masaryk University, Faculty of Science, Department of Chemistry, Kamenice 5, 62500 Brno, Czech Republic
| | - Jan Havliš
- Masaryk University, CEITEC - Central European Institute of Technology, Kamenice 5, 62500 Brno, Czech Republic; Masaryk University, Faculty of Science, National Centre of Biomolecular Research, Kamenice 5, 62500 Brno, Czech Republic.
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A review of multivariate designs applied to the optimization of methods based on inductively coupled plasma optical emission spectrometry (ICP OES). Microchem J 2016. [DOI: 10.1016/j.microc.2016.05.015] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Duodu GO, Goonetilleke A, Ayoko GA. Optimization of in-cell accelerated solvent extraction technique for the determination of organochlorine pesticides in river sediments. Talanta 2016; 150:278-85. [DOI: 10.1016/j.talanta.2015.12.049] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Revised: 12/17/2015] [Accepted: 12/18/2015] [Indexed: 10/22/2022]
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D’Archivio AA, Maggi MA, Marinelli C, Ruggieri F, Stecca F. Optimisation of temperature-programmed gas chromatographic separation of organochloride pesticides by response surface methodology. J Chromatogr A 2015; 1423:149-57. [DOI: 10.1016/j.chroma.2015.10.082] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2015] [Revised: 10/26/2015] [Accepted: 10/27/2015] [Indexed: 10/22/2022]
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Garcel1 RHR, León OG, Magaz EO. PRELIMINARY MODELING OF AN INDUSTRIAL RECOMBINANT HUMAN ERYTHROPOIETIN PURIFICATION PROCESS BY ARTIFICIAL NEURAL NETWORKS. BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING 2015. [DOI: 10.1590/0104-6632.20150323s00003527] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Artificial neural network prediction of multilinear gradient retention in reversed-phase HPLC: comprehensive QSRR-based models combining categorical or structural solute descriptors and gradient profile parameters. Anal Bioanal Chem 2014; 407:1181-90. [DOI: 10.1007/s00216-014-8317-3] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2014] [Revised: 10/30/2014] [Accepted: 11/03/2014] [Indexed: 11/26/2022]
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Yu Y, Jiang X, Gong S, Feng L, Zhong Y, Pang Z. The proton permeability of self-assembled polymersomes and their neuroprotection by enhancing a neuroprotective peptide across the blood-brain barrier after modification with lactoferrin. NANOSCALE 2014; 6:3250-3258. [PMID: 24503971 DOI: 10.1039/c3nr05196j] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Biotherapeutics such as peptides possess strong potential for the treatment of intractable neurological disorders. However, because of their low stability and the impermeability of the blood-brain barrier (BBB), biotherapeutics are difficult to transport into brain parenchyma via intravenous injection. Herein, we present a novel poly(ethylene glycol)-poly(d,l-lactic-co-glycolic acid) polymersome-based nanomedicine with self-assembled bilayers, which was functionalized with lactoferrin (Lf-POS) to facilitate the transport of a neuroprotective peptide into the brain. The apparent diffusion coefficient (D*) of H(+) through the polymersome membrane was 5.659 × 10(-26) cm(2) s(-1), while that of liposomes was 1.017 × 10(-24) cm(2) s(-1). The stability of the polymersome membrane was much higher than that of liposomes. The uptake of polymersomes by mouse brain capillary endothelial cells proved that the optimal density of lactoferrin was 101 molecules per polymersome. Fluorescence imaging indicated that Lf101-POS was effectively transferred into the brain. In pharmacokinetics, compared with transferrin-modified polymersomes and cationic bovine serum albumin-modified polymersomes, Lf-POS obtained the greatest BBB permeability surface area and percentage of injected dose per gram (%ID per g). Furthermore, Lf-POS holding S14G-humanin protected against learning and memory impairment induced by amyloid-β25-35 in rats. Western blotting revealed that the nanomedicine provided neuroprotection against over-expression of apoptotic proteins exhibiting neurofibrillary tangle pathology in neurons. The results indicated that polymersomes can be exploited as a promising non-invasive nanomedicine capable of mediating peptide therapeutic delivery and controlling the release of drugs to the central nervous system.
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Affiliation(s)
- Yuan Yu
- Department of Pharmaceutics, School of Pharmacy, The Second Military Medical University, 800 XiangYin Road, Shanghai 200433, China.
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Cela R, Ordoñez E, Quintana J, Rodil R. Chemometric-assisted method development in reversed-phase liquid chromatography. J Chromatogr A 2013; 1287:2-22. [DOI: 10.1016/j.chroma.2012.07.081] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Revised: 07/25/2012] [Accepted: 07/26/2012] [Indexed: 11/16/2022]
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Vemic A, Malenovic A, Rakic T, Kostic N, Jancic Stojanovic B. Chemometrical Tools in the Study of the Retention Behavior of Azole Antifungals. J Chromatogr Sci 2013; 52:95-102. [DOI: 10.1093/chromsci/bms211] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Chen G, Li J, Zhang S, Song C, Li G, Sun Z, Suo Y, You J. A sensitive and efficient method to systematically detect two biophenols in medicinal herb, herbal products and rat plasma based on thorough study of derivatization and its convenient application to pharmacokinetics with semi-automated device. J Chromatogr A 2012; 1249:190-200. [DOI: 10.1016/j.chroma.2012.06.027] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2012] [Revised: 06/10/2012] [Accepted: 06/11/2012] [Indexed: 11/29/2022]
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Artificial Neural Network Modelling of the Retention of Acidic Analytes in Strong Anion-Exchange HPLC: Elucidation of Structure-Retention Relationships. Chromatographia 2012. [DOI: 10.1007/s10337-012-2251-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Wu H, Li J, Zhang Q, Yan X, Guo L, Gao X, Qiu M, Jiang X, Lai R, Chen H. A novel small Odorranalectin-bearing cubosomes: Preparation, brain delivery and pharmacodynamic study on amyloid-β25–35-treated rats following intranasal administration. Eur J Pharm Biopharm 2012; 80:368-78. [DOI: 10.1016/j.ejpb.2011.10.012] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2011] [Revised: 09/04/2011] [Accepted: 10/14/2011] [Indexed: 01/11/2023]
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Korany MA, Mahgoub H, Fahmy OT, Maher HM. Application of artificial neural networks for response surface modelling in HPLC method development. J Adv Res 2012. [DOI: 10.1016/j.jare.2011.04.001] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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Yu Y, Pang Z, Lu W, Yin Q, Gao H, Jiang X. Self-Assembled Polymersomes Conjugated with Lactoferrin as Novel Drug Carrier for Brain Delivery. Pharm Res 2011; 29:83-96. [DOI: 10.1007/s11095-011-0513-7] [Citation(s) in RCA: 60] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2011] [Accepted: 06/10/2011] [Indexed: 01/29/2023]
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Malenović A, Jančić-Stojanović B, Kostić N, Ivanović D, Medenica M. Optimization of Artificial Neural Networks for Modeling of Atorvastatin and Its Impurities Retention in Micellar Liquid Chromatography. Chromatographia 2011. [DOI: 10.1007/s10337-011-1994-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC. Anal Bioanal Chem 2010; 397:2367-74. [PMID: 20490467 PMCID: PMC2895920 DOI: 10.1007/s00216-010-3778-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2010] [Revised: 04/11/2010] [Accepted: 04/22/2010] [Indexed: 11/27/2022]
Abstract
Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples. ANN-derived response surface plot for two interacting factors and overall response ![]()
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29
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An optimization on strontium separation model for fission products (inactive trace elements) using artificial neural networks. ANN NUCL ENERGY 2009. [DOI: 10.1016/j.anucene.2009.04.015] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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30
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Anđelija M, Darko I, Biljana SJ, Mirjana M. Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities. J LIQ CHROMATOGR R T 2009. [DOI: 10.1080/10826070902768161] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
| | - Ivanović Darko
- a Faculty of Pharmacy, Department of Drug Analysis , Belgrade, Serbia
| | | | - Medenica Mirjana
- b Faculty of Pharmacy, Department of Physical Chemistry , Belgrade, Serbia
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31
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Li Y, Du X, Yuan Q, Lv X. Development and validation of a new PCR optimization method by combining experimental design and artificial neural network. Appl Biochem Biotechnol 2009; 160:269-79. [PMID: 19266318 DOI: 10.1007/s12010-009-8581-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2008] [Accepted: 02/18/2009] [Indexed: 11/24/2022]
Abstract
Polymerase chain reaction (PCR) is one of the most powerful techniques in a variety of clinical and biological research fields. In this paper, a chemometrics approach, combining experimental design (ED) and artificial neural network (ANN), was proposed for optimization of PCR amplification of lycopene cyclase gene carRA in Blakeslea Trispora. Five-level star design was carried out to obtain experimental information and provide data source for ANN modeling. Nine variables were used as inputs in ANN, including the added amount of template, primer, dNTP, polymerase and magnesium ion, the temperature of denaturating, annealing and extension, and the number of cycles. The output variable was the efficiency (yield) of the PCR. Based on the developed model, the effects of each parameter on PCR efficiency were predicted and the most suitable operation condition for present system was determined. At last, the validation experiment was performed under the optimized condition, and the expectant results were produced. The results obtained in this paper showed that the combination of ANN and ED provided a satisfactory optimization model with good descriptive and predictive abilities, indicating that the method of combining ANN and ED can be a useful tool in PCR optimization and other biological applications.
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Affiliation(s)
- Ye Li
- Key Laboratory of Bioprocess of Beijing, Beijing University of Chemical Technology, Beijing, China
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32
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Vučićević K, Popović G, Nikolic K, Vovk I, Agbaba D. An Experimental Design Approach to Selecting the Optimum HPLC Conditions for the Determination of 2-Arylimidazoline Derivatives. J LIQ CHROMATOGR R T 2009. [DOI: 10.1080/10826070802711113] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Katarina Vučićević
- a Institute of Pharmaceutical Chemistry and Drug Analysis, Faculty of Pharmacy , University of Belgrade , Belgrade, Serbia
| | - Gordana Popović
- a Institute of Pharmaceutical Chemistry and Drug Analysis, Faculty of Pharmacy , University of Belgrade , Belgrade, Serbia
| | - Katarina Nikolic
- a Institute of Pharmaceutical Chemistry and Drug Analysis, Faculty of Pharmacy , University of Belgrade , Belgrade, Serbia
| | - Irena Vovk
- b Laboratory of Food Chemistry , National Institute of Chemistry , Ljubljana, Slovenia
| | - Danica Agbaba
- a Institute of Pharmaceutical Chemistry and Drug Analysis, Faculty of Pharmacy , University of Belgrade , Belgrade, Serbia
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33
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Du X, Li Y, Yuan Q. A sequence optimization strategy for chromatographic separation in reversed-phase high-performance liquid chromatography. AIChE J 2009. [DOI: 10.1002/aic.12006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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34
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Combined effect of solvent content, temperature and pH on the chromatographic behaviour of ionisable compounds. J Chromatogr A 2008; 1193:117-28. [DOI: 10.1016/j.chroma.2008.04.019] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2008] [Revised: 04/04/2008] [Accepted: 04/09/2008] [Indexed: 11/18/2022]
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35
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Jančić B, Medenica M, Ivanović D, Janković S, Malenović A. Monitoring of fosinopril sodium impurities by liquid chromatography–mass spectrometry including the neural networks in method evaluation. J Chromatogr A 2008; 1189:366-73. [DOI: 10.1016/j.chroma.2007.11.076] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2007] [Revised: 11/03/2007] [Accepted: 11/27/2007] [Indexed: 10/22/2022]
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36
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Biljana J, Mirjana M, Darko I, Anđelija M, Igor P. Chromatographic Behavior of Fosinopril Sodium and Fosinoprilat Using Neural Networks. Chromatographia 2008. [DOI: 10.1365/s10337-008-0575-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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37
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Quiming NS, Denola NL, Saito Y, Catabay AP, Jinno K. Chromatographic Behavior of Uric Acid and Methyl Uric Acids on a Diol Column in HILIC. Chromatographia 2008. [DOI: 10.1365/s10337-008-0559-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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38
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Havel J, Li R, Macka M. CE study of neuroprotective humanin peptide and its derivatives: Interactions with phosphate, sulphate, alkylsulphonates and sulphated-β-CD. Electrophoresis 2008; 29:665-71. [DOI: 10.1002/elps.200700588] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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39
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Quiming NS, Denola NL, Soliev AB, Saito Y, Jinno K. High Performance Liquid Chromatographic Separation and Quantitative Analysis of Ginsenosides Using a Polyvinyl Alcohol-Bonded Stationary Phase. Chromatographia 2007. [DOI: 10.1365/s10337-007-0258-y] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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40
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Ferreira SLC, Bruns RE, da Silva EGP, Dos Santos WNL, Quintella CM, David JM, de Andrade JB, Breitkreitz MC, Jardim ICSF, Neto BB. Statistical designs and response surface techniques for the optimization of chromatographic systems. J Chromatogr A 2007; 1158:2-14. [PMID: 17416377 DOI: 10.1016/j.chroma.2007.03.051] [Citation(s) in RCA: 340] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2007] [Revised: 03/08/2007] [Accepted: 03/13/2007] [Indexed: 12/01/2022]
Abstract
This paper describes fundamentals and applications of multivariate statistical techniques for the optimization of chromatographic systems. The surface response methodologies: central composite design, Doehlert matrix and Box-Behnken design are discussed and applications of these techniques for optimization of sample preparation steps (extractions) and determination of experimental conditions for chromatographic separations are presented. The use of mixture design for optimization of mobile phases is also related. An optimization example involving a real separation process is exhaustively described. A discussion about model validation is presented. Some applications of other multivariate techniques for optimization of chromatographic methods are also summarized.
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Affiliation(s)
- Sergio Luis Costa Ferreira
- Universidade Federal da Bahia, Instituto de Química, Campus Universitário de Ondina, Salvador, Bahia 40170-290, Brazil.
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da Silva GA, Augusto F, Poppi RJ. Simultaneous optimization by neuro-genetic approach of a multiresidue method for determination of pesticides in Passiflora alata infuses using headspace solid phase microextraction and gas chromatography. J Chromatogr A 2007; 1138:251-61. [PMID: 17101143 DOI: 10.1016/j.chroma.2006.10.075] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2006] [Revised: 10/26/2006] [Accepted: 10/30/2006] [Indexed: 11/26/2022]
Abstract
A simultaneous optimization strategy based on neuro-genetic approach has been applied to a HS-SPME-GC-ECD (Headspace Solid Phase Microextraction coupled to Gas Chromatography with Electron Capture Detection) method for simultaneous determination of the pesticides chlorotalonil, methyl parathion, malathion, alpha-endosulfan and beta-endosulfan in herbal infusions of Passiflora alata (Dryander). Two types of extractive fibers were used: a home-made device coated by sol-gel process with polydimethylsiloxane-poly(vinyl alcohol) (PDMS/PVA) and a commercial PDMS. The effects of extraction parameters such as dilution of the infusion, extraction temperature and time, as well as sample ionic strength were evaluated through the Doehlert design. To find a model that could relate these extraction parameters with the extraction efficiency of all pesticide simultaneously, a Bayesian Regularized Artificial Neural Network (BRANN) approach was employed. Subsequently, Genetic Algorithm (GA) was applied to attain the optimum values from the model developed by the neural network. The use of the proposed approach allowed the determination of a single extraction condition that maximized the peak areas of all pesticides simultaneously, showing a promising and a suitable new procedure to the optimization process of complex analytical problems.
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Affiliation(s)
- Gilmare Antônia da Silva
- Instituto de Química, Universidade Estadual de Campinas, Caixa Postal 6154, 13084-971 Campinas, SP, Brazil
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42
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Kowalski CH, da Silva GA, Poppi RJ, Godoy HT, Augusto F. Neuro-genetic multioptimization of the determination of polychlorinated biphenyl congeners in human milk by headspace solid phase microextraction coupled to gas chromatography with electron capture detection. Anal Chim Acta 2006; 585:66-75. [PMID: 17386648 DOI: 10.1016/j.aca.2006.11.073] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2006] [Revised: 10/30/2006] [Accepted: 11/29/2006] [Indexed: 11/25/2022]
Abstract
Polychlorinated biphenyls (PCB) can eventually contaminate breast milk, which is a serious issue to the newborn due to their high vulnerability. Solid phase microextraction (SPME) can be a very convenient technique for their isolation and pre-concentration prior chromatographic analysis. Here, a simultaneous multioptimization strategy based on a neuro-genetic approach was applied to a headspace SPME method for determination of 12 PCB in human milk. Gas chromatography with electron capture detection (ECD) was adopted for the separation and detection of the analytes. Experiments according to a Doehlert design were carried out with varied extraction time and temperature, media ionic strength and concentration of the methanol (co-solvent). To find the best model that simultaneously correlate all PCB peak areas and SPME extraction conditions, a multivariate calibration method based on a Bayesian Neural Network (BNN) was applied. The net output from the neural network was used as input in a genetic algorithm (GA) optimization operation (neuro-genetic approach). The GA pointed out that the best values of the overall SPME operational conditions were the saturation of the media with NaCl, extraction temperature of 95 degrees C, extraction time of 60 min and addition of 5% (v/v) methanol to the media. These optimized parameters resulted in the decrease of the detection limits and increase on the sensitivity for all tested analytes, showing that the use of neuro-genetic approach can be a promising way for optimization of SPME methods.
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43
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Hanrahan G, Lu K. Application of Factorial and Response Surface Methodology in Modern Experimental Design and Optimization. Crit Rev Anal Chem 2006. [DOI: 10.1080/10408340600969478] [Citation(s) in RCA: 139] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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44
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Pan C, Xu S, Zhou H, Fu Y, Ye M, Zou H. Recent developments in methods and technology for analysis of biological samples by MALDI-TOF-MS. Anal Bioanal Chem 2006; 387:193-204. [PMID: 17086385 DOI: 10.1007/s00216-006-0905-4] [Citation(s) in RCA: 89] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2006] [Revised: 09/28/2006] [Accepted: 09/29/2006] [Indexed: 10/24/2022]
Abstract
Matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS) is widely used in a variety of fields because it has the characteristics of speed, ease of use, high sensitivity, and wide detectable mass range for obtaining molecular weights and for structural characterization of macromolecules. In this article we summarize recent developments in matrix additives, new matrices, and sample-pretreatment methods using off-probe or on-probe techniques or nanomaterials for MALDI-TOF-MS analysis of biological samples.
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Affiliation(s)
- Chensong Pan
- National Chromatographic R & A Center, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, People's Republic of China
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