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Multivariate spectroscopic methods for the analysis of solutions
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
2004 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation.

The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins.

In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

Place, publisher, year, edition, pages
Stockholm: Institutionen för analytisk kemi , 2004. , 73 p.
Keyword [en]
Chemometrics, UV-Vis spectroscopy, Multivariate calibration, Lidocaine, Identity, Content, PLS, SIMCA, Non-column, Diode array UV spectroscopy, DAD, Control sample, High Capacity Analysis (HCA), Fluorescence spectroscopy, Albumin, Immunoglobulin G, HPLC-DAD, Prilocaine, Peak purity determination, PCA, PARAFAC, Partial separation, Curve resolution
National Category
Analytical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-110ISBN: 91-7265-789-8 (print)OAI: oai:DiVA.org:su-110DiVA: diva2:189424
Public defence
2004-05-14, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 12 A, Stockholm, 13:15
Opponent
Supervisors
Available from: 2004-04-22 Created: 2004-04-22Bibliographically approved
List of papers
1. Determination of the content and identity of lidocaine soluions with UV-visible spectroscopy and multivariate calibration
Open this publication in new window or tab >>Determination of the content and identity of lidocaine soluions with UV-visible spectroscopy and multivariate calibration
2001 (English)In: The Analyst, ISSN 0003-2654, E-ISSN 1364-5528, Vol. 126, no 7, 1142-1148 p.Article in journal (Refereed) Published
Abstract [en]

A method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of ultraviolet-visible (UV–Vis) spectroscopy, orthogonal signal correction (OSC) and multivariate calibration with soft independent modelling of class analogy (SIMCA) classification and partial least squares (PLS) regression. The content was determined with PLS regression and the identity with PLS regression and SIMCA classification. The method was tested on the local anaesthetic compound lidocaine. For the validation, external test sets of both manufactured sample solutions and samples from a stability study were used. For comparison with this new method, liquid chromatography was used as a reference method. The results show that in respect of accuracy, precision and repeatability, the new method is comparable to the reference method. The main advantage over liquid chromatography is the much shorter time of analysis and the simpler analytical procedure. An estimate of the analysis time saved with the proposed method compared with using liquid chromatography, together with practical considerations, is given.

Identifiers
urn:nbn:se:su:diva-22773 (URN)10.1039/b102545g (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
2. Rapid determination of lidocaine solutions with non-column chromatographic diode array UV spectroscopy and multivariate calibration
Open this publication in new window or tab >>Rapid determination of lidocaine solutions with non-column chromatographic diode array UV spectroscopy and multivariate calibration
2003 (English)In: Journal of Pharmaceutical and Biomedical Analysis, ISSN 0731-7085, E-ISSN 1873-264X, Vol. 30, no 5, 1575-1586 p.Article in journal (Refereed) Published
Abstract [en]

A new method for the rapid determination of pharmaceutical solutions is proposed. A conventional HPLC system with a Diode Array Detector (DAD) was used with no chromatographic column connected. As eluent, purified water (Milli Q) was used. The pump and autosampler of the HPLC system were mainly utilised as an automatic and convenient way of introducing the sample into the DAD. The method was tested on the local anaesthetic compound lidocaine. The UV spectrum (245–290 nm) from the samples analysed in the detector was used for multivariate calibration for the determination of lidocaine solutions. The content was determined with PLS regression. The effect on the predictive ability of three factors: flow, data-collection rate and rise time as well as two ways of exporting a representative UV spectrum from the DAD file collected was investigated by means of an experimental design comprising 11 experiments. For each experiment, 14 solutions containing a known content of lidocaine were analysed (0.02–0.2 mg ml−1). From these 14 samples two calibration sets and two test sets were made and as the response in the experimental design the Root Mean Square Error of Prediction (RMSEP) values from the predictions of the two test sets were used. When the factor setting giving the lowest RMSEP was found, this setting was used when analysing a new calibration set of 12 lidocaine samples (0.1–0.2 mg ml−1). This calibration model was validated by two external test sets, A and B, analysed on separate occasions for the evaluation of repeatability (test set A) and determination over time (test set B). For comparison, the reference method, liquid chromatography, was also used for analysis of the ten samples in test set B. This comparison of the two methods was done twice on different occasions. The results show that in respect of accuracy, precision and repeatability the new method is comparable to the reference method. The main advantages compared with liquid chromatography are the much shorter time of analysis (<30 s) as well as the automatic and simple analytical procedure and the low consumption of organic solvents.

Keyword
Non-column, Diode array UV spectroscopy, Multivariate calibration, Lidocaine, PLS
Identifiers
urn:nbn:se:su:diva-22774 (URN)10.1016/S0731-7085(02)00548-4 (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
3. Use of control sample for estimation of prediction error in multivariate determination of lidocaine solutions with non-column chromatographic diode array UV spectroscopy
Open this publication in new window or tab >>Use of control sample for estimation of prediction error in multivariate determination of lidocaine solutions with non-column chromatographic diode array UV spectroscopy
2003 (English)In: Journal of Pharmaceutical and Biomedical Analysis, ISSN 0731-7085, E-ISSN 1873-264X, Vol. 33, no 5, 859-869 p.Article in journal (Refereed) Published
Abstract [en]

The aim of this study was to investigate the ability of a control sample, of known content and identity, to diagnose and correct errors in the predictions when the same multivariate calibration model was used for analysis of new samples over time. A calibration set consisting of 16 samples with a known content of lidocaine was analysed and two external test sets, A and B, were used for the validation. Test set A contained 15 samples with different concentrations of lidocaine and test set B contained three samples with different lidocaine content, which were analysed six times in order to obtain a measure of repeatability. The multivariate calibration was done with PLS regression on UV spectra collected between 245 and 290 nm. A representative UV spectrum was exported from the collected DAD files by two methods, average spectrum over the whole file and average spectrum over the sample plug. Test set A was analysed further on another three occasions together with a control sample. The results showed that the control sample could be used to give a diagnosis and estimate of the prediction error. Moreover, the measured prediction error of the control sample could also be used to correct the predictions, thereby reducing the prediction error. Finally, some practical considerations regarding use of the proposed DAD method with a control sample are presented. The procedure suggested could lead to an efficient analytical approach where the same calibration model could be used over time without recalibration, which may be attractive in industrial quality control or screening analysis in pharmaceutical research.

Keyword
Control sample, Non-column, Diode array UV spectroscopy, Multivariate calibration, Lidocaine
Identifiers
urn:nbn:se:su:diva-22775 (URN)10.1016/S0731-7085(03)00417-5 (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
4. Simultaneous determination of albumin and immunoglobulin G with fluorescence spectroscopy and multivariate calibration
Open this publication in new window or tab >>Simultaneous determination of albumin and immunoglobulin G with fluorescence spectroscopy and multivariate calibration
2004 (English)In: Talanta: The International Journal of Pure and Applied Analytical Chemistry, ISSN 0039-9140, E-ISSN 1873-3573, Vol. 62, no 3, 567-574 p.Article in journal (Refereed) Published
Abstract [en]

A method is proposed for the simultaneous determination of albumin and immunoglobulin G (IgG1) with fluorescence spectroscopy and multivariate calibration with partial least squares regression (PLS). The influence of some instrumental parameters were investigated with two experimental designs comprising 19 and 11 experiments, respectively. The investigated parameters were excitation and emission slit, detection voltage and scan rate. When a suitable instrumental setting had been found, a minor calibration and test set were analysed and evaluated. Thereafter, a larger calibration of albumin and IgG1 was made out of 26 samples (0–42 μg ml−1 albumin and 0–12.7 μg ml−1 IgG1). This calibration was validated with a test set consisting of 14 samples in the same concentration range. The precision of the method was estimated by analysing two test set samples for six times each. The scan modes tested were emission scan and synchronous scan Δ60 nm. The results showed that the method could be used for determination of albumin and IgG1 (albumin, root mean square error of prediction (RMSEP) <2, relative standard error of prediction (RSEP) <6% and IgG1, RMSEP <1, RSEP <8%) in spite of the overlapping fluorescence of the two compounds. The estimated precision was relative standard deviation (R.S.D.) <1.7%. The method was finally applied for the analysis of some sample fractions from an albumin standard used in affinity chromatography.

Keyword
Determination, Albumin, Immunoglobulin G, Fluorescence spectroscopy, Multivariate calibration
Identifiers
urn:nbn:se:su:diva-22776 (URN)10.1016/j.talanta.2003.08.024 (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
5. Peak purity determination with principal component analysis of high-performance liquid chromatography-diode array detection data
Open this publication in new window or tab >>Peak purity determination with principal component analysis of high-performance liquid chromatography-diode array detection data
2004 (English)In: Journal of Chromatography A, ISSN 0021-9673, E-ISSN 1873-3778, Vol. 1029, no 1-2, 13-20 p.Article in journal (Refereed) Published
Abstract [en]

A method is proposed for the determination of chromatographic peak purity by means of principal component analysis (PCA) of high-performance liquid chromatography with diode array detection (HPLC–DAD) data. The method is exemplified with analysis of binary mixtures of lidocaine and prilocaine with different levels of separation. Lidocaine and prilocaine have very similar spectra and the chromatograms used had substantial peak overlap. The samples analysed contained a constant amount of lidocaine and a minor amount of prilocaine (0.02–2 conc.%) and hence the focus was on determining the purity of the lidocaine peak in the presence of much smaller levels of prilocaine. The peak purity determination was made by examination of relative observation residuals, scores and loadings from the PCA decomposition of DAD data over a chromatographic peak. As a reference method, the functions for peak purity analysis in the chromatographic data system used (Chromeleon) were applied. The PCA method showed good results at the same level as the detection limit of baseline-separated prilocaine, outperforming the methods in Chromeleon by a factor of ten. There is a discussion of the interpretation of the result, with some comparisons with evolving factor analysis (EFA). The main advantage of the PCA method for determination of peak purity over methods like EFA lies in its simplicity, short time of calculation and ease of use.

Keyword
Principal component analysis, Peak purity determination, Relative observation residuals, Scores, Loadings
Identifiers
urn:nbn:se:su:diva-22777 (URN)10.1016/j.chroma.2003.12.052 (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
6. Parallel factor analysis of HPLC-DAD data for binary mixtures of lidocaine and prilocaine with different levels of separation
Open this publication in new window or tab >>Parallel factor analysis of HPLC-DAD data for binary mixtures of lidocaine and prilocaine with different levels of separation
2004 (English)In: Analytica Chimica Acta, ISSN 0003-2670, E-ISSN 1873-4324, Vol. 514, no 2, 203-209 p.Article in journal (Refereed) Published
Abstract [en]

A set of 17 samples containing a constant amount of lidocaine (667 muM) and a decreasing amount of prilocaine (667-0.3 muM) was analysed by LC-DAD at three different levels of separation, followed by parallel factor analysis (PARAFAC) of the data obtained. In Case 1 no column was connected, the chromatographic resolution (R-s) therefore being zero, while Cases 2 and 3 had partly separated peaks (R-s = 0.7 and 1.0). The results showed that in Case 1, analysed without any separation, the PARAFAC decomposition with a model consisting of two components gave a good estimate of the spectral and concentration profiles of the two compounds. In Cases 2 and 3, the use of PARAFAC models with two components resolved the underlying chromatographic, spectral and concentration profiles. The loadings related to the concentration profile of prilocaine were used for regression and prediction of the prilocaine content. The results showed that prediction of prilocaine content was possible with satisfactory prediction (RMSEP < 0.01). This study shows that PARAFAC is a powerful technique for resolving partly separated peaks into their pure chromatographic, spectral and concentration profiles, even with completely overlapping spectra and the absence or very low levels of separation.

Keyword
PARAFAC; HPLC-DAD; binary mixtures; lidocaine; prilocaine; partial separation
Identifiers
urn:nbn:se:su:diva-22778 (URN)10.1016/j.aca.2004.03.062 (DOI)
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved

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