Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Use of control sample for estimation of prediction error in multivariate determination of lidocaine solutions with non-column chromatographic diode array UV spectroscopy
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
Stockholm University, Faculty of Science, Department of Analytical Chemistry.
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.

Place, publisher, year, edition, pages
2003. Vol. 33, no 5, 859-869 p.
Keyword [sv]
Control sample, Non-column, Diode array UV spectroscopy, Multivariate calibration, Lidocaine
Identifiers
URN: urn:nbn:se:su:diva-22775DOI: 10.1016/S0731-7085(03)00417-5OAI: oai:DiVA.org:su-22775DiVA: diva2:189420
Note
Part of urn:nbn:se:su:diva-110Available from: 2004-04-22 Created: 2004-04-22 Last updated: 2017-12-13Bibliographically approved
In thesis
1. Multivariate spectroscopic methods for the analysis of solutions
Open this publication in new window or tab >>Multivariate spectroscopic methods for the analysis of solutions
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
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:nbn:se:su:diva-110 (URN)91-7265-789-8 (ISBN)
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

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Jacobsson, Sven P.
By organisation
Department of Analytical Chemistry
In the same journal
Journal of Pharmaceutical and Biomedical Analysis

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 40 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf