Use of multivariate characterization, design and analysis in assay optimization
| Autor: | Natalia Borg, Arshad Mian, Lars Ståhle |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
Multivariate statistics
Multivariate analysis Chromatography Chemical Phenomena Chemistry Physical Chemistry Clinical Biochemistry Pharmaceutical Science Experimental data Nucleosides Regression analysis Chemistry Techniques Analytical Confidence interval Analytical Chemistry Characterization (materials science) Chemometrics Models Chemical Multivariate Analysis Drug Discovery Least-Squares Analysis Quantitative analysis (chemistry) Software Spectroscopy Chromatography Liquid |
| Zdroj: | Journal of Pharmaceutical and Biomedical Analysis. 13:369-376 |
| ISSN: | 0731-7085 |
| Popis: | A procedure is proposed for utilizing information from previous work on development of LC assays in order to facilitate the analysis of novel compounds related to those previously analysed. The procedure employs a multivariate method from the field of chemometrics, partial least squares analysis (PLS) to combine quantitative information on the chemical properties of a compound with a quantitative description of the column and the mobile phase and then to use this information to form a regression model for the retention time. A test of the procedure was made by using data on nucleoside analogues studied in our laboratory. Data obtained from chromatographic studies of seven compounds tested in a total of 28 combinations of columns and mobile phases (3–5 per compound) were used to calculate a PLS model. The model was then used to predict retention times of nine other substances and the results were compared with experimental data. The predictions were (115 ± 82%) (95% confidence interval) of the experimentally observed retention times. The results are encouraging and the method will be subject to further and extended investigations. |
| Databáze: | OpenAIRE |
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