Use of ICA on HPCL-DAD data and high-order statistics to automatically achieve peak picking
(2008) , 17 pages
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- Authors
Govaerts, Bernadette 
- Abstract
- One of the major difficulties within the context of the fully automated development of chromatographic methods consists in the automated detection of the peaks coming from complex matrices such as multicomponent pharmaceutical formulations or stability studies of these formulations. The same problem can also occur with plant materials or biological matrices. This step is thus critical and time-consuming, especially when Designs of Experiments (DOE) are used to generate chromatograms. The use of DOE leads to maximize the changes of the analytical conditions in order to cleverly explore an experimental domain. Unfortunately, this generally provides very different and “uncontrolled” chromatograms which can be hardly interpretable, complicating picking and peak tracking. In this context, numerical signal processing methods such as Independent Components Analysis (ICA) was investigated to solve this problem. The ICA principle assumes that the observed signal is the resultant of several phenomena (known as sources) and that all these sources are statistically independent. ICA is able to estimate sources which most often seem judicious to represent the constitutive components of a chromatogram. In the present study, ICA was applied to HPLC-UV-DAD chromatograms and we showed that ICA allows differentiating noises and artifacts components from those of interest, by applying clustering methods based on high-order statistics computed on these components. Furthermore, on the basis of the described numerical strategy, it was also possible to rebuild a cleaned chromatogram easily legible. This represents a very significant advance towards our final objective, the fully automated development of liquid chromatography (LC) method.
- Affiliations
Uliège Sevice de Chimie Analytique
Citations
Debrus, B., Lebrun, P., Ceccato, A., Caliaro, G., Govaerts, B., Olsen, B., Rozet, E., Boulanger, B., & Hubert, P. (2008). Use of ICA on HPCL-DAD data and high-order statistics to automatically achieve peak picking (STAT Discussion Paper 0811). https://hdl.handle.net/2078.5/26539