title: Classification of structurally related commercial contrast media by near infrared spectroscopy.
abstract: Near infrared spectroscopy (NIRS) is a non-destructive measurement technique with broad application in pharmaceutical industry. Correct identification of pharmaceutical ingredients is an important task for quality control. Failure in this step can result in several adverse consequences, varied from economic loss to negative impact on patient safety. We have compared different methods in classification of a set of commercially available structurally related contrast media, Iodixanol (Visipaque(®)), Iohexol (Omnipaque(®)), Caldiamide Sodium and Gadodiamide (Omniscan(®)), by using NIR spectroscopy. The performance of classification models developed by soft independent modelling of class analogy (SIMCA), partial least squares discriminant analysis (PLS-DA) and Main and Interactions of Individual Principal Components Regression (MIPCR) were compared. Different variable selection methods were applied to optimize the classification models. Models developed by backward variable elimination partial least squares regression (BVE-PLS) and MIPCR were found to be most effective for classification of the set of contrast media. Below 1.5% of samples from the independent test set were not recognized by the BVE-PLS and MIPCR models, compared to up to 15% when models developed by other techniques were applied.
authors.affiliation: University of Oslo, School of Pharmacy, Department of Pharmacy, P.O. Box 1068, Blindern, N-0316 Oslo, Norway. Electronic address: w.l.yip@farmasi.uio.no.
authors.forename: Wai Lam
authors.initials: WL
authors.lastname: Yip
authors.affiliation: GE Healthcare, Nycoveien 1, P.O. Box 4220, 0401 Oslo, Norway.
authors.forename: Tom Collin
authors.initials: TC
authors.lastname: Soosainather
authors.affiliation: University of Oslo, School of Pharmacy, Department of Pharmacy, P.O. Box 1068, Blindern, N-0316 Oslo, Norway; KD Metrix, Spireaveien 10A, 0580 Oslo, Norway.
authors.forename: Knut
authors.initials: K
authors.lastname: Dyrstad
authors.affiliation: University of Oslo, School of Pharmacy, Department of Pharmacy, P.O. Box 1068, Blindern, N-0316 Oslo, Norway.
authors.forename: Sverre Arne
authors.initials: SA
authors.lastname: Sande
mesh_terms: D003287:Contrast Media / Q000737:chemistry / Q000145:classification*; D016002:Discriminant Analysis; D016018:Least-Squares Analysis; D015233:Models, Statistical; D019265:Spectroscopy, Near-Infrared / Q000379:methods*
chemical_list: D003287:Contrast Media
keywords: %ICC; BVE-PLS; BiPLS; CSMWPLS; LV; MIPCR; MRI; MWPLS; Main and Interactions of Individual Principal Components Regression; Main and Interactions of Individual Principal Components Regression (MIPCR); Multivariate classification; NIRS; Near infrared spectroscopy (NIRS); PAT; PC; PCA; PLS-DA; PLSR; Partial least squares discriminant analysis (PLS-DA); RMSECV; SCMWPLS; SIMCA; SNV; SVM; Soft independent modelling of class analogy (SIMCA); Standard Normal Variate; backward interval partial least squares; backward variable elimination partial least squares regression; changeable size moving window partial least squares; iPLS; incorrect classification rate; interval partial least squares; latent variables; magnetic resonance imaging; moving window partial least squares; near infrared spectroscopy; partial least squares discriminant analysis; partial least squares regression; principal component; principal component analysis; process analytical technology; root mean square error of cross validation; search combination moving window partial least squares; soft independent modelling of class analogy; support vector machine