Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Chemometric Methods for Spectroscopy-Based Pharmaceutical Analysis

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Spectroscopy is widely used to characterize pharmaceutical products or processes, especially due to its desirable characteristics of being rapid, cheap, non-invasive/non-destructive and applicable both off-line and in-/at-/on-line. Spectroscopic techniques produce profiles containing a high amount of information, which can profitably be exploited through the use of multivariate mathematic and statistic (chemometric) techniques. The present paper aims at providing a brief overview of the different chemometric approaches applicable in the context of spectroscopy-based pharmaceutical analysis, discussing both the unsupervised exploration of the collected data and the possibility of building predictive models for both quantitative (calibration) and qualitative (classification) responses.

          Related collections

          Most cited references51

          • Record: found
          • Abstract: not found
          • Article: not found

          The Generalization of Student's Ratio

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Pattern recognition by means of disjoint principal components models

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              A Note on the Use of Principal Components in Regression

                Bookmark

                Author and article information

                Contributors
                Journal
                Front Chem
                Front Chem
                Front. Chem.
                Frontiers in Chemistry
                Frontiers Media S.A.
                2296-2646
                21 November 2018
                2018
                : 6
                : 576
                Affiliations
                Department of Chemistry, University of Rome La Sapienza , Rome, Italy
                Author notes

                Edited by: Cosimino Malitesta, University of Salento, Italy

                Reviewed by: Daniel Cozzolino, Central Queensland University, Australia; Andreia Michelle Smith-Moritz, University of California, Davis, United States

                *Correspondence: Federico Marini federico.marini@ 123456uniroma1.it

                This article was submitted to Analytical Chemistry, a section of the journal Frontiers in Chemistry

                Article
                10.3389/fchem.2018.00576
                6258797
                30519559
                2273569c-98e5-4249-abf9-38b0bf776e53
                Copyright © 2018 Biancolillo and Marini.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 July 2018
                : 05 November 2018
                Page count
                Figures: 4, Tables: 0, Equations: 0, References: 61, Pages: 14, Words: 10215
                Categories
                Chemistry
                Review

                spectroscopy,chemometrics and statistics,component analysis (pca),partial least squares (pls),classification,partial least squares discriminant analysis (pls-da),soft independent modeling of class analogies (simca),pharmaceutical quality control

                Comments

                Comment on this article