A review on multivariate curve resolution applied to spectroscopic and chromatographic data acquired during the real-time monitoring of evolving multi-component processes: From process analytical chemistry (PAC) to process analytical technology (PAT)

• Type: Another Publication in an International Scientific Journal
• Date: 2022

Authors

Mazivila, SJ (Author) Other; Joao L M Santos (Author) FFUP

Journal

Title: TrAC - Trends in Analytical Chemistry

Vol. 157

ISSN: 0165-9936

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 0 Citations

Other information

Authenticus ID: P-00W-Y6F

DOI: 10.1016/j.trac.2022.116698

Abstract (EN): This review addresses the most important results arising from the combination of multivariate curve resolution -alternating least-squares (MCR-ALS) with both spectroscopic and chromatographic data acquired throughout the real-time monitoring of the evolution of distinct multi-component processes. The word ???process??? should be interpreted as any event occurring in an evolving system, such as a (bio) chemical reaction, a physical transformation, or a chromatographic elution. This work aims to review the progress and evolving stages that took place in real-time process monitoring and control between the closely related process analytical chemistry (PAC) and process analytical technology (PAT), from the perspective of the utilization of spectroscopic and chromatographic techniques coupled to MCR-ALS. The selection of MCR-ALS model is eminently supported by the ability of its internal algorithms to provide uniquely resolved pure concentration profiles and spectral signatures of each involved components with physicochemical meaning regarding the in-situ monitored process, establishing the definite quality-by -design (QbD) approach. These chemically interpretable insights of evolving multi-component processes are attained after successful data decomposition of the full acquired signals with the aid of the so-called second-order advantage, even when handling first-order data. This data decomposition, carried out by using MCR-ALS, can assist process chemists, PAT scientists, analytical chemists, and process engineers in the implementation of productive pioneering modeling under both the PAC and PAT frameworks via real-time processing of workflow data acquired during the entire monitored process in order to gain in-depth process understanding. In this sense, emphasis is directed to significant advances reached at distinct fields, such as: i) the curing process of epoxy resins; ii) biodiesel production; iii) degradation and removal of high concern emerging contaminants in environmental samples; iv) pharmaceutical co-crystallization process; v) polymorphic phase transitions occurring during the processing/storage of solid dosage forms; vi) polymorphic transformations endured by a solid pharmaceutical drug during its dissolution process. The previously mentioned topics are addressed seeking to establish a well-defined state-of-the-art of the implemented approaches, which are expected to inspire future research trends in real-time process monitoring under the scope of the emerging digital manufacturing process, which is a declared milestone of the forthcoming Industry 4.0 or fourth industrial revolution. ?? 2022 Elsevier B.V. All rights reserved.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 26