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Rapid Quantification of NaDCC for Water Purification Tablets in Commercial Production Using ATR-FTIR Spectroscopy Based on Machine Learning Techniques

Research output: Chapter in Book/Report/Conference proceedingsConference proceedingpeer-review

Abstract

Accurate, fast and simple quantitative analysis of solid dosage forms is required for efficient pharmaceutical manufacturing. A spectroscopic analysis in ATR-FTIR (Attenuated Total Reflection-Fourier Transform Infrared) mode was developed for NaDCC (Sodium dichloroisocyanurate) quantification. This fast and low-cost method can be used to quantify NaDCC solid dosage forms using ATR-FTIR in absorbance mode in conjunction with partial least squares. A simple sampling procedure is included in the proposed experiment by just dissolving the samples in deionized water. An algorithm pipeline is also included for data cleaning, such as outlier removal, scatter correction, scaling, and mapping of the sample’s spectrum to a NaDCC concentration. In addition, a simple model based on Beer’s law was evaluated on a sub-range of. Furthermore, a variable selection algorithm shows minimum excipient interference from the sample matrix in addition to visual analysis. A statistical analysis of the proposed method shows that it demonstrates a promising result with a regression coefficient of 0.996 and recovery range of 95.5%–107%. As a result of the positive correlation of ATR-FTIR with NaDCC concentration, and in conjunction with the proposed method, this can serve as a clean, fast, affordable and eco-friendly method for pharmaceutical analysis.

Original languageEnglish
Title of host publicationArtificial Intelligence and Cognitive Science - 30th Irish Conference, AICS 2022, Revised Selected Papers
EditorsLuca Longo, Ruairi O’Reilly
PublisherSpringer Science and Business Media Deutschland GmbH
Pages106-120
Number of pages15
ISBN (Print)9783031264375
DOIs
Publication statusPublished - 2023
Event30th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2022 - Munster, Ireland
Duration: 8 Dec 20229 Dec 2022

Publication series

NameCommunications in Computer and Information Science
Volume1662 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference30th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2022
Country/TerritoryIreland
CityMunster
Period8/12/229/12/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • ATR-FTIR
  • Chemometric
  • Machine learning

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