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 language | English |
|---|---|
| Title of host publication | Artificial Intelligence and Cognitive Science - 30th Irish Conference, AICS 2022, Revised Selected Papers |
| Editors | Luca Longo, Ruairi O’Reilly |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 106-120 |
| Number of pages | 15 |
| ISBN (Print) | 9783031264375 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 30th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2022 - Munster, Ireland Duration: 8 Dec 2022 → 9 Dec 2022 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 1662 CCIS |
| ISSN (Print) | 1865-0929 |
| ISSN (Electronic) | 1865-0937 |
Conference
| Conference | 30th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2022 |
|---|---|
| Country/Territory | Ireland |
| City | Munster |
| Period | 8/12/22 → 9/12/22 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- ATR-FTIR
- Chemometric
- Machine learning
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