Quantitative analysis of active pharmaceutical ingredients (APIs) using a potentiometric electronic tongue in a SIA flow system
An advanced potentiometric electronic tongue and Sequential Injection Analysis (SIA) measurement system was applied for the quantitative analysis of mixtures containing three active pharmaceutical ingredients (APIs): acetaminophen, ascorbic acid and acetylsalicylic acid, in the presence of various a...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:154708 |
| Acceso en línea: | https://ddd.uab.cat/record/154708 https://dx.doi.org/urn:doi:10.1002/elan.201500407 |
| Access Level: | acceso abierto |
| Palabra clave: | Pharmaceutical analysis Active pharmaceutical ingredients (APIs) Ion-selective electrodes Automated electronic tongue Sequential injection analysis |
| Sumario: | An advanced potentiometric electronic tongue and Sequential Injection Analysis (SIA) measurement system was applied for the quantitative analysis of mixtures containing three active pharmaceutical ingredients (APIs): acetaminophen, ascorbic acid and acetylsalicylic acid, in the presence of various amounts of caffeine as interferent. The flow-through sensor array was composed of miniaturized classical ion-selective electrodes based on plasticized PVC membranes containing only ion exchangers. Partial Least Squares (PLS) analysis of the steady-state sensor array responses, measured in API mixtures prepared by the SIA system permitted a correct quantitative analysis of acetylsalicylic acid and ascorbic acid. Further optimization using multiway PLS fed by dynamic responses without additional feature extraction did not improve significantly the resolution of acetaminophen. Lastly, the chemometric treatment, involving the extraction of dynamic components of the transient response employing the Wavelet transform, the removal of less-significant coefficients by means of Causal Index pruning and training of an Artificial Neural Network (ANN) with the selected coefficients, allowed the simultaneous determination of all the three studied APIs, while counterbalancing any interference due to caffeine. |
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