Development of spectroscopic methods for assessing polymorphic content of efavirenz
The present work aimed to develop a new method for assessing the content of mixtures of polymorphic forms I and II of the drug Efavirenz (EFV) by vibrational spectroscopic techniques such as Middle (MIR) and Near (NIR) infrared and Raman, using multivariate calibration models. Benchtop and handheld...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade de São Paulo (USP) |
| Repositorio: | Brazilian Journal of Pharmaceutical Sciences |
| Idioma: | inglés |
| OAI Identifier: | oai:revistas.usp.br:article/231122 |
| Acceso en línea: | https://www.revistas.usp.br/bjps/article/view/231122 |
| Access Level: | acceso abierto |
| Palabra clave: | Efavirenz Infrared spectroscopy Near-infrared spectroscopy Partial least squares Polymorph(s) Raman spectroscopy |
| Sumario: | The present work aimed to develop a new method for assessing the content of mixtures of polymorphic forms I and II of the drug Efavirenz (EFV) by vibrational spectroscopic techniques such as Middle (MIR) and Near (NIR) infrared and Raman, using multivariate calibration models. Benchtop and handheld instruments were used for NIR and Raman and a benchtop instrument for MIR. In addition, VIP scores and iPLS, variable selection methods were employed. The infrared techniques showed the best models, with Root Mean Squares Error (RMSE) around 5% (w/w). When MIR and portable NIR instruments were used, this value was lowered to 4% (w/w) with selection of variables by iPLS. Raman spectroscopy showed higher error, even with selection of variables, possibly due to the spot laser size used by instruments and the lack of uniformity of the particle size in the samples. The infrared methods developed were shown to be effective in quantifying polymorphic mixtures of EFV. Given the ease of use of handheld instruments, they may be applied as tools of process analytical technology for monitoring quality control during industrial processing. |
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