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Correlation of pazopanib solubility in (ethyl acetate + ethanol) and (ethyl acetate + 2-propanol) cosolvent mixtures at different temperatures using different mathematical models
Correlación de la solubilidad de pazopanib en mezclas de cosolventes (acetato de etilo + etanol) y (acetato de etilo + 2-propanol) a diferentes temperaturas utilizando diferentes modelos matemáticos
Correlação da solubilidade do pazopanibe em misturas de cossolventes (acetato de etila + etanol) e (acetato de etila + 2-propanol) em diferentes temperaturas usando diferentes modelos matemáticos
DOI:
https://doi.org/10.15446/rcciquifa.v55n2.124590Palabras clave:
Solubility, Pazopanib, Cosolvency, Mathematical models, Thermodynamics (en)Solubilidad, Pazopanib, Cosolvencia, Modelos matemáticos, Termodinámica (es)
Solubilidade, Pazopanibe, Cosolvência, Modelos matemáticos, Termodinâmica (pt)
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Objectives: To evaluate the predictive capacity and relevance of six mathematical models for correlating Pazopanib solubility in ethyl acetate + ethanol and ethyl acetate + 2-propanol cosolvent mixtures. Methods: A Python-based computational framework using nonlinear optimization algorithms (Levenberg-Marquardt) was employed to fit van't Hoff, Buchowski-Ksiazczak (lh), Apelblat, van't Hoff-Yaws, Wilson, and NRTL models to experimental data ranging from 288.15 K to 328.15 K. Results: Although three-parameter models (Apelblat and van't Hoff-Yaws) yielded nearly perfect statistical fits (R2 »0.9999), they suffered from severe multicollinearity and coefficients lacking physical significance. Two-parameter semi-empirical models, particularly van't Hoff and lh, demonstrated greater stability and thermodynamic consistency. Activity coefficient-based models (Wilson and NRTL) exhibited severe numerical instability and an order-of-magnitude increase in residual errors. Conclusions: For industrial design and solubility prediction, the van't Hoff and Buchowski-Ksiazczak models are technically superior due to their parsimony and statistical robustness, whereas activity-based models prove unreliable for this specific system.
Objetivo: Evaluar la capacidad predictiva y pertinencia de seis modelos matemáticos para correlacionar la solubilidad de Pazopanib en mezclas cosolventes de acetato de etilo con etanol y 2-propanol. Métodos: Se empleó un marco computacional en Python utilizando algoritmos de optimización no lineal (Levenberg-Marquardt) para ajustar los modelos de van't Hoff, Buchowski-Ksiazczak (lh), Apelblat, van't Hoff-Yaws, Wilson y NRTL a datos experimentales entre 288.15 K y 328.15 K. Resultados: Los modelos de tres parámetros (Apelblat y van't Hoff-Yaws) alcanzaron ajustes estadísticos superiores (R2 » 0.9999$), aunque presentaron multicolinealidad severa y coeficientes sin significado físico. Los modelos de dos parámetros, especialmente van't Hoff y lh, mostraron mayor estabilidad y consistencia termodinámica. Los modelos basados en coeficientes de actividad (Wilson y NRTL) exhibieron inestabilidad numérica y errores significativamente mayores, evidenciados en el análisis de residuales. Conclusiones: Para fines de diseño industrial y predicción, los modelos de van't Hoff y Buchowski-Ksiazczak son técnicamente superiores debido a su parsimonia y robustez estadística, mientras que los modelos de tres parámetros y de coeficientes de actividad resultan poco fiables para la caracterización termodinámica de este sistema.
Objetivos: Avaliar a capacidade preditiva e a pertinência de seis modelos matemáticos para correlacionar a solubilidade do Pazopanibe em misturas cossolventes de acetato de etila com etanol e 2-propanol. Métodos: Utilizou-se uma estrutura computacional em Python com algoritmos de otimização não linear (Levenberg-Marquardt) para ajustar os modelos de van't Hoff, Buchowski-Ksiazczak (lh) Apelblat, van't Hoff-Yaws, Wilson e NRTL a dados experimentais entre 288,15 K e 328,15 K. Resultados: Os modelos de três parâmetros (Apelblat e van't Hoff-Yaws) apresentaram os melhores ajustes estatísticos (R2 » 0,9999), porém exibiram problemas de multicolinearidade e falta de significado físico em seus coeficientes. Os modelos semiempíricos de dois parâmetros, especialmente van't Hoff e lh demonstraram maior estabilidade e consistência termodinâmica. Os modelos baseados em coeficientes de atividade (Wilson e NRTL) mostraram instabilidade numérica grave e parâmetros sem validade física. Conclusões: Para fins de projeto industrial, os modelos de van't Hoff e Buchowski-Ksiazczak são superiores devido à sua parcimônia e estabilidade estatística, sendo os mais recomendados para a predição da solubilidade neste sistema
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