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Drugs solubility prediction in mono-solvents at various temperatures using a minimum number of experimental data points
Predicción de solubilidad de fármacos en mono-solventes a varias temperaturas utilizando un número mínimo de puntos de datos experimentales
Previsão de solubilidade de drogas em monossolventes em várias temperaturas usando um número mínimo de pontos de dados experimentais
DOI:
https://doi.org/10.15446/rcciquifa.v52n2.110747Palabras clave:
Solubility prediction, extrapolation method , mono-solvent systems , van’t Hoff equation, Hansen parameters, Catalan parameters (en)Predicción de solubilidad , método de extrapolación, sistemas monosolventes , ecuación de van’t Hoff , parámetros de Hansen , parámetros de Catalán (es)
Previsão de solubilidade, método de extrapolação , sistemas monossolvente , equação de van’t Hoff , Parâmetros de Hansen , Parâmetros catalães (pt)
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Introduction: Solubility is one of the most basic information in a re-crystallization process and in many cases, there are only a few grams (or even mg or mg) of an expensive pharmaceutical or fine chemical to make a large number of crystallization tests. Aim: To develop a computational procedure for prediction of drugs solubility in any mono-solvent and temperature of interest using a minimum number of experimental data points. Methods: For achieving this purpose, here, the available solubility data sets were collected from the recently published articles and selected a minimum data point of each dataset to train a simple model based on the well-known van’t Hoff equation combined with Abraham, Hansen and Catalan parameters as variables presenting the drug-solvent interactions in the solutions. After obtaining the model parameters, the next solubility data in each dataset was predicted by extrapolation method and the accuracy of model was estimated using the computation the mean percentage deviation of the back-calculated data. Results: The model adequately trained using a minimum data point could be used as a practical strategy for predicting the solubility of drugs in mono-solvents at different temperatures with acceptable prediction error and using minimum experimental efforts.
Introducción: la solubilidad es una de las informaciones más básicas en un proceso de recristalización y, en muchos casos, solo hay unos pocos gramos (o incluso mg o mg) de un producto farmacéutico o químico fino costoso para realizar una gran cantidad de pruebas de cristalización. Objetivo: desarrollar un procedimiento computacional para la predicción de la solubilidad de los fármacos en cualquier mono-solvente y la temperatura de interés utilizando un número mínimo de puntos de datos experimentales. Método: para lograr este propósito, aquí, los conjuntos de datos de solubilidad disponibles se recopilaron de los artículos publicados recientemente y se seleccionaron puntos de datos mínimos de cada conjunto de datos para entrenar un modelo simple basado en la conocida ecuación de van’t Hoff combinada con los parámetros de Abraham, Hansen, Catalán, como variables de presentación de las interacciones fármaco-disolvente en las soluciones. Después de obtener los parámetros del modelo, los siguientes datos de solubilidad en cada conjunto de datos se predijeron mediante el método de extrapolación y la precisión del modelo se estimó mediante el cálculo de la desviación porcentual media de los datos retrocalculados. Resultados: el modelo entrenado adecuadamente utilizando puntos de datos mínimos podría utilizarse como una estrategia práctica para predecir la solubilidad de fármacos en mono-solventes a diferentes temperaturas con un error de predicción aceptable y utilizando esfuerzos experimentales mínimos.
Introdução: a solubilidade é uma das informações mais básicas em um processo de recristalização e, em muitos casos, existem apenas alguns gramas (ou mesmo mg ou mg) de um produto farmacêutico ou químico fino caro para fazer um grande número de testes de cristalização. Objetivo: desenvolver um procedimento computacional para prever a solubilidade de drogas em quaisquer monossolventes e temperatura de interesse usando um número mínimo de pontos de dados experimentais. Métodos: para atingir esse objetivo, aqui, os conjuntos de dados de solubilidade disponíveis foram coletados dos artigos publicados recentemente e selecionados um mínimo de pontos de dados de cada conjunto de dados para treinar um modelo simples baseado na conhecida equação de van’t Hoff combinada com os parâmetros de Abraham, Hansen e Catalan como variáveis apresentando as interações fármaco-solvente nas soluções. Depois de obter os parâmetros do modelo, os próximos dados de solubilidade em cada conjunto de dados foram previstos pelo método de extrapolação e a precisão do modelo foi estimada usando o cálculo do desvio percentual médio dos dados calculados de volta. Resultados: o modelo adequadamente treinado usando um mínimo de pontos de dados pode ser usado como uma estratégia prática para predizer a solubilidade de drogas em monossolventes em diferentes temperaturas com erro de predição aceitável e usando esforços experimentais mínimos.
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