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The purpose of this research is to develop a multiple linear regression model to predict the intention to vaccinate for COVID-19. An anonymous cross-sectional online survey utilizing Qualtrics software was conducted. Descriptive statistics and inter-correlations between predictors and criterion variables were presented. Multiple linear regression was used to analyze associations among predictors and criterion variables. Overall, results indicated that while 79% of participants reported their intentions to get vaccinated against COVID-19 when a vaccine becomes available, 21% reported not being likely to. Further, results showed that six socio-demographic, health-related, and belief factors had positive effects on intentions to vaccinate for COVID-19. Specifically, the predictive variables of the belief in the effectiveness of the COVID-19 vaccine, political party affiliation, previous influenza vaccinations, employment status, perceived knowledge of COVID-19 and the COVID-19 vaccine, as well as education level have crucial roles in predicting the dependent variable of the intention to vaccinate for COVID-19. This research contributes to our understanding of the various factors that influence the decision to vaccinate for COVID-19. Overall, the proposed regression model with the variables present in this study represents a strong effect and explains the proportion of the variability in the intention to vaccinate with over 70% accuracy. These results have important practical as well as theoretical implications for public health policymakers. With significant percentages of the population that are still hesitant to vaccinate, future studies should focus on finding this missing link and implementing any social/public health policies to level up individual intentions.

The purpose of this research is to develop a multiple linear regression model to predict the intention to vaccinate for COVID-19. An anonymous cross-sectional online survey utilizing Qualtrics software was conducted. Descriptive statistics and inter-correlations between predictors and criterion variables were presented. Multiple linear regression was used to analyze associations among predictors and criterion variables. Overall, results indicated that while 79% of participants reported their intentions to get vaccinated against COVID-19 when a vaccine becomes available, 21% reported not being likely to. Further, results showed that six socio-demographic, health-related, and belief factors had positive effects on intentions to vaccinate for COVID-19. Specifically, the predictive variables of the belief in the effectiveness of the COVID-19 vaccine, political party affiliation, previous influenza vaccinations, employment status, perceived knowledge of COVID-19 and the COVID-19 vaccine, as well as education level have crucial roles in predicting the dependent variable of the intention to vaccinate for COVID-19. This research contributes to our understanding of the various factors that influence the decision to vaccinate for COVID-19. Overall, the proposed regression model with the variables present in this study represents a strong effect and explains the proportion of the variability in the intention to vaccinate with over 70% accuracy. These results have important practical as well as theoretical implications for public health policymakers. With significant percentages of the population that are still hesitant to vaccinate, future studies should focus on finding this missing link and implementing any social/public health policies to level up individual intentions.

The purpose of this research is to develop a multiple linear regression model to predict the intention to vaccinate for COVID-19. An anonymous cross-sectional online survey utilizing Qualtrics software was conducted. Descriptive statistics and inter-correlations between predictors and criterion variables were presented. Multiple linear regression was used to analyze associations among predictors and criterion variables. Overall, results indicated that while 79% of participants reported their intentions to get vaccinated against COVID-19 when a vaccine becomes available, 21% reported not being likely to. Further, results showed that six socio-demographic, health-related, and belief factors had positive effects on intentions to vaccinate for COVID-19. Specifically, the predictive variables of the belief in the effectiveness of the COVID-19 vaccine, political party affiliation, previous influenza vaccinations, employment status, perceived knowledge of COVID-19 and the COVID-19 vaccine, as well as education level have crucial roles in predicting the dependent variable of the intention to vaccinate for COVID-19. This research contributes to our understanding of the various factors that influence the decision to vaccinate for COVID-19. Overall, the proposed regression model with the variables present in this study represents a strong effect and explains the proportion of the variability in the intention to vaccinate with over 70% accuracy. These results have important practical as well as theoretical implications for public health policymakers. With significant percentages of the population that are still hesitant to vaccinate, future studies should focus on finding this missing link and implementing any social/public health policies to level up individual intentions.

Globally, CO2 emissions have increased over the last decades. This trend has been broken in Sweden, where CO2 emissions are declining. Oil is one of Sweden's largest sources of energy, accounting for over 20 % of all energy consumption, and oil combustion is a large source of CO2 emissions. This paper aims to answer the question, “How have oil prices impacted carbon dioxide emissions in Sweden?” which is relevant for policy-making regarding emission reduction, as it can explain how effective economic instruments are in reducing CO2 emissions from oil. The study is conducted by setting up a Multiple Linear Regression Model where the correlational effects of oil prices on CO2 emissions are studied, as well as the effects of control variables. Sweden is the only country studied, between 1980 and 2021, by looking at monthly data. The effects of the oil price increases were lagged to see the effects in different months after the price increase. The results were that oil price increases lead to an immediate increase in CO2 emissions while decreasing after a more extended time. The direct effects of an oil price increase suggest that increases in oil price increase CO2 emissions by 0.179 kg per capita and month, which according to economic theory is inaccurate. In the longer time frame, CO2 emissions were shown to be reduced by between 0.24 to 0.42 kg per capita depending on the time after the price increase. However, because of possible biases and endogeneity occurring in this study, the results will explain the correlation between oil prices and CO2 emissions, and not the cause-and-effect relationship. There is therefore no proof of causality in this study. Previous research has suggested that oil demand is inelastic, meaning demand does not change much due to price changes. Here, the opposite is proven since significant effects are found from price changes in oil. These results are important for how policies should be introduced in the future since it found that oil pri

The purpose of this research is to develop a multiple linear regression model to predict the intention to vaccinate for COVID-19. An anonymous cross-sectional online survey utilizing Qualtrics software was conducted. Descriptive statistics and inter-correlations between predictors and criterion variables were presented. Multiple linear regression was used to analyze associations among predictors and criterion variables. Overall, results indicated that while 79% of participants reported their intentions to get vaccinated against COVID-19 when a vaccine becomes available, 21% reported not being likely to. Further, results showed that six socio-demographic, health-related, and belief factors had positive effects on intentions to vaccinate for COVID-19. Specifically, the predictive variables of the belief in the effectiveness of the COVID-19 vaccine, political party affiliation, previous influenza vaccinations, employment status, perceived knowledge of COVID-19 and the COVID-19 vaccine, as well as education level have crucial roles in predicting the dependent variable of the intention to vaccinate for COVID-19. This research contributes to our understanding of the various factors that influence the decision to vaccinate for COVID-19. Overall, the proposed regression model with the variables present in this study represents a strong effect and explains the proportion of the variability in the intention to vaccinate with over 70% accuracy. These results have important practical as well as theoretical implications for public health policymakers. With significant percentages of the population that are still hesitant to vaccinate, future studies should focus on finding this missing link and implementing any social/public health policies to level up individual intentions.

Various studies have focused on estimating the price of cryptocurrencies using time series models and static variables. This study focuses on Bitcoin price prediction, using a model that combines multiple linear regression and neural networks. This approach makes it possible to identify the factors that influence Bitcoin volatility and, through a dynamic selection of variables, to constantly detect the most relevant set of characteristics for prediction. Likewise, the amount of data is optimized to improve precision and avoid overuse of historical information. The combination of these techniques captures underlying patterns and trends, increasing the reliability of predictions, with an accuracy of 88%. However, it is crucial to consider the need for continuous evaluations to adapt to changing market conditions. This approach provides a more accurate tool for making informed decisions in a highly volatile market., Diversos estudios se han enfocado en estimar el precio de las criptomonedas utilizando modelos de series de tiempo y variables estáticas. Este estudio se centra en la predicción del precio de Bitcoin, utilizando un modelo que combina la regresión lineal múltiple y las redes neuronales. Este enfoque permite identificar los factores que influyen en la volatilidad de Bitcoin y, mediante una selección dinámica de variables, detectar constantemente el conjunto de características más relevante para la predicción. Asimismo, se optimiza la cantidad de datos para mejorar la precisión y evitar la sobreutilización de información histórica. La combinación de estas técnicas permitió capturar patrones y tendencias subyacentes, aumentando la confiabilidad de las predicciones, con una precisión del 88%. Sin embargo, es crucial considerar la necesidad de evaluaciones continuas para adaptarse a las cambiantes condiciones del mercado. Este enfoque brinda una herramienta más precisa para tomar decisiones informadas en un mercado altamente volátil.

Este estudio tiene como objetivo determinar la influencia la implementación de buenas prácticas del gobierno corporativo en la rentabilidad del patrimonio de Empresas Públicas de Medellín. Por lo cual se tomaron datos trimestrales en el período comprendido entre 2012 y 2020, elaborando un índice de gobierno corporativo y desarrollando un modelo de regresión lineal múltiple en busca de la correlación directa entre el ROE, el índice y los indicadores financieros establecidos. Los resultados indican que el índice de gobierno corporativo influye en la gestión de la rentabilidad del patrimonio y del activo de E.P.M., The objective of this study is to determine the influence of the implementation of good corporate governance practices on the return on equity of Empresas Públicas de Medellín. Therefore, quarterly data were taken for the period between 2012 and 2020, elaborating a corporate governance index and developing a multiple linear regression model in search of the direct correlation between ROE, the index and the established financial indicators. The results indicate that the corporate governance index influences E.P.M.'s return on equity and return on assets management.

A reasonable number of studies on the effect of Female life expectancy (FLE) upon the quality of women's lives in developed countries have been done. Bangladesh lacks such a study. We explore the effect of decreasing fertility and childhood mortality rates on FLE in Bangladesh and evaluate the potential impthe act of the demographic transition on GDP. Also, we investigate the trends and patterns of different factors from 1995 to 2018. Partial Least Squares-Structural Equation Modeling (PLS-SEM) is functioned to fit an appropriate model to link fertility, GDP, and childhood mortality with FLE. The significance of the relationships has also been assessed. Results indicate that declines in fertility and childhood mortality have made significant improvements in FLE. The prospects of demographic transition due to fertility decline have been analyzed, and challenges to achieve it are highlighted.

A standardized website evaluation model is needed in the tourism sector. This research article aims at revising previous models and updating them to contribute with a unified evaluation model for the analysis of web quality that incorporates a three-dimensional approach on usability, since usability is closely related to graphic design and navigability. This perspective has not been stated before. To test this correlation, a model to evaluate User Usable Experience (UUX) which integrates this three-dimensional approach on usability is proposed and a set of indicators that have been devised from a close bibliographic revision of previous web analysis models is shown. Its application to a purposive sampling verifies the positive correlation among the three above mentioned parameters by means of a multiple linear regression model. The results confirm the need to analyse UUX from a three-dimensional perspective on usability.

A standardized website evaluation model is needed in the tourism sector. This research article aims at revising previous models and updating them to contribute with a unified evaluation model for the analysis of web quality that incorporates a three-dimensional approach on usability, since usability is closely related to graphic design and navigability. This perspective has not been stated before. To test this correlation, a model to evaluate User Usable Experience (UUX) which integrates this three-dimensional approach on usability is proposed and a set of indicators that have been devised from a close bibliographic revision of previous web analysis models is shown. Its application to a purposive sampling verifies the positive correlation among the three above mentioned parameters by means of a multiple linear regression model. The results confirm the need to analyse UUX from a three-dimensional perspective on usability.

The company’s social responsibility, also called corporate social responsibility (CSR), is considered a key strategic factor in management. The purpose of this paper is to analyze the existing relationships between the CSR principles and the profitability of companies in the construction sector in Galicia. To this end, a review of the concept of CSR and its evolution is made; then, an analysis of the relationship between CSR and business results for Galician companies of the construction sector is carried out; finally, quantitative indicators are developed to evaluate the management and performance of the company and the theoretical approaches are compared with the results obtained through econometric modeling for a sample of 100 companies. This comparative analysis is done through return on assets (ROA,) or economic profitability, and return on equity (ROE), or financial profitability. We conclude that there is a positive relationship between financial returns and CSR, so the latter is consolidated as a source of competitive advantage, A Responsabilidade Social da Empresa (RSE), tamén denominada Responsabilidade Social Corporativa (RSC), formúlase como un factor estratéxico clave na xestión. O obxecto deste traballo é analizar as relacións existentes entre os principios de RSE e a rendibilidade das empresas do sector da construción en Galicia. Para iso realízase unha revisión do concepto de RSE e da súa evolución; a continuación analízase a relación entre a RSE e os resultados empresariais a nivel global para empresas galegas representativas do sector da construción; e, por último, desenvólvense indicadores cuantitativos que permiten avaliar a xestión e o desempeño na empresa e contrástanse as formulacións teóricas cos resultados obtidos a través da modelización econométrica para unha mostra de 100 empresas. A análise comparativa realízase a través da rendibilidade sobre activos ou económica (ROA, Return On Assets) e a rendibilidade, sobre fondos propios ou financeira (ROE, Return On Equity). Concluímos que existe unha relación positiva entre os rendementos financeiros e a RSE, polo que esta se consolida como fonte de vantaxe competitiva, La Responsabilidad Social de la Empresa (RSE), también denominada Responsabilidad Social Corporativa (RSC), se plantea como un factor estratégico clave en la gestión. El objeto de este trabajo es analizar las relaciones existentes entre los principios de RSE y la rentabilidad de las empresas del sector de la construcción en Galicia. Para ello se realiza una revisión del concepto de RSE y de su evolución; a continuación se analiza la relación entre la RSE y los resultados empresariales a nivel global para empresas gallegas representativas del sector de la construcción; y, por último se desarrollan indicadores cuantitativos que permiten evaluar la gestión y el desempeño en la empresa y se contrastan los planteamientos teóricos con los resultados obtenidos a través de la modelización econométrica para una muestra de 100 empresas. El análisis comparativo se realiza a través de la rentabilidad sobre activos o económica (ROA, Return On Assets) y la rentabilidad sobre fondos propios o financiera (ROE, Return On Equity). Concluimos que existe una relación positiva entre los rendimientos financieros y la RSE, por lo que esta se consolida como fuente de ventaja competitiva

The company’s social responsibility, also called corporate social responsibility (CSR), is considered a key strategic factor in management. The purpose of this paper is to analyze the existing relationships between the CSR principles and the profitability of companies in the construction sector in Galicia. To this end, a review of the concept of CSR and its evolution is made; then, an analysis of the relationship between CSR and business results for Galician companies of the construction sector is carried out; finally, quantitative indicators are developed to evaluate the management and performance of the company and the theoretical approaches are compared with the results obtained through econometric modeling for a sample of 100 companies. This comparative analysis is done through return on assets (ROA,) or economic profitability, and return on equity (ROE), or financial profitability. We conclude that there is a positive relationship between financial returns and CSR, so the latter is consolidated as a source of competitive advantage, A Responsabilidade Social da Empresa (RSE), tamén denominada Responsabilidade Social Corporativa (RSC), formúlase como un factor estratéxico clave na xestión. O obxecto deste traballo é analizar as relacións existentes entre os principios de RSE e a rendibilidade das empresas do sector da construción en Galicia. Para iso realízase unha revisión do concepto de RSE e da súa evolución; a continuación analízase a relación entre a RSE e os resultados empresariais a nivel global para empresas galegas representativas do sector da construción; e, por último, desenvólvense indicadores cuantitativos que permiten avaliar a xestión e o desempeño na empresa e contrástanse as formulacións teóricas cos resultados obtidos a través da modelización econométrica para unha mostra de 100 empresas. A análise comparativa realízase a través da rendibilidade sobre activos ou económica (ROA, Return On Assets) e a rendibilidade, sobre fondos propios ou financeira (ROE, Return On Equity). Concluímos que existe unha relación positiva entre os rendementos financeiros e a RSE, polo que esta se consolida como fonte de vantaxe competitiva, La Responsabilidad Social de la Empresa (RSE), también denominada Responsabilidad Social Corporativa (RSC), se plantea como un factor estratégico clave en la gestión. El objeto de este trabajo es analizar las relaciones existentes entre los principios de RSE y la rentabilidad de las empresas del sector de la construcción en Galicia. Para ello se realiza una revisión del concepto de RSE y de su evolución; a continuación se analiza la relación entre la RSE y los resultados empresariales a nivel global para empresas gallegas representativas del sector de la construcción; y, por último se desarrollan indicadores cuantitativos que permiten evaluar la gestión y el desempeño en la empresa y se contrastan los planteamientos teóricos con los resultados obtenidos a través de la modelización econométrica para una muestra de 100 empresas. El análisis comparativo se realiza a través de la rentabilidad sobre activos o económica (ROA, Return On Assets) y la rentabilidad sobre fondos propios o financiera (ROE, Return On Equity). Concluimos que existe una relación positiva entre los rendimientos financieros y la RSE, por lo que esta se consolida como fuente de ventaja competitiva

Esta investigación pretende a partir de un modelo de regresión lineal múltiple, crear un aporte empírico para determinar cómo las características y habilidades de los gerentes, además de las variables financieras tradicionalmente utilizadas, se relacionan e impactan la rentabilidad y sostenibilidad de las micro, pequeñas y medianas empresas en el contexto colombiano. Para lograr este objetivo, se utilizó la información financiera y gerencial del año 2016 de 35 compañías MiPymes colombianas de diferentes sectores económicos; se calcularon 25 ratios financieros a través de los estados financieros, se midieron 10 habilidades gerenciales a través de encuestas y se definieron 10 variables de caracterización relacionadas con cada empresa y su gerente para ser utilizadas como variables independientes en un modelo de regresión lineal múltiple utilizando el Margen EBITDA como variable dependiente con el fin de representar la rentabilidad y sostenibilidad de estas compañías. Se encontró que algunas variables de caracterización propias de los gerentes y altos directivos de las compañías, como su auto-confianza, su afinidad para enfrentar nuevos desafíos, su rol, entre otros, afectan de manera significativa el comportamiento del Margen EBITDA demostrando que existe una relación entre la manera cómo estos gerentes toman decisiones y el desempeño de la empresa., This research aims to create, from a multiple linear regression model, an empirical contribution to determine how the characteristics and skills of managers, in addition to the financial variables traditionally used, relate to and impact the profitability and sustainability of micro, small and medium-sized companies in the Colombian context. To achieve this objective, we used the financial and managerial information of 2016 of 35 Colombian MiPymes companies from different economic sectors; 25 financial ratios were calculated through the financial statements, 10 management skills were measured through surveys and 10 characterization variables were defined related to each company and its manager to be used as independent variables in a multiple linear regression model using the EBITDA margin as a dependent variable in order to represent the profitability and sustainability of these companies. It was found that some characteristic variables of the managers and senior managers of the companies, such as their self-confidence, their affinity to face new challenges, their role, among others, significantly affect the behavior of the EBITDA Margin, demonstrating that there is a relationship between the way these managers make decisions and the performance of the company.

[Resumo] A Responsabilidade Social da Empresa (RSE), tamén denominada Responsabilidade Social Corporativa (RSC), formúlase como un factor estratéxico clave na xestión. O obxecto deste traballo é analizar as relacións existentes entre os principios de RSE e a rendibilidade das empresas do sector da construción en Galicia. Para iso realízase unha revisión do concepto de RSE e da súa evolución; a continuación analízase a relación entre a RSE e os resultados empresariais a nivel global para empresas galegas representativas do sector da construción; e, por último, desenvólvense indicadores cuantitativos que permiten avaliar a xes-tión e o desempeño na empresa e contrástanse as formulacións teóricas cos resultados obtidos a través da modelización eco-nométrica para unha mostra de 100 empresas. A análise comparativa realízase a través da rendibilidade sobre activos ou económica (ROA, Return On Assets) e a rendibilidade, sobre fondos propios ou financeira (ROE, Return On Equity). Concluímos que existe unha relación positiva entre os rendementos financeiros e a RSE, polo que esta se consolida como fonte de vantaxe competitiva., [Resumen] La Responsabilidad Social de la Empresa (RSE), también denominada Responsabilidad Social Corporativa (RSC), se plantea como un factor estratégico clave en la gestión. El objeto de este trabajo es analizar las relaciones existentes entre los princi-pios de RSE y la rentabilidad de las empresas del sector de la construcción en Galicia. Para ello se realiza una revisión del con-cepto de RSE y de su evolución; a continuación se analiza la relación entre la RSE y los resultados empresariales a nivel global para empresas gallegas representativas del sector de la construcción; y, por último se desarrollan indicadores cuantitativos que permiten evaluar la gestión y el desempeño en la empresa y se contrastan los planteamientos teóricos con los resultados obtenidos a través de la modelización econométrica para una muestra de 100 empresas. El análisis comparativo se realiza a través de la rentabilidad sobre activos o económica (ROA, Return On Assets) y la rentabilidad sobre fondos propios o finan-ciera (ROE, Return On Equity). Concluimos que existe una relación positiva entre los rendimientos financieros y la RSE, por lo que esta se consolida como fuente de ventaja competitiva., [Abstract] The company’s social responsibility, also called corporate social responsibility (CSR), is considered a key strategic factor in management. The purpose of this paper is to analyze the existing relationships between the CSR principles and the profitabil-ity of companies in the construction sector in Galicia. To this end, a review of the concept of CSR and its evolution is made; then, an analysis of the relationship between CSR and business results for Galician companies of the construction sector is carried out; finally, quantitative indicators are developed to evaluate the management and performance of the company and the theoretical approaches are compared with the results obtained through econometric modeling for a sample of 100 com-panies. This comparative analysis is done through return on assets (ROA,) or economic profitability, and return on equity (ROE), or financial profitability. We conclude that there is a positive relationship between financial returns and CSR, so the latter is consolidated as a source of competitive advantage.

This paper presents a comprehensive statistical evaluation of the conductivity performance of PEDOT/PSS films generated at various spin coating speeds (1000 to 5000 rpm) by correspondence analysis (CA), regression and ANOVA models. Poly(3,4-ethylenedioxythiophene) (PEDOT) is a highly conducting insoluble polymer which, when doped with poly(styrene sulfonic acid) (PSS) in water, results in a dispersion with good film forming properties. Our interest in PEDOT/PSS is in its application as an interfacial layer and gate electrode in organic photovoltaic and organic field effect transistor devices, respectively. The generation of a homogeneous spun-cast layer of PEDOT/PSS over the entire substrate for these intended applications is a function of the spin-coating speed which, in turn, affects the thickness of the film and, consequently, its conductivity measured by the four point probe. From correspondence analysis, we find that only the 1000 rpm spin-coating speed is strongly associated with high thickness and high resistivity (i.e. low conductivity), although further analysis of speeds 2000 - 5000 rpm shows that the spin-coating speed is still associated with the thickness of the films, and subsequently, their conductivities, such that the thinnest and most conductive films result from the highest spin-coating speed (5000 rpm). We also observed the phenomenon of the horseshoe effect from the CA displays and discussed the reasons for not resorting to detrending solutions for dealing with its presence. From multiple and nonlinear regression models, spin-coating speeds 1000 and 2000 rpm were found to produce films of less precise conductivity values as reflected in the absolute value of mean of residuals of nonlinear regression models while more precise and optimal conductivity values are obtained when the films are generated between 3000 and 5000 rpm. The ANOVA models showed that the means of conductivity of films obtained at 1000 rpm is statistically significantly differe

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallisation (onset of crystallisation) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental dataset obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature (Tg) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallisation (onset of crystallisation) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental dataset obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature (Tg) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallisation (onset of crystallisation) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental dataset obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature (Tg) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.