The development of a multiple linear regression model for aiding formulation development of solid dispersions

As poor solubility continues to be problem for new chemical entities (NCEs) in medicines development the use and interest in solid dispersions as a formulation-based solution has grown. Solid dispersions, where a drug is typically dispersed in a molecular state within an amorphous water-soluble polymer, present a good strategy to significantly enhance the effective drug solubility and hence bioavailability of drugs. The main drawback of this formulation strategy is the inherent instability of the amorphous form. With the right choice of polymer and manufacturing method, sufficient stability can be accomplished. However, finding the right combination of carrier and manufacturing method can be challenging, being labour, time and material costly. Therefore, a knowledge based support tool based upon a statistically significant data set to help with the formulation process would be of great value in the pharmaceutical industry. Here, 60 solid dispersion formulations were produced using ten, poorly soluble, chemically diverse APIs, three commonly used polymers and two manufacturing methods (spray drying and hot-melt extrusion). A long term stability study, up to one year, was performed on all formulations at accelerated conditions. Samples were regularly checked for the onset of crystallisation during the period, using mainly, polarised light microscopy. The stability data showed a large variance in stability between, methods, polymers and APIs. No obvious trends could be observed. Using statistical modelling, the experimental data in combination with calculated and predicted physicochemical properties of the APIs, several multiple linear regression (MLR) models were built. These had a good adjusted R2 and most showed good predictability in leave-one-out cross validations. Additionally, a validation on half of the models (eg. those based on spray-drying models) using an external dataset showed excellent predictability, with the correct ranking of formulations and accurate prediction of stability. In conclusion, this work has provided important insight into the complex correlations between the physical stability of amorphous solid dispersions and factors such as manufacturing method, carrier and properties of the API. Due to the expansive number of formulations studied here, which is far greater than previously published in the literature in a single study, more general conclusions can be drawn about these correlations than has previously been possible. This thesis has shown the potential of using well-founded statistical models in the formulation development of solid dispersion and given more insight into the complexity of these systems and how stability of these is dependent on multiple factors

Multiple linear regression modelling to predict the stability of polymer-drug solid dispersions: comparison of the effects of polymers and manufacturing methods on solid dispersion stability

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

The development of a multiple linear regression model for aiding formulation development of solid dispersions

As poor solubility continues to be problem for new chemical entities (NCEs) in medicines development the use and interest in solid dispersions as a formulation-based solution has grown. Solid dispersions, where a drug is typically dispersed in a molecular state within an amorphous water-soluble polymer, present a good strategy to significantly enhance the effective drug solubility and hence bioavailability of drugs. The main drawback of this formulation strategy is the inherent instability of the amorphous form. With the right choice of polymer and manufacturing method, sufficient stability can be accomplished. However, finding the right combination of carrier and manufacturing method can be challenging, being labour, time and material costly. Therefore, a knowledge based support tool based upon a statistically significant data set to help with the formulation process would be of great value in the pharmaceutical industry. Here, 60 solid dispersion formulations were produced using ten, poorly soluble, chemically diverse APIs, three commonly used polymers and two manufacturing methods (spray drying and hot-melt extrusion). A long term stability study, up to one year, was performed on all formulations at accelerated conditions. Samples were regularly checked for the onset of crystallisation during the period, using mainly, polarised light microscopy. The stability data showed a large variance in stability between, methods, polymers and APIs. No obvious trends could be observed. Using statistical modelling, the experimental data in combination with calculated and predicted physicochemical properties of the APIs, several multiple linear regression (MLR) models were built. These had a good adjusted R2 and most showed good predictability in leave-one-out cross validations. Additionally, a validation on half of the models (eg. those based on spray-drying models) using an external dataset showed excellent predictability, with the correct ranking of formulations and accurate prediction of stability. In conclusion, this work has provided important insight into the complex correlations between the physical stability of amorphous solid dispersions and factors such as manufacturing method, carrier and properties of the API. Due to the expansive number of formulations studied here, which is far greater than previously published in the literature in a single study, more general conclusions can be drawn about these correlations than has previously been possible. This thesis has shown the potential of using well-founded statistical models in the formulation development of solid dispersion and given more insight into the complexity of these systems and how stability of these is dependent on multiple factors

Complex behavioral alterations after diffuse traumatic axonal injury in mice are normalized by post-injury neutralization of interleukin-1β

Abstract Wide-spread traumatic axonal injury (TAI), clinically known as diffuse axonal injury, results in brain network dysfunction which commonly leads to persisting cognitive and behavioral impairments following traumatic brain injury (TBI). TBI induces a complex neuroinflammatory response, frequently located at sites of axonal pathology. The role of the pro-inflammatory cytokine interleukin-1β (IL-1β) in TAI has not been established. An IL-1β-neutralizing or a control antibody was administered intraperitoneally at 30 min following central fluid percussion injury (cFPI) in mice, a model of wide-spread TAI. Animals subjected to moderate cFPI (n=41) were compared to sham-injured controls (n=20) and untreated, naive animals (n=9). The anti-IL-1β antibody reached the target brain regions in adequate therapeutic concentrations (up to ~30µg /g brain tissue) at 24h post-injury in both cFPI-injured (n=5) and sham-injured animals (n=3) whereas at 72 h post-injury (n=3 cFPI-injured), the antibody concentration was lower (up to ~18µg /g brain tissue). Functional outcome was analyzed using the multivariate concentric square field™ (MCSF) test at 2 and 9 days post-injury and the Morris water maze (MWM) at 14-21 days post-injury. Following TAI, the IL-1β-neutralizing antibody resulted in an improved behavioral outcome, including normalized behavioral profiles in the MCSF test, and improved performance in the MWM probe (memory) trial, although without influencing MWM learning. The IL1β neutralizing treatment did not influence cerebral ventricle size or the number of activated microglia at 21 days post- injury. These findings support the hypothesis that IL-1β is an important contributor to the processes causing complex cognitive and behavioral disturbances following TAI. Keywords: Interleukin 1β, central fluid percussion injury, mice, multivariate concentric square field test, Morris water maze, microglia, traumatic brain injury, traumatic axonal injury, diffuse axonal injury, behavioral outcom