Computational prediction of glass-forming ability and crystallization tendencies

The Third Annual FPTP Network Meetin

Improvement of physicochemical parameters of acyclovir using cocrystallization approach

ABSTRACT Acyclovir is an antiviral drug having potent activity against the virus of herpes family and varicella zoster. Unfortunately, drug suffers very poor oral bioavailability (15-30%). The main objective of present study was to develop acyclovir cocrystals with improved solubility which may result in improvement of bioavailability. Hansen solubility approach was used as a tool to predict the cocrystal formation of a drug with selected coformer. Cocrystals of acyclovir with various coformers were screened in order to enhance their water solubility. Cocrystals of the drug were prepared using various methods like solvent evaporation, wet grinding, and antisolvent addition. Formation of cocrystals by solvent evaporation method was found to be better method amongst all. Optimization of cocrystal formation was carried out by employing different solvents as well as the stoichiometric ratio of acyclovir with that of coformer. Synthesis of cocrystals was optimized using water as a solvent system resulted in good agreements. The potential cocrystal formation of acyclovir was characterized by IR, PXRD and DSC techniques. An in-vitro dissolution study was performed to determine the dissolution rate of cocrystals. The results suggest that acyclovir forms cocrystals with tartaric acid and the initial dissolution rate of synthesized cocrystals were considerably faster as compared to pure acyclovir

Molecular Drivers of Crystallization Kinetics for Drugs in Supersaturated Aqueous Solutions

In this study, we explore molecular properties of importance in solution-mediated crystallization occurring in supersaturated aqueous drug solutions. Furthermore, we contrast the identified molecular properties with those of importance for crystallization occurring in the solid state. A literature data set of 54 structurally diverse compounds, for which crystallization kinetics from supersaturated aqueous solutions and in melt-quenched solids were reported, was used to identify molecular drivers for crystallization kinetics observed in solution and contrast these to those observed for solids. The compounds were divided into fast, moderate, and slow crystallizers, and in silico classification was developed using a molecular K-nearest neighbor model. The topological equivalent of Grav3 (related to molecular size and shape) was identified as the most important molecular descriptor for solution crystallization kinetics; the larger this descriptor, the slower the crystallization. Two electrotopological descriptors (the atom-type E-state index for -Caa groups and the sum of absolute values of pi Fukui(+) indices on C) were found to separate the moderate and slow crystallizers in the solution. The larger these descriptors, the slower the crystallization. With these 3 descriptors, the computational model correctly sorted the crystallization tendencies from solutions with an overall classification accuracy of 77% (test set)

Physical stability of drugs after storage above and below the glass transition temperature : Relationship to glass-forming ability

Amorphous materials are inherently unstable and tend to crystallize upon storage. In this study, we investigated the extent to which the physical stability and inherent crystallization tendency of drugs are related to their glass-forming ability (GFA), the glass transition temperature (T-g) and thermodynamic factors. Differential scanning calorimetry was used to produce the amorphous state of 52 drugs [ 18 compounds crystallized upon heating (Class II) and 34 remained in the amorphous state (Class III)] and to perform in situ storage for the amorphous material for 12 h at temperatures 20 degrees C above or below the T-g. A computational model based on the support vector machine (SVM) algorithm was developed to predict the structure-property relationships. All drugs maintained their Class when stored at 20 degrees C below the T-g. Fourteen of the Class II compounds crystallized when stored above the T-g whereas all except one of the Class III compounds remained amorphous. These results were only related to the glass-forming ability and no relationship to e. g. thermodynamic factors was found. The experimental data were used for computational modeling and a classification model was developed that correctly predicted the physical stability above the T-g. The use of a large dataset revealed that molecular features related to aromaticity and pi-pi interactions reduce the inherent physical stability of amorphous drugs

Physical stability of drugs after storage above and below the glass transition temperature : Relationship to glass-forming ability

Amorphous materials are inherently unstable and tend to crystallize upon storage. In this study, we investigated the extent to which the physical stability and inherent crystallization tendency of drugs are related to their glass-forming ability (GFA), the glass transition temperature (T-g) and thermodynamic factors. Differential scanning calorimetry was used to produce the amorphous state of 52 drugs [ 18 compounds crystallized upon heating (Class II) and 34 remained in the amorphous state (Class III)] and to perform in situ storage for the amorphous material for 12 h at temperatures 20 degrees C above or below the T-g. A computational model based on the support vector machine (SVM) algorithm was developed to predict the structure-property relationships. All drugs maintained their Class when stored at 20 degrees C below the T-g. Fourteen of the Class II compounds crystallized when stored above the T-g whereas all except one of the Class III compounds remained amorphous. These results were only related to the glass-forming ability and no relationship to e. g. thermodynamic factors was found. The experimental data were used for computational modeling and a classification model was developed that correctly predicted the physical stability above the T-g. The use of a large dataset revealed that molecular features related to aromaticity and pi-pi interactions reduce the inherent physical stability of amorphous drugs

Physical stability of drugs after storage above and below the glass transition temperature: Relationship to glass-forming ability

A B S T R A C T Amorphous materials are inherently unstable and tend to crystallize upon storage. In this study, we investigated the extent to which the physical stability and inherent crystallization tendency of drugs are related to their glass-forming ability (GFA), the glass transition temperature (T g ) and thermodynamic factors. Differential scanning calorimetry was used to produce the amorphous state of 52 drugs [18 compounds crystallized upon heating (Class II) and 34 remained in the amorphous state (Class III)] and to perform in situ storage for the amorphous material for 12 h at temperatures 20 C above or below the T g . A computational model based on the support vector machine (SVM) algorithm was developed to predict the structure-property relationships. All drugs maintained their Class when stored at 20 C below the T g . Fourteen of the Class II compounds crystallized when stored above the T g whereas all except one of the Class III compounds remained amorphous. These results were only related to the glass-forming ability and no relationship to e.g. thermodynamic factors was found. The experimental data were used for computational modeling and a classification model was developed that correctly predicted the physical stability above the T g . The use of a large dataset revealed that molecular features related to aromaticity and p-p interactions reduce the inherent physical stability of amorphous drugs

Computational predictions of glass-forming ability and crystallization tendency of drug molecules.

Amorphization is an attractive formulation technique for drugs suffering from poor aqueous solubility as a result of their high lattice energy. Computational models that can predict the material properties associated with amorphization, such as glass-forming ability (GFA) and crystallization behavior in the dry state, would be a time-saving, cost-effective, and material-sparing approach compared to traditional experimental procedures. This article presents predictive models of these properties developed using support vector machine (SVM) algorithm. The GFA and crystallization tendency were investigated by melt-quenching 131 drug molecules in situ using differential scanning calorimetry. The SVM algorithm was used to develop computational models based on calculated molecular descriptors. The analyses confirmed the previously suggested cutoff molecular weight (MW) of 300 for glass-formers, and also clarified the extent to which MW can be used to predict the GFA of compounds with MW < 300. The topological equivalent of Grav3_3D, which is related to molecular size and shape, was a better descriptor than MW for GFA; it was able to accurately predict 86% of the data set regardless of MW. The potential for crystallization was predicted using molecular descriptors reflecting Hückel pi atomic charges and the number of hydrogen bond acceptors. The models developed could be used in the early drug development stage to indicate whether amorphization would be a suitable formulation strategy for improving the dissolution and/or apparent solubility of poorly soluble compounds