Computational Predictions of Glass-Forming Ability And

Article pubs.acs.org/molecularpharmaceutics Terms of Use Computational Predictions of Glass-Forming Ability and Crystallization Tendency of Drug Molecules † ‡ § † † Amjad Alhalaweh, Ahmad Alzghoul, Waseem Kaialy, Denny Mahlin, and Christel A. S. Bergström*, † Department of Pharmacy, Uppsala University, Uppsala Biomedical Centre, P.O. Box 580, SE-751 23 Uppsala, Sweden ‡ Department of Information Technology, Uppsala University, Lagerhyddsv.̈ 2, hus 1, Box 337, SE-751 05 Uppsala, Sweden § School of Pharmacy, Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton WV1 1LY, United Kingdom ABSTRACT: 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. KEYWORDS: amorphous, glass forming ability, crystallization tendency, support vector machine, molecular descriptors ■ INTRODUCTION soluble compounds so as to transform them into functional 6−9 ff medicines. Downloaded via MONASH UNIV on November 29, 2019 at 03:11:23 (UTC). Drug compounds can exist in di erent solid forms. On The amorphous form of a material (also known as a glass) is solidification, single-component systems can assume a crystal- formed by processing, and thus disordering, the crystalline line form with long- and short-range order, some of which form. Amorphous drugs have been extensively investigated as See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles. display polymorphism, or a glass form with only short-range this state has the potential to overcome issues related to order. Multicomponent systems may also exist in several ff dissolution rate and/or solubility-limited absorption. This di erent solid forms, and in these, long-range order is obtained strategy is of particular interest for nonionizable compounds, by ordered packing of two or more components. Examples of as the commonly used salt formation cannot be applied to such such systems include crystalline forms of drug molecules in compounds.10,11 The number of marketed dosage forms taking combination with counterions (salts), solvents (solvates/ advantage of amorphization is growing and is likely to increase 1−3 hydrates), or inert guest molecules (cocrystals). A multi- further as a response to the limited solubility often associated component system can also exist in the amorphous form, either with new molecules. Prediction of glass formation using a in the recently established coamorphous state in which a drug theoretical, computational approach is therefore warranted to and a guest molecule interact to form an amorphous material or reduce time, cost, and material demands when deciding upon in the traditionally used amorphous solid dispersions using formulation strategies to be explored experimentally in the − polymer matrices.4,5 Screening for the type of solid system that laboratory.12 14 should be used to improve the performance of a drug has been 2,6 the subject of great interest. The aim of these and other Received: April 24, 2014 screening exercises is to avoid the risk of using metastable Revised: July 9, 2014 forms, to comply with regulatory guidelines, or to identify Accepted: July 11, 2014 potential strategies for improving delivery of poorly water- Published: July 11, 2014 © 2014 American Chemical Society 3123 dx.doi.org/10.1021/mp500303a | Mol. Pharmaceutics 2014, 11, 3123−3132 Molecular Pharmaceutics Article The glass-forming ability (GFA) of a material has been defined as the ability of the material to vitrify on cooling from the melted state or to form a glass as a result of processes including spray-drying or mechanical activation.15 Predictions of the GFA, based on measured parameters, have been − − published previously for various materials.12 14,16 18 Previous investigations have indicated that the Hruby parameter strongly correlates with the stability of the glass and the glass-forming tendency for inorganic materials.18 Researchers have studied the GFA of drugs and related this property to both calculated molecular descriptors and experimentally determined properties. Molecular weight (MW) has been found to be an important parameter for determining the GFA.12,13 Using a data set of 50 compounds, we have previously identified that drug molecules with a MW above 300 g/mol are glass- formers.13 This hypothesis was then confirmed using a test set of an additional 50 compounds.13 However, for compounds with a MW below 300 g/mol, no clear trends were observed for this relatively large data set. Other studies have indicated that the molecular flexibility (reflected by the number of rotatable bonds) is another important property for predicting GFA, with flexible compounds being more likely to form the amorphous state.12 In addition to MW and rotatable bonds, branched carbon skeletons, the presence of electronegative atoms, and a low number of aromatic rings have also been suggested to drive GFA.14 A recent study classified the crystallization tendencies for the amorphous forms of drug molecules according to their crystallization behavior from the undercooled melt.12 In that study a data set of 51 drugs was used and compounds that crystallized on cooling the undercooled melt at a temperature lower than the melting temperature were considered to be nonglass-formers (nGFs), defined as Class I compounds (Figure 1a). Glass-formers (GFs), which crystallized on heating fi the melt-quenched material above the Tg, were de ned as Class II compounds (Figure 1b), and compounds that showed no sign of crystallization on heating the melt-quenched material were classified as Class III compounds (Figure 1c). This analysis of the crystallization tendency needs to be experimentally assessed and computational models for prediction are therefore warranted. In this study, the molecular properties considered important for predicting the GFA and the crystallization tendency were explored using a data set of 131 compounds. The following specific objectives were explored, using this large data set: (1) whether the MW can also predict the GFA for compounds with MW < 300; (2) whether other molecular descriptors can predict the GFA better than the MW; and (3) whether the crystallization tendency can be predicted using calculated molecular descriptors. Figure 1. Differential scanning calorimetry thermograms showing the crystallization behavior of the three classes. (a) Class I crystallization ■ EXPERIMENTAL SECTION upon cooling. (b) Class II crystallization in the second heat. (c) Class Materials. All chemicals were purchased from standard III, no crystallization was observed. suppliers and were of high purity (98−99%). The compounds were selected to be structurally diverse (Table 1) to enable the mg of each compound in nonhermetic aluminum pans. The application of the developed models to a wide range of drug compounds were scanned at a heating rate of 10 °C/min under molecules. a continuously purged dry nitrogen atmosphere (50 mL/min). Production of the Amorphous State. The compounds Glass formation was investigated by weighing 1−3 mg of the were amorphized by in situ quenching in a differential scanning compound into nonhermetic pans and heating to around 2 °C calorimetry (DSC) Q2000 calorimeter (TA Instruments), above the peak melting point using an equilibrate function. The which was calibrated for temperature and enthalpy using system was kept isothermal at this temperature for 2 min to indium. The instrument was equipped with a refrigerated ensure complete melting and was thereafter cooled to −70 °C cooling system. The melting point was determined using 1−3 at a ramp rate of 20 °C/min. The formation of a glass state was 3124 dx.doi.org/10.1021/mp500303a | Mol. Pharmaceutics 2014, 11, 3123−3132 Molecular Pharmaceutics Article Table 1. Glass-Forming Ability and Calculated Molecular Properties for the Data Set Studied; Compounds Are Organized a Based on Alphabetical Order within the Class with Training Set Compounds Listed First compound class MW amide ring pi Fukui T_Grav3 pi atomic HBA log P rot bonds Tr/Te aceclofenac III 354.2 0 0 8.3 16.7 0.94 5

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