Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance, and Comparison to Density Functional Theory.

Crystal lattice energy is a key property affecting the ease of processing pharmaceutical materials during manufacturing, as well as product performance. We present an extensive comparison of 324 force-field protocols for calculating the lattice energies of single component, organic molecular crystals (further restricted to Z' less than or equal to one), corresponding to a wide variety of force-fields (DREIDING, Universal, CVFF, PCFF, COMPASS, COMPASSII), optimization routines, and other variations, which could be implemented as part of an automated workflow using the industry standard Materials Studio software. All calculations were validated using a large new dataset (SUB-BIG), which we make publicly available. This dataset comprises public domain sublimation data, from which estimated experimental lattice energies were derived, linked to 235 molecular crystals. Analysis of pharmaceutical relevance was performed according to two distinct methods based upon (A) public and (B) proprietary data. These identified overlapping subsets of SUB-BIG comprising (A) 172 and (B) 63 crystals, of putative pharmaceutical relevance, respectively. We recommend a protocol based on the COMPASSII force field for lattice energy calculations of general organic or pharmaceutically relevant molecular crystals. This protocol was the most highly ranked prior to subsetting and was either the top ranking or amongst the top 15 protocols (top 5%) following subsetting of the dataset according to putative pharmaceutical relevance. Further analysis identified scenarios where the lattice energies calculated using the recommended force-field protocol should either be disregarded (values greater than or equal to zero and/or the messages generated by the automated workflow indicate extraneous atoms were added to the unit cell) or treated cautiously (values less than or equal to -249 kJ/mol), as they are likely to be inaccurate. Application of the recommended force-field protocol, coupled with these heuristic filtering criteria, achieved an root mean-squared error (RMSE) around 17 kJ/mol (mean absolute deviation (MAD) around 11 kJ/mol, Spearman's rank correlation coefficient of 0.88) across all 226 SUB-BIG structures retained after removing calculation failures and applying the filtering criteria. Across these 226 structures, the estimated experimental lattice energies ranged from -60 to -269 kJ/mol, with a standard deviation around 29 kJ/mol. The performance of the recommended protocol on pharmaceutically relevant crystals could be somewhat reduced, with an RMSE around 20 kJ/mol (MAD around 13 kJ/mol, Spearman's rank correlation coefficient of 0.76) obtained on 62 structures retained following filtering according to pharmaceutical relevance method B, for which the distribution of experimental values was similar. For a diverse set of 17 SUB-BIG entries, deemed pharmaceutically relevant according to method B, this recommended force-field protocol was compared to dispersion corrected density functional theory (DFT) calculations (PBE + TS). These calculations suggest that the recommended force-field protocol (RMSE around 15 kJ/mol) outperforms PBE + TS (RMSE around 37 kJ/mol), although it may not outperform more sophisticated DFT protocols and future studies should investigate this. Finally, further work is required to compare our recommended protocol to other lattice energy calculation protocols reported in the literature, as comparisons based upon previously reported smaller datasets indicated this protocol was outperformed by a number of other methods. The SUB-BIG dataset provides a basis for these future studies and could support protocol refinement.

Drug-Excipient Interactions in the Solid State: The Role of Different Stress Factors.

Understanding properties and mechanisms that govern drug degradation in the solid state is of high importance to ensure drug stability and safety of solid dosage forms. In this study, we attempt to understand drug-excipient interactions in the solid state using both theoretical and experimental approaches. The model active pharmaceutical ingredients (APIs) under study are carvedilol (CAR) and codeine phosphate (COP), which are known to undergo esterification with citric acid (CA) in the solid state. Starting from the crystal structures of two different polymorphs of each compound, we calculated the exposure and accessibility of reactive hydroxyl groups for a number of relevant crystal surfaces, as well as descriptors that could be associated with surface stabilities using molecular simulations. Accelerated degradation experiments at elevated temperature and controlled humidity were conducted to assess the propensity of different solid forms of the model APIs to undergo chemical reactions with anhydrous CA or CA monohydrate. In addition, for CAR, we studied the solid state degradation at varying humidity levels and also under mechano-activation. Regarding the relative degradation propensities, we found that variations in the exposure and accessibility of molecules on the crystal surface play a minor role compared to the impact of molecular mobility due to different levels of moisture. We further studied drug-excipient interactions under mechano-activation (comilling of API and CA) and found that the reaction proceeded even faster than in physical powder mixtures kept at accelerated storage conditions.

Formulation pre-screening of inhalation powders using computational atom-atom systematic search method.

The synthonic modeling approach provides a molecule-centered understanding of the surface properties of crystals. It has been applied extensively to understand crystallization processes. This study aimed to investigate the functional relevance of synthonic modeling to the formulation of inhalation powders by assessing cohesivity of three active pharmaceutical ingredients (APIs, fluticasone propionate (FP), budesonide (Bud), and salbutamol base (SB)) and the commonly used excipient, α-lactose monohydrate (LMH). It is found that FP (-11.5 kcal/mol) has a higher cohesive strength than Bud (-9.9 kcal/mol) or SB (-7.8 kcal/mol). The prediction correlated directly to cohesive strength measurements using laser diffraction, where the airflow pressure required for complete dispersion (CPP) was 3.5, 2.0, and 1.0 bar for FP, Bud, and SB, respectively. The highest cohesive strength was predicted for LMH (-15.9 kcal/mol), which did not correlate with the CPP value of 2.0 bar (i.e., ranking lower than FP). High FP-LMH adhesive forces (-11.7 kcal/mol) were predicted. However, aerosolization studies revealed that the FP-LMH blends consisted of agglomerated FP particles with a large median diameter (∼4-5 µm) that were not disrupted by LMH. Modeling of the crystal and surface chemistry of LMH identified high electrostatic and H-bond components of its cohesive energy due to the presence of water and hydroxyl groups in lactose, unlike the APIs. A direct comparison of the predicted and measured cohesive balance of LMH with APIs will require a more in-depth understanding of highly hydrogen-bonded systems with respect to the synthonic engineering modeling tool, as well as the influence of agglomerate structure on surface-surface contact geometry. Overall, this research has demonstrated the possible application and relevance of synthonic engineering tools for rapid pre-screening in drug formulation and design.

De-Risking Early-Stage Drug Development With a Bespoke Lattice Energy Predictive Model: A Materials Science Informatics Approach to Address Challenges Associated With a Diverse Chemical Space.

The solid-state properties of new chemical entities are critical to the stability and bioavailability of pharmaceutical drug products. The stability of the solid-state packing is described by the packing energy and an accurate prediction of this property for drug molecules would therefore be desirable. However, this has been difficult to achieve because of the lack of fundamental thermodynamic data on drug molecules. A potential solution would be to use calculated lattice energies to build a model and design molecules with desired physicochemical properties from an early stage, aligning with a "design by first intent" strategy for physicochemical properties. We first demonstrate the high correlation and interchangeability between QSPR models built using calculated lattice energies and experimental sublimation enthalpies for small organic molecules. We then present a QSPR model trained on in-house molecules using lattice energies calculated from crystal structures. The result is a model that enables fast prediction of the lattice energies of in-house molecules from 2-D molecular structure with reasonable accuracy (R2 = 0.92, root mean square error = 3.58 kcal/mol). We explore the model elements to improve our understanding of the molecular properties that contribute to lattice energy and then suggest potential cross-industry aspects that may enhance the application of the concept.

Quantifying solubility enhancement due to particle size reduction and crystal habit modification: case study of acetyl salicylic acid.

The poor solubility of potential drug molecules is a significant problem in the design of pharmaceutical formulations. It is well known, however, that the solubility of crystalline materials is enhanced when the particle size is reduced to submicron levels and this factor can be expected to enhance drug product bioavailability. Direct estimation of solubility enhancement, as calculated via the Gibbs-Thompson relationship, demands reasonably accurate values for the particle/solution interfacial tension and, in particular, its anisotropy with respect to the crystal product's habit and morphology. In this article, an improved, more molecule-centered, approach is presented towards the calculation of solubility enhancement factors in which molecular modeling techniques are applied, and the effects associated with both crystal habit modification and solvent choice are examined. A case study for facetted, acetyl salicylic acid (aspirin) crystals in equilibrium with saturated aqueous ethanol solution reveals that their solubility will be enhanced in the range (7-58%) for a crystal size of 0.02 microm, with significantly higher enhancement for crystal morphologies in which the hydrophobic crystal faces are more predominant than the hydrophilic faces and for solvents in which the solubility is smaller.

Low solubility in drug development: de-convoluting the relative importance of solvation and crystal packing.

OBJECTIVES: An increasing trend towards low solubility is a major issue for drug development as formulation of low solubility compounds can be problematic. This paper presents a model which de-convolutes the solubility of pharmaceutical compounds into solvation and packing properties with the intention to understand the solubility limiting features. METHODS: The Cambridge Crystallographic Database was the source of structural information. Lattice energies were calculated via force-field based approaches using Materials Studio. The solvation energies were calculated applying quantum chemistry models using Cosmotherm software. KEY FINDINGS: The solubilities of 54 drug-like compounds were mapped onto a solvation energy/crystal packing grid. Four quadrants were identified were different balances of solvation and packing were defining the solubility. A version of the model was developed which allows for the calculation of the two features even in absence of crystal structure. CONCLUSION: Although there are significant number of in-silico models, it has been proven very difficult to predict aqueous solubility accurately. Therefore, we have taken a different approach where the solubility is not predicted directly but is de-convoluted into two constituent features.

Application of COSMO-RS as an excipient ranking tool in early formulation development.

The low amounts of drug available in early discovery often results in limited information on the physico-chemical (solubility etc.) properties of a compound being obtained. As a result, predictive tools and miniaturised screens have been investigated to aid formulation development in early discovery. This study looks at the potential application of the quantum chemistry program, Conductor Screening Model for Real Solvents (COSMO-RS) to help with the selection of excipients for formulation development in early discovery. The excipient solubility predictions obtained from COSMO-RS were compared to experimentally obtained solubilities. The results showed that in general, COSMO-RS was able to help formulators with the selection of the most appropriate excipients to solubilise the model compound.

An examination of polymorphic stability and molecular conformational flexibility as a function of crystal size associated with the nucleation and growth of benzophenone.

The polymorphic behaviour of the aromatic ketone, benzophenone, which is a conformationally flexible molecule and forms crystal structures dominated by van der Waals intermolecular interactions, is examined. Crystallization of this material from the undercooled molten state yields the two known polymorphic forms, i.e. the stable alpha-form and the metastable beta-form. The relative, energetic stabilities are examined using both crystal lattice and molecular conformational modelling techniques. Examination of nano-sized faceted molecular clusters of these forms, with cluster sizes ranging from 3 to 100 molecules, reveals that at very small cluster size (< 5 molecules) the relative energetic stability of clusters representative for the two forms become very similar, indicating that for high melting undercooling (i.e. small critical cluster size for nucleation) crystallization of the metastable beta-phase becomes more likely. Detailed analysis of the variation in molecular conformations within the simulated molecular clusters reveals more disordered three-dimensional structures at small compared to larger cluster sizes. The conformational disorder was found to be higher for the metastable beta-form. This observation, together with the lower stability of clusters for this form is indicative of the difficulty in achieving crystallization of the metastable beta-form from the melt, which requires a considerable undercooling.