Fragkoulis Theodosiou

Mapping crystallization outcomes in ternary solvent mixtures for systems able to solvate remains experimentally intensive due to the significant compositional phase space that needs to be explored to derive complete phase diagrams. Here, we show that these phase diagrams can be generated readily by combining rapid mechanochemical determination of critical solvent activities using binary solvent mixtures with thermodynamic activity mapping such as NRTL modeling. This approach enables quantitative prediction of ternary phase diagrams without direct experimental mapping of the full compositional space. Using nitrofurantoin as a model system, which forms an anhydrous phase, a monohydrate, and a dmf solvate, we determine the critical solvent activities from binary mixtures and use these together with predicted activity maps to generate ternary phase diagrams. The resulting framework accurately predicts phase boundaries and solid-form outcomes across two ternary solvent systems. Comparison with experimental data across 108 controlled solvent activity liquid assisted grinding (CSA-LAG) outcomes shows excellent agreement, with predictive accuracy exceeding 90% and correct reproduction of phase diagram topology. This strategy reduces the required experimental effort by more than 70% while providing mechanistic insight into competing solvation equilibria through solvent activity and activity-ratio landscapes. Since multicomponent solvate phase behavior is governed by solvent activity rather than composition, determination of critical activities in low dimensional space with activities modeling allow for a shift from empirical screening to thermodynamically guided prediction in crystallization design.

Hydrates are common solid forms that can significantly affect a compound’s stability, physicochemical properties, and commercial viability. Despite their importance in pharmaceutical development, hydrate structures, their relationship to material properties, and their propensity for formation remain poorly understood. In 2003, Gillon et al. introduced a simple yet powerful framework for the structural classification of hydrates based on the hydrogen-bonding environment of crystalline water molecules. This framework categorizes water molecules according to the number of hydrogen-bond donor (D) and acceptor (A) interactions in which they participate, giving rise to eight distinct environments. In the original study, the DDA environment, where water donates two hydrogen bonds and accepts one, was reported as the most common. The statistical distribution of these environments in the Cambridge Structural Database (CSD) has since provided a useful benchmark for the qualitative assessment of hydrate structures. Here, we revisit Gillon’s water environment classification using a substantially expanded data set comprising 13,881 hydrate entries from the CSD and provide updated statistics on hydrate structures. Our analysis confirms that the DDA environment remains the most prevalent, followed by DDAA and DD, while the remaining environments occur less frequently. Extending beyond the original work, we quantify the energetics associated with each environment and demonstrate that the four-hydrogen-bond DDAA environment is energetically the most favorable, followed by environments involving three, two, and one hydrogen bonds, respectively. We further show that water-mediated intermolecular interactions contribute up to 40% of the total lattice interaction energy in the hydrate structures, highlighting the surprisingly large influence of this small solvent molecule on crystal stability. Despite its superior energetic stability, the DDAA environment is not the most frequently observed experimentally. This apparent discrepancy arises because the hydrogen-bonding capability and topology of the main component in the hydrate constrains the maximum hydrogen-bonding environment that water can achieve. Overall, this work provides a comprehensive analysis of hydrate structures and energetics across the CSD. The resulting insights offer a valuable framework for the qualitative assessment of newly discovered hydrate forms and for evaluating whether their structures conform to established crystallographic trends.

Crystalline solvates, including hydrates, hold untapped potential in pharmaceutical development, yet their exploitation remains minimal due to the difficult and laborious task of unequivocally establishing their physical stabilities. We introduce Controlled Solvent-Activity Liquid-Assisted Grinding (CSA-LAG), a mechanochemical protocol that offers solvate phase boundary elucidation by varying the activity of a chosen solvent in defined binary/ternary mixtures and analysing the equilibrated resulting solid form. Using small API amounts, CSA-LAG reaches equilibrium within minutes and yields critical solvent activities that delimit neat, hydrated, solvated and competing-solvate domains. The method uses mixtures of known thermodynamic activities, requires far less material and time than traditional slurries and affords high reproducibility. Applied to four pharmaceutical compounds, CSA-LAG reproduces slurry boundaries and quantifies activity thresholds for single, stepwise and competitive solvations. Defining these boundaries enables rational form selection and process design either by avoiding or targeting solvates, whilst turning a month-scale empirical screening into a rapid, thermodynamically guided workflow.