Understanding molecular self-association in solution is vital for uncovering polymorph-selective crystal nucleation pathways. In this paper, we combine solution NMR spectroscopy and molecular dynamics simulations to shed light on the structural and dynamical features of p-aminobenzoic acid (pABA) in solution, and on their role in pABA crystals nucleation. pABA is known to yield different crystal forms (α, and β) depending on solvent choice and supersaturation conditions. NMR reveals that dominant interactions stabilizing pABA oligomers are markedly solvent-dependent: in organic solvents, hydrogen bonds dominate, while water promotes π-πstacking. Despite this clear preference, both types of interactions contribute to the variety of self-associated species in all solvents considered. MD simulations support this observation and show that pABA oligomers are short-lived and display a fluxional character, therefore indicating that the growth unit involved in pABA crystallization is likely to be a single molecule. Nevertheless, we note that the interactions dominating in pABA oligomers are indicative of the polymorph obtained from precipitation. In water, at low pABA concentrations - conditions that are known to yield crystals of the β form - carboxylic-carboxylic hydrogen bonds are exclusively asymmetric. At higher pABA concentration conditions in which the crystallization is known to yield the α form - a small but statistically significant fraction of symmetric carboxylic-carboxylic hydrogen-bonded dimers is present. We interpret the presence of these interactions in solvated pABA oligomers as indicative of the fact that a simultaneous and complete desolvation of two carboxylic groups, necessary to form the symmetric hydrogen-bonded dimer typical of the α crystal form, is accessible, therefore directing the nucleation pathway toward the nucleation of α-pABA.

Polymorph-Selective Role of Hydrogen Bonding and π-π Stacking in p-Aminobenzoic Acid Solutions

Controlling the physical properties of solid forms for active pharmaceutical ingredients (APIs) through cocrystallization is an important part of drug product development. However, it is difficult to know a priori which coformers will form cocrystals with a given API, and the current state-of-the-art for cocrystal discovery involves an expensive, time-consuming, and, at the early stages of pharmaceutical development, API material-limited experimental screen. We propose a systematic, high-throughput computational approach primarily aimed at identifying API/coformer pairs that are unlikely to lead to experimentally observable cocrystals and can therefore be eliminated with only a brief experimental check, from any experimental investigation. On the basis of a well-established crystal structure prediction (CSP) methodology, the proposed approach derives its efficiency by not requiring any expensive quantum mechanical calculations beyond those already performed for the CSP investigation of the neat API itself. The approach and assumptions are tested through a computational investigation on 30 potential 1:1 multicomponent systems (cocrystals and solvate) involving 3 active pharmaceutical ingredients and 9 coformers and one solvent. This is complemented with a detailed experimental investigation of all 30 pairs, which led to the discovery of five new cocrystals (three API–coformer combinations, a polymorphic cocrystal example, and one with different stoichiometries) and a cis-aconitic acid polymorph. The computational approach indicates that, for some APIs, a significant proportion of all potential API/coformer pairs could be investigated with only a brief experimental check, thereby saving considerable experimental effort.

https://pubs.acs.org/doi/pdf/10.1021/acs.cgd.2c00433

Efficient Screening of Coformers for Active Pharmaceutical Ingredient Cocrystallization

Solvent–Antisolvent Competitive Interactions Mediate Imidacloprid Polymorphs in Antisolvent Crystallization

The discovery of new crystalline forms of large, flexible drug molecules is of significant interest to the pharmaceutical industry as a means of improving one or more physicochemical properties of the active pharmaceutical ingredient (API). Trametinib (TRMB) is an anticancer drug, for which no solid-state forms are yet reported. Here, we report the results of an extensive screen for cocrystals of TRMB in an effort to improve the poor aqueous solubility of this API. Contrary to expectations, this effort led to the discovery of only six isostructural solvates of TRMB, where the solvent molecules fill the voids of the crystal structure and are stabilized by various intermolecular interactions. Computational crystal structure prediction methods were used to rationalize the high propensity for solvent inclusion in TRMB as arising from the poor crystal packing in TRMB. All predicted polymorphs of TRMB within a relative lattice energy of 44 kJ mol–1 of the global minimum display solvent accessible voids ranging from 1.4 to 16.5% of the unit cell volume. The serendipitous discovery of solvates in experiments targeting cocrystals,strongly suggests that the well-established synthon approach for the discovery of cocrystals works relatively well for documented literature examples that use rigid coformers with minimal conformational flexibility. However, for large APIs such as TRMB, in-silico screening methods should be adopted to reduce the need for extensive experimental cocrystal screens as the ability to form a cocrystal for drug candidates relies on more than synthon complementarity. 

Unravelling the Origin of Solvate Formation in the Anticancer Drug Trametinib: Insights from Crystal Structure Analysis and Computational Modeling

Stronger drug–solvent interactions than drug–drug interactions are responsible for the formation of solvates in niclosamide.

Why does the niclosamide drug form solvates or hydrates?

Classical nucleation theory teaches the idea that molecular clusters form and grow in solution and that depending on prevailing conditions there is a chance for some to grow large enough to overcome the interfacial energy penalty and become mature crystals. However, from such a kinetic analysis, nothing is learnt of the nature of the composition or the molecular packing in such clusters. As a means of addressing this shortcoming consideration has, in the past, been given to the idea that in certain systems crystallography may offer additional, structural, insights. From this approach the notions of ‘nucleation pathway’ or ‘nucleation transition state’ have become useful concepts around which to formulate hypotheses as to how clusters may yield specific molecular packing, resulting for example, in the observation of crystal polymorphs. Here we offer an in-depth crystallographic analysis related to the nucleation of the α and β polymorphs of para-aminobenzoic acid in an attempt to reveal the pathways leading to the two forms. Using a combination of CSD analyses, crystal structure prediction and targeted crystallizations we explore plausible solution pathways to these polymorphs and discuss our results in the light of known kinetic data for the nucleation and growth of this material.

/pdf/can-solvated-intermediates-inform-us-about-nucleation-5es5pbm7kn.pdf

Can solvated intermediates inform us about nucleation pathways? The case of β-pABA

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Can solvated intermediates inform us about nucleation pathways? The case of β-pABA