Pharmaceutical hydrates under ambient conditions from high-pressure seeds: a case study of GABA monohydrate

Fabbiani, Francesca P. A.; Buth, Gernot; Levendis, Demetrius C.; Cruz‐Cabeza, Aurora J.

doi:10.1039/c3cc48466a

Cited by 54 publications

(60 citation statements)

References 38 publications

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“…Increased thermodynamic stability with increasing pressure could however arise in binary systems from differential enthalpies of solvation. This seems to be the case for GABA monohydrate 38 where periodic DFT calculations at 0 K showed that at high pressure the enthalpy of hydration becomes increasingly more negative. GABA monohydrate can be recovered under ambient-pressure conditions, and used for seeding, because under these conditions it is energetically close to the anhydrous polymorph plus ice.…”

Section: Discussionmentioning

confidence: 97%

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

et al. 2016

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The crystal structure of the organic semiconductor 9,10-diphenylanthracene (DPA) has been studied by single-crystal X-ray diffraction at variable pressure up to 3 GPa. Under ambient conditions and in the presence of 1,1,2,2-tetrachloroethane, the material invariably crystallises in an unsolvated form, in the space group C2/c, with Z′ = 1/2, as reported in the literature. As pressure is increased to a modest 0.5 GPa, crystallisation occurs in the form of a newly discovered solvate with a 1 : 2 DPA-tetrachloroethane stoichi- . Monte Carlo simulations show that the mobility of the solvent in its cage would be extremely reduced even under ambient conditions, ruling out a mechanism of solvate formation and subsequent release. According to a structure-oriented perspective, the kinetics of the process could then be such that the nucleating system at ambient pressure separates out the solvent, while a 0.5 GPa pressure provides a solute-solvent grip that forces cocrystallisation, in agreement with both experiments and simulations. Even in the absence of experimental or computational proof of the thermodynamic stability of the solvate at high pressure, this appears to be a plausible and sensible case scenario in its own right.

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Section: Discussionmentioning

confidence: 97%

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

et al. 2016

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“…It complies with the pressure-promoted solvation observed in MOFs and molecular crystals. [27][28][29][30] It allows more compact packing of the molecules in the limited space, enabling the formation of solvates with possible technological applications. 31 The molecular volume of the g-CD-MOF-1 phase a crystal at 0.16 GPa is higher than that at ambient conditions.…”

Section: Resultsmentioning

confidence: 99%

Pressure inverse solubility and polymorphism of an edible γ-cyclodextrin-based metal–organic framework

Patyk‐Kaźmierczak

Warren

Allan

et al. 2017

Phys. Chem. Chem. Phys.

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A very exceptional effect of pressure-induced dissolution has been revealed for an edible metal-organic framework, g-CD-MOF-1, formed using g-cyclodextrin and KOH base. In addition, a new polymorph of g-CD-MOF-1 has been obtained. The trigonal structure is a symmetry sub-group modification of the cubic form. The pressure-induced dissolution of g-CD-MOF-1 and its polymorphism are shown to be closely related and regulated by adsorption in the pores, as well as the guest framework interactions.

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“…There are many types of crystallographic studies that cannot afford excluding the required data points from refinement because the entire dataset is too small. Such studies include low-resolution macromolecular studies, highpressure studies, neutron studies, and some of the latest data from free electron lasers (21,22,30).…”

Section: Discussionmentioning

confidence: 99%

“…In high-pressure crystallography the situation is even worse because the incompleteness of the data owing to shadows from the experimental setup is systematic and leads to data-to-parameter ratios too low to rely on R1 alone. The entire dataset may have fewer than 500 observations (22).…”

Section: Significancementioning

confidence: 99%

New method to compute R _complete enables maximum likelihood refinement for small datasets

Luebben¹,

Gruene

2015

Proc. Natl. Acad. Sci. U.S.A.

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The crystallographic reliability index R complete is based on a method proposed more than two decades ago. Because its calculation is computationally expensive its use did not spread into the crystallographic community in favor of the cross-validation method known as R free . The importance of R free has grown beyond a pure validation tool. However, its application requires a sufficiently large dataset. In this work we assess the reliability of R complete and we compare it with k-fold cross-validation, bootstrapping, and jackknifing. As opposed to proper cross-validation as realized with R free , R complete relies on a method of reducing bias from the structural model. We compare two different methods reducing model bias and question the widely spread notion that random parameter shifts are required for this purpose. We show that R complete has as little statistical bias as R free with the benefit of a much smaller variance. Because the calculation of R complete is based on the entire dataset instead of a small subset, it allows the estimation of maximum likelihood parameters even for small datasets. R complete enables maximum likelihood-based refinement to be extended to virtually all areas of crystallographic structure determination including high-pressure studies, neutron diffraction studies, and datasets from free electron lasers. structure determination | reliability index | maximum likelihood refinement | overfitting | model bias T he quality of crystallographic models is described by several quality indicators. Both for small and macromolecular structure deposition, the crystallographic reliability index R1 must be provided (1, 2). It is calculated for the dataset H of observations and a structural model asDepending on the data-to-parameter ratio, R1 is affected by more or less severe overfitting (3, 4). To overcome this problem, cross-validation was introduced into crystallography (5-9). For cross-validation in crystallography, a certain fraction of the observations, typically 5-10%, are withheld as test set T and never used for model building and refinement. They are only used to calculate the reliability index R free :R free is much less affected by overfitting and since its introduction it has gained importance beyond validation of the structural model. It is used to optimize weights for restrained refinement (4, 10-13). The concept of R free paved the way for maximum likelihood methods in crystallography. It was shown that the estimation of maximum likelihood parameters based on the test set T provides much better accuracy than that based on the data used during refinement (14-16).Cross-validation reduces the bias of a statistic (17, 18) but can show large variance, especially when T is small (8, 17). The relative error of the crystallographic R free was established as σðR free Þ = R free = ffiffiffiffiffiffiffiffi ffi 2jTj p (19). The test set should hold at least 500 data points so that σðR free Þ=R free ≤ 0.032. Maximum likelihood methods estimate parameters in resolution bins, and a total of jTj ...

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Pharmaceutical hydrates under ambient conditions from high-pressure seeds: a case study of GABA monohydrate

Cited by 54 publications

References 38 publications

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

Pressure inverse solubility and polymorphism of an edible γ-cyclodextrin-based metal–organic framework

New method to compute R _complete enables maximum likelihood refinement for small datasets

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Pharmaceutical hydrates under ambient conditions from high-pressure seeds: a case study of GABA monohydrate

Cited by 54 publications

References 38 publications

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

X-ray diffraction and computational studies of the pressure-dependent tetrachloroethane solvation of diphenylanthracene

Pressure inverse solubility and polymorphism of an edible γ-cyclodextrin-based metal–organic framework

New method to compute R complete enables maximum likelihood refinement for small datasets

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New method to compute R _complete enables maximum likelihood refinement for small datasets