Multicomponent Materials to Improve Solubility: Eutectics of Drug Aminoglutethimide

Here, we report the synthesis and experimental characterization of three drug-drug eutectic mixtures of drug aminoglutethimide (AMG) with caffeine (CAF), nicotinamide (NIC) and ethenzamide (ZMD). The eutectic mixtures i.e., AMG-CAF (1:0.4, molar ratio), AMG-NIC (1:1.9, molar ratio) and AMG-ZMD (1:1.4, molar ratio) demonstrate significant melting point depressions ranging from 99.2 to 127.2 °C compared to the melting point of the drug AMG (151 °C) and also show moderately higher aqueous solubilities than that of the AMG. The results presented include the determination of the binary melt phase diagrams and accompanying analytical characterization via X-ray powder diffraction, FT-IR spectroscopy and scanning electron microscopy.

Multicomponent Materials to Improve Solubility: Eutectics of Drug Aminoglutethimide

Here, we report the synthesis and experimental characterization of three drug-drug eutectic mixtures of drug aminoglutethimide (AMG) with caffeine (CAF), nicotinamide (NIC) and ethenzamide (ZMD). The eutectic mixtures (AMG-CAF, AMG-NIC and AMG-ZMD) demonstrate significant melting point depressions ranging from 99.2 to 127.2 °C compared to the melting point of the drug AMG (151°C) and also show significantly higher aqueous solubilities than that of the AMG. The results presented include the determination of the binary melt phase diagrams and accompanying analytical characterization via X-ray powder diffraction, FT-IR spectroscopy and Scanning electron microscopy.

Development and validation of a new microplate assay that utilises optical density to quantify the antibacterial activity of honeys including Jarrah, Marri and Manuka

The phenol equivalence assay is the current industry-adopted test used to quantify the antibacterial activity of honeys in Australia and New Zealand. Activity is measured based on the diffusion of honey through agar and resulting zone of growth inhibition. Due to differences in the aqueous solubilities of antibacterial compounds found in honeys, this method may not be optimal for quantifying activity. Therefore, a new method was developed based on the existing broth microdilution assay that is widely used for determining minimum inhibitory concentrations (MICs). It utilises the four organisms Staphylococcus aureus ATCC 29213, Enterococcus faecalis ATCC 29212, Escherichia coli ATCC 25922 and Pseudomonas aeruginosa ATCC 27853, and an optical density endpoint to quantify bacterial growth. Decreases in bacterial growth in the presence of honey, relative to the positive growth control, are then used to derive a single value to represent the overall antibacterial activity of each honey. Antibacterial activity was quantified for a total of 77 honeys using the new method, the phenol equivalence assay and the standard broth microdilution assay. This included 69 honeys with undisclosed floral sources and the comparators Manuka, Jarrah (Eucalyptus marginata), Marri (Corymbia calophylla), artificial and multifloral honey. For the 69 honey samples, phenol equivalence values ranged from 0–48.5 with a mean of 34 (% w/v phenol). Mean MICs, determined as the average of the MICs obtained for each of the four organisms for each honey ranged from 7–24% (w/v honey). Using the new assay, values for the 69 honeys ranged from 368 to 669 activity units, with a mean of 596. These new antibacterial activity values correlated closely with mean MICs (R2 = 0.949) whereas the relationship with phenol equivalence values was weaker (R2 = 0.649). Limit of detection, limit of quantitation, measuring interval, limit of reporting, sensitivity, selectivity, repeatability, reproducibility, and ruggedness were also investigated and showed that the new assay was both robust and reproducible.

Three machine learning models for the 2019 Solubility Challenge

<p class="ADMETabstracttext">We describe three machine learning models submitted to the 2019 Solubility Challenge. All are founded on tree-like classifiers, with one model being based on Random Forest and another on the related Extra Trees algorithm. The third model is a consensus predictor combining the former two with a Bagging classifier. We call this consensus classifier Vox Machinarum, and here discuss how it benefits from the Wisdom of Crowds. On the first 2019 Solubility Challenge test set of 100 low-variance intrinsic aqueous solubilities, Extra Trees is our best classifier. One the other, a high-variance set of 32 molecules, we find that Vox Machinarum and Random Forest both perform a little better than Extra Trees, and almost equally to one another. We also compare the gold standard solubilities from the 2019 Solubility Challenge with a set of literature-based solubilities for most of the same compounds.</p>

Technical note: Estimating aqueous solubilities and activity coefficients of mono- and <i>α</i>, <i>ω</i>-dicarboxylic acids using COSMO-RS-DARE

We have used the COSMOtherm program to estimate activity coefficients and solubilities of mono- and α, ω-dicarboxylic acids, and water in binary acid-water systems. The deviation from ideality was found to be larger in the systems containing larger acids than in the systems containing smaller acids. We found a better agreement between estimated and experimental activity coefficients of monocarboxylic acids when the water clustering with a carboxylic acid and itself was taken into account using the dimerization, aggregation and reaction extension (COSMO-RS-DARE) of COSMOtherm. Based on effective equilibrium constants of different clustering reactions in the binary solutions, acid dimer formation is more dominant in systems containing larger dicarboxylic acids (C5–C8), while for monocarboxylic acids (C1–C6) and smaller dicarboxylic acids (C2–C4), hydrate formation is more favorable, especially in dilute solutions.

Dialing in Direct Air Capture of CO2 by Crystal Engineering of Bis-iminoguanidines

We report a structure-properties relationship study of DAC by crystallization of bis-iminoguanidine (BIG) carbonate salts. The study focuses on a series of basic BIG structures including the glyoxal-bis(iminoguanidine) prototype (GBIG) and its simple analogs methylglyoxal-bis(iminoguanidine) (MGBIG) and diacetyl-bis(iminoguanidine) (DABIG). We find that minor structural modifications in the molecular structure of GBIG, such as substituting one or two hydrogen atoms with methyl groups, result in major changes in the crystal structures, induced by the increased conformational flexibility and steric hindrance. As a result, the corresponding aqueous solubilities within the series increase significantly, leading in turn to enhanced DAC performances.

Dialing in Direct Air Capture of CO2 by Crystal Engineering of Bis-iminoguanidines

We report a structure-properties relationship study of DAC by crystallization of bis-iminoguanidine (BIG) carbonate salts. The study focuses on a series of basic BIG structures including the glyoxal-bis(iminoguanidine) prototype (GBIG) and its simple analogs methylglyoxal-bis(iminoguanidine) (MGBIG) and diacetyl-bis(iminoguanidine) (DABIG). We find that minor structural modifications in the molecular structure of GBIG, such as substituting one or two hydrogen atoms with methyl groups, result in major changes in the crystal structures, induced by the increased conformational flexibility and steric hindrance. As a result, the corresponding aqueous solubilities within the series increase significantly, leading in turn to enhanced DAC performances.