The cocrystal formation potential of itraconazole, a potent antifungal drug, with C2–C10 aliphatic dicarboxylic acids has been investigated. Using two experimental screening techniques (solvent-assisted grinding and evaporation-based crystallization), the cocrystals of itraconazole with C2–C7 dicarboxylic acids have been successfully synthesized and characterized by powder X-ray diffraction, solid state nuclear magnetic resonance, Raman spectroscopy, and thermal analysis. The characterized multicomponent compounds include anhydrous cocrystals (malonic, succinic, glutaric, and pimelic acids), a cocrystal hydrate (adipic acid), and cocrystal solvates with acetone and tetrahydrofuran (oxalic acid). This study is the first to demonstrate the diversity in itraconazole cocrystals with a range of aliphatic dicarboxylic acids of variable carbon chain lengths.

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Electrospray ionization (ESI) is the most widely used ionization method in on-line coupling of capillary electrophoresis-mass spectrometry (CE-MS). The conventional coaxial sheath flow electrospray interface is currently being replaced by the more sensitive nanoelectrospray technique. The usual limitation of nanoelectrospray CE-MS interface has been its short lifetime caused by deterioration of the metal coating on the CE capillary terminus. This article describes an easy way to construct a more durable and sensitive nanospray interface for nonaqueous CE-MS. In this approach a very thin glass spray capillary (ca. 30 microm outer diameter) is partly inserted inside the CE capillary, the junction being surrounded by the electrolyte medium, which is in contact with the platinum electrode. The interface was tested with five pharmaceuticals: methadone, pentazocine, levorphanol, dihydrocodeine, and morphine. Detection limits ranged from 12 to 540 fmol. Separation efficiency and reproducibility were also studied. The CE current was found to be stable and the migration times were highly reproducible. All the CE separations were carried out in a nonaqueous background electrolyte solution.

Data fusion approach was investigated in the context of pK a prediction for 391 small molecules derived from a public data source as well as for 681 compounds from an internal corporate database. Four different pKa prediction methods (Simulations Plus ADMET-Predictor S + pKa, ACD/Labs Percepta Classic, ACD/Labs Percepta GALAS and Epik) were used to predict the most acidic or basic pKa for each of the compounds. By using data fusion, the median absolute error for the internal compounds was reduced from the best performing single model's value of 0.69 down to 0.50. In addition to the improved accuracy, data fusion also enabled predictions for all of the compounds in the dataset as individual methods failed on some of the molecules.