Rapid screening approaches for solubility enhancement, precipitation inhibition and dissociation of a cocrystal drug substance using high throughput experimentation

Biological Activity In Vitro, Absorption, BBB Penetration, and Tolerability of Nanoformulation of BT44:RET Agonist with Disease-Modifying Potential for the Treatment of Neurodegeneration

BT44 is a novel, second-generation glial cell line-derived neurotropic factor mimetic with improved biological activity and is a lead compound for the treatment of neurodegenerative disorders. Like many other small molecules, it suffers from intrinsic poor aqueous solubility, posing significant hurdles at various levels for its preclinical development and clinical translation. Herein, we report a poly(2-oxazoline)s (POx)-based BT44 micellar nanoformulation with an ultrahigh drug-loading capacity of 47 wt %. The BT44 nanoformulation was comprehensively characterized by 1H NMR spectroscopy, differential scanning calorimetry (DSC), powder X-ray diffraction (XRD), dynamic light scattering (DLS), and cryo-transmission/scanning electron microscopy (cryo-TEM/SEM). The DSC, XRD, and redispersion studies collectively confirmed that the BT44 formulation can be stored as a lyophilized powder and can be redispersed upon need. The DLS suggested that the redispersed formulation is suitable for parenteral administration (Dh ≈ 70 nm). The cryo-TEM measurements showed the presence of wormlike structures in both the plain polymer and the BT44 formulation. The BT44 formulation retained biological activity in immortalized cells and in cultured dopamine neurons. The micellar nanoformulation of BT44 exhibited improved absorption (after subcutaneous injection) and blood-brain barrier (BBB) penetration, and no acute toxic effects in mice were observed. In conclusion, herein, we have developed an ultrahigh BT44-loaded aqueous injectable nanoformulation, which can be used to pave the way for its preclinical and clinical development for the management of neurodegenerative disorders.

Development of a Microgram Scale Video-Microscopic Method to Investigate Dissolution Behavior of Poorly Water-Soluble Drugs

Poor aqueous solubility is a common characteristic of new drug candidates, which leads to low or inconsistent oral bioavailability. This has sparked an interest in material efficient testing of solubility and dissolution rate. The aim was to develop a microgram scale video-microscopic method to screen the dissolution rates of poorly water-soluble drugs. This method was applied to six drugs (carvedilol, diazepam, dipyridamole, felodipine, fenofibrate, and indomethacin) in fasted state simulated intestinal fluid (FaSSIF), of indomethacin in buffer with varying pH, and of diazepam and dipyridamole in customized media. An additional aim was to track phase transformations for carbamazepine in FaSSIF. The dissolution rates and particle behavior of the drugs were investigated by tracking particle surface area over time using optical video-microscopy. Applying miniaturized UV spectroscopic dissolution resulted in a similar grouping of dissolution rates and pH effects, as for the video-microscopic setup. Using customized media showed that lysophospholipid enhanced the dissolution rate of diazepam and dipyridamole. The video-microscopic setup allowed for the nucleation of transparent particles on dissolving carbamazepine particles to be tracked over time. The developed setup offers a material efficient screening approach to group drugs according to dissolution rate, where the use of optical microscopy helps to achieve a high sample throughput.

Ketoprofen-FA Co-crystal: In Vitro and In Vivo Investigation for the Solubility Enhancement of Drug by Design of Expert

The present piece of research work is framed for improving the solubility of ketoprofen by forming co-crystal using fumaric acid as a coformer. Co-crystal of ketoprofen and fumaric acid was prepared by simple solvent-assisted grinding method, containing drug and coformer as independent variables and solubility and % drug release were assumed to be dependent variables. Differential scanning calorimetry, Fourier transform infrared spectroscopy, X-ray diffraction, nuclear magnetic resonance and scanning electron microscopy techniques were used to characterize the preparation of optimized batch of co-crystal and further, evaluated for in vitro and in vivo anti-inflammatory and analgesic activities. Based on results of solubility and dissolution rate studies the formulation showed magnified improvement in both the properties on co-crystallization. The values of Gibbs free energy are negative at all levels of carrier demonstrating spontaneity of the drug solubilization process. The IC₅₀ value of optimized batch of co-crystal formulation and the pure drug was observed as 327.33 μg/ml and 556.11 μg/ml, respectively, demonstrating that co-crystal formulation possesses more percentage protection against protein denaturation than the drug ketoprofen. In vivo (anti-inflammatory and analgesic) activities revealed that optimized batch of co-crystal formulation delivered a rapid pharmacological response in Wistar rats and albino mice when compared with standard drug.

Automated high throughput pKa and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge

The goal of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge is to improve the accuracy of current computational models to estimate free energy of binding, deprotonation, distribution and other associated physical properties that are useful for the design of new pharmaceutical products. New experimental datasets of physicochemical properties provide opportunities for prospective evaluation of computational prediction methods. Here, aqueous pK_a and a range of bi-phasic logD values for a variety of pharmaceutical compounds were determined through a streamlined automated process to be utilized in the SAMPL8 physical property challenge. The goal of this paper is to provide an in-depth review of the experimental methods utilized to create a comprehensive data set for the blind prediction challenge. The significance of this work involves the use of high throughput experimentation equipment and instrumentation to produce acid dissociation constants for twenty-three drug molecules, as well as distribution coefficients for eleven of those molecules.