Optimization of the stability constants of the ternary system of diclofenac/famotidine/β-cyclodextrin by nonlinear least-squares method using theoretical equations

How Does the Powder Mixture of Ibuprofen and Caffeine Attenuate the Solubility of Ibuprofen? Comparative Study for the Xanthine Derivatives to Recognize Their Intermolecular Interactions Using Fourier-Transform Infrared (FTIR) Spectra, Differential Scanning Calorimetry (DSC), and X-ray Powder Diffractometry (XRPD)

Molecular interactions between active pharmaceutical ingredients (APIs) and xanthine (XAT) derivatives were analyzed using singular value decomposition (SVD). XAT derivatives were mixed with equimolar amounts of ibuprofen (IBP) and diclofenac (DCF), and their dissolution behaviors were measured using high-performance liquid chromatography. The solubility of IBP decreased in mixtures with caffeine (CFN) and theophylline (TPH), whereas that of DCF increased in mixtures with CFN and TPH. No significant differences were observed between the mixtures of theobromine (TBR) or XAT with IBP and DCF. Mixtures with various molar ratios were analyzed using differential scanning calorimetry, X-ray powder diffraction, and Fourier-transform infrared spectroscopy to further explore these interactions. The results were subjected to SVD. This analysis provides valuable insights into the differences in interaction strength and predicted interaction sites between XAT derivatives and APIs based on the combinations that form mixtures. The results also showed the impact of the XAT derivatives on the dissolution behavior of IBP and DCF. Although IBP and DCF were found to form intermolecular interactions with CFN and TPH, these effects resulted in a reduction of the solubility of IBP and an increase in the solubility of DCF. The current approach has the potential to predict various interactions that may occur in different combinations, thereby contributing to a better understanding of the impact of health supplements on pharmaceuticals.

Febuxostat ternary inclusion complex using SBE7-βCD in presence of a water-soluble polymer: physicochemical characterization, in vitro dissolution, and in vivo evaluation

Febuxostat (FBX), a potent xanthine oxidase inhibitor, is widely used as a blood uric acid-reducing agent and has recently shown a promising repurposing outcome as an anti-cancer. FBX is known for its poor water solubility, which is the main cause of its weak oral bioavailability. In a previous study, we developed a binary system complex between FBX and sulfobutylether-β-cyclodextrin (SBE7-βCD) with improved dissolution behavior. The aim of the current study was to investigate the effect of incorporating a water-soluble polymer with a binary system forming a ternary one, on further enhancement of FBX solubility and dissolution rate. In vivo oral bioavailability was also studied using LC-MS/MS chromatography. The polymer screening study revealed a marked increment in the solubility of FBX with SBE7-βCD in the presence of 5% w/v polyethylene glycol (PEG 6000). In vitro release profile showed a significant increase in the dissolution rate of FBX from FBX ternary complex (FTC). Oral in vivo bioavailability of prepared FTC showed more than threefold enhancement in Cmax value (17.05 ± 2.6 µg/mL) compared to pure FBX Cmax value (5.013 ± 0.417 µg/mL) with 257% rise in bioavailability. In conclusion, the association of water-soluble polymers with FBX and SBE7-βCD system could significantly improve therapeutic applications of the drug.

Using singular value decomposition to analyze drug/β-cyclodextrin mixtures: insights from X-ray powder diffraction patterns

The article discusses the use of mathematical models and linear algebra to understand the crystalline structures and interconversion pathways of drug complexes with β-cyclodextrin (β-CD). It involved the preparation and analysis of mixtures of indomethacin, diclofenac, famotidine, and cimetidine with β-CD using techniques such as differential scanning calorimetry (DSC), X-ray powder diffraction (XRPD), and proton nuclear magnetic resonance (1H-NMR). Singular value decomposition (SVD) analysis is used to identify the presence of different polymorphs in the mixtures of these drugs and β-CD, determine interconversion pathways, and distinguish between different forms. In general, linear algebra or artificial intelligence (AI) is used to approximate the contribution of distinguishable entities to various phenomena. We expected linear algebra to completely reveal all eight entities present in the diffractogram dataset. However, after performing the SVD procedure, we found that only six independent basis functions were extracted, and the entities of the INM α-form and the CIM B-form were not included. It is considered that this is due to that data processing is limited to revealing only six or seven independent factors, as it is a small world. The authors caution that these may not always reproduce or approach reality in complicated real-world situations.