An empirical predictive model for determining the aqueous solubility of BCS class IV drugs in amorphous solid dispersions.

CONTEXT: Determining solubility of drugs is laborious and time-consuming process that may not yield meaningful results. Amorphous solid dispersion (ASD) is a widely used solubility enhancement technique. Predictive models could streamline this process and accelerate the development of oral drugs with improved aqueous solubilities. OBJECTIVE: This study aimed to develop a predictive model to estimate the solubility of a compound from the ASDs in polymer matrices. METHODS: ASDs of model drugs (acetazolamide, chlorothiazide, furosemide, hydrochlorothiazide, sulfamethoxazole) with model polymers (PVP, PVPVA, HPMC E5, Soluplus) and a surfactant (TPGS) were prepared using hotmelt process. The prepared ASDs were characterized using DSC, FTIR, and XRD. The aqueous solubility of the model drugs was determined using shake-flask method. Multiple linear regression was used to develop a predictive model to determine aqueous solubility using the molecular descriptors of the drug and polymer as predictor variables. The model was validated using Leave-One-Out Cross-Validation. RESULTS: The ASDs' drug components were identified as amorphous via DSC and XRD Studies. There were no significant chemical interactions between the model drugs and the polymers based on FTIR studies. The ASDs showed a significant (p < 0.05) improvement in solubility, ranging from a 3-fold to 118-fold, compared with the pure drug. The developed empirical model predicted the solubility of the model drugs from the ASDs containing model polymer matrices with an accuracy greater than 80%. CONCLUSION: The developed empirical model demonstrated robustness and predicted the aqueous solubility of model drugs from the ASDs of model polymer matrices with an accuracy greater than 80%.

A comparative study on micelles, liposomes and solid lipid nanoparticles for paclitaxel delivery.

The purpose of this work was to compare the in vitro and in vivo characteristics of LDV-targeted lipid-based micelles, liposomes and solid lipid nanoparticles (SLN) to provide further insights into their therapeutic potential for clinical development. Micelles, liposomes and SLN were prepared using LDV peptide amphiphiles and palmitic acid-derived lipids using solvent evaporation, thin-film hydration and microfluidic mixing respectively. Nanocarriers were characterized for their physicochemical properties, paclitaxel loading efficiency, in vitro release behavior, stability in biological media as well as in vivo antitumor efficacy in melanoma xenograft model. TEM and DLS results confirmed the presence of paclitaxel-loaded nanosized micelles (6 to 12 nm), liposomes (123.31 ± 5.87 nm) and SLN (80.53 ± 5.37 nm). SLN demonstrated the slowest paclitaxel release rate and the highest stability in biological media compared to micelles and liposomes. Paclitaxel-loaded SLN demonstrated a statistically significant delay in tumor growth compared to mice treated with paclitaxel-loaded liposomes and paclitaxel-loaded micelles (p < 0.05). The results obtained in this study indicate the potential of SLN as drug delivery vehicles for anticancer therapy.