HSPiP, Computational Modeling, and QbD-Assisted Optimized Method Validation of 5-Fluorouracil for Transdermal Products.

This study addressed the simplest and most efficient HPLC (high-performance liquid chromatography) method for the estimation of 5-fluorouracil (5-FU) from rat blood plasma by implementing the Hansen solubility parameters (HSP), computation prediction program, and QbD (quality by design) tool. The mobile phase selection was based on the HSP predictions and experimental data. The Taguchi model identified seven variables (preoptimization) to screen two factors (mobile phase ratio as A and column temperature as B) at three levels as input parameters in "CCD (central composite design)" optimization (retention time as Y1 and peak area as Y2). The stability study (freeze-thaw cycle and short- and long-term stability) was conducted in the rat plasma. Results showed that HSPiP-based HSP values and computational model-based predictions were well simulated with the experimental solubility data. Acetonitrile (ACN) was relatively suitable over methanol as evidenced by the experimental solubility value, HSP predicted parameters (δh of 5-FU - δh of ACN = 8.3-8.3 = 0 as high interactive solvent whereas δh of 5-FU - δh of methanol = 8.3-21.7 = -13.4), and instrumental conditions. CCD-based dependent variables (Y1 and Y2) exhibited the best fit of the model as evidenced by a high value of combined desirability (0.978). The most robust method was adopted at A = 96:4 and B = 40 °C to get earlier Y1 and high Y2 as evidenced by high desirability (D) = 0.978 (quadratic model with p < 0.0023). The estimated values of LLOD and LLOQ were found to be 0.11 and 0.36 µg/mL, respectively with an accuracy range of 94.4-98.7%. Thus, the adopted method was the most robust, reliable, and reproducible methodology for pharmacokinetic parameters after the transdermal application of formulations in the rat.

Optimized Green Nanoemulsions to Remove Pharmaceutical Enoxacin from Contaminated Bulk Aqueous Solution.

We attempted to develop green nanoemulsions (ENE1-ENE5) using capryol-C90 (C90), lecithin, Tween 80, and N-methyl-2-pyrrolidone (NMP). HSPiP software and experimentally obtained data were used to explore excipients. ENE1-ENE5 nanoemulsions were prepared and evaluated for in vitro characterization parameters. An HSPiP based QSAR (quantitative structure-activity relationship) module established a predictive correlation between the Hansen solubility parameter (HSP) and thermodynamic parameters. A thermodynamic stability study was conducted under stress conditions of temperature (from -21 to 45 °C) and centrifugation. ENE1-ENE5 were investigated for the influence of size, viscosity, composition, and exposure time on emulsification (5-15 min) on %RE (percent removal efficiency). Eventually, the treated water was evaluated for the absence of the drug using electron microscopy and optical emission spectroscopy. HSPiP program predicted excipients and established the relationship between enoxacin (ENO) and excipients in the QSAR module. The stable green nanoemulsions ENE-ENE5 possessed the globular size range of 61-189 nm, polydispersity index (PDI) of 0.1-0.53, viscosity of 87-237 cP, and ζ potential from -22.1 to -30.8 mV. The values of %RE depended upon the composition, globular size, viscosity, and exposure time. ENE5 showed %RE value as 99.5 ± 9.2% at 15 min of exposure time, which may be due to the available maximized adsorption surface. SEM-EDX (scanning electron microscopy-X-ray dispersive energy mode) and inductively coupled plasma-optical emission spectroscopy (ICP-OES) negated the presence of ENO in the treated water. These variables were critical factors for efficient removal of ENO during water treatment process design. Thus, the optimized nanoemulsion can be a promising approach to treat water contaminated with ENO (a potential pharmaceutical antibiotics).

Identification of Potential Antitubulin Agents with Anticancer Assets from a Series of Imidazo[1,2-a]quinoxaline Derivatives: In Silico and In Vitro Approaches.

Computer-aided drug design is a powerful and promising tool for drug design and development, with a reduced cost and time. In the current study, we rationally selected a library of 34 fused imidazo[1,2-a]quinoxaline derivatives and performed virtual screening, molecular docking, and molecular mechanics for a lead identification against tubulin as an anticancer molecule. The computational analysis and pharmacophoric features were represented as 1A2; this was a potential lead against tubulin, with a maximized affinity and binding score at the colchicine-binding site of tubulin. The efficiency of this lead molecule was further identified using an in vitro assay on a tubulin enzyme and the anticancer potential was established using an MTT assay. Compound 1A2 (IC50 = 4.33-6.11 µM against MCF-7, MDA-MB-231, HCT-116, and A549 cell lines) displayed encouraging results similar to the standard drug colchicine in these in vitro studies, which further confirmed the effectiveness of CADD in new drug developments. Thus, we successfully applied the utility of in silico techniques to identify the best plausible leads from the fused azaheterocycles.

Green Nanoemulsion Water/Ethanol/Transcutol/LabM-Based Treatment of Pharmaceutical Antibiotic Erythromycin-Contaminated Aqueous Bulk Solution.

Contaminated wastewater released from hospital, domestic, and industrial sources is a major challenge to aquatic animals and human health. In this study, we addressed removal of erythromycin (ERN) from contaminated water employing water/ethanol/Transcutol/Labrafil M 1944 CS (LabM) green nanoemulsions as a nanocarrier system. ERN is a major antibiotic contaminant harming aquatic and human lives. Green nanoemulsions were prepared and evaluated for size, size distribution (measuring polydispersity index), stability, zeta potential, refractive index, and viscosity. Transmission electron microscopy (TEM) was used to visualize morphological behavior. The treated-water was analyzed for ERN by the spectroscopy, scanning electron microscopy-energy-dispersive X-ray analysis mode (SEM-EDX), and inductively coupled plasma-optical emission spectroscopy (ICP-OES) techniques. We studied factors (composition, size, viscosity, and time of exposure) affecting removal efficiency (%RE). The obtained green nanoemulsions (ENE1-ENE5) were stable and clear (<180 nm). ENE5 had the smallest size (58 nm), a low polydispersity index value (0.19), optimal viscosity (∼121.7 cP), and a high negative zeta potential value (-25.4 mV). A high %RE value (98.8%) was achieved with a reduced size, a high water amount, a low Capryol 90 content, and optimal viscosity as evidenced by the obtained results. Moreover, contact time had insignificant effect on %RE. UV-vis spectroscopy, SEM-EDX, and ICP-OES confirmed the absence of ERN from the treated water. Conclusively, ERN can easily be removed from polluted water employing green nanoemulsions prepared from the optimized excipients, and evaluated characteristics.