Analytical quality-by-design (AQbD) approach for comprehensive analysis of bioactive compounds from Citrus peel wastes by UPLC.

The growing interest in ingredients from natural sources has expanded the need for quality assessments of plant extracts. Analytical quality-by-design (AQbD) has been increasingly applied in regulated environments such as pharmaceutical industries and, more recently, for the bioactive compounds found in botanical materials. This work aimed to obtain qualitative (overall resolution and maximum peak capacity) and quantitative performances for target analytes using AQbD principles. The analytical target profile was elaborated; critical method parameters (independent variables) that affect the critical method attributes (dependent variables) were selected from a risk assessment for a reversed-phase liquid chromatography with diode array detection (RPLC-DAD) method. YMC-Triart C18 (3.0 × 100 mm, 1.9 µm) and a gradient elution using 0.2% acetic acid and methanol:acetonitrile 1:3 (v/v) were chosen as the stationary and mobile phases, respectively. The optimal and robust conditions (temperature at 33.3 °C, flow rate of 0.68 mL.min-1, and a gradient slope of 4.18%.min-1) were established by the method operable design region (MODR). The validation was performed by accuracy profiles using 90% expectation tolerance intervals for the selected compounds found in Citrus spp. using C. japonica as blank matrix. The lower limits of quantification for hesperidin, bergapten, herniarin, and citropten were 5.32, 0.40, 0.49, and 0.52 mg.L-1, respectively (acceptance limit was set at ± 20%). Nobiletin did not show an adequate quantitative performance.

Hybrid nanofilms as topical anesthetics for pain-free procedures in dentistry.

Topical anesthetics are widely applied in order to relieve the discomfort and anxiety caused by needle insertion and other painful superficial interventions at the oral cavity. So far, there are no commercially available effective topical anesthetic formulations for that purpose, and the most of developments are related to hydrophilic and low mucoadhesive forms. Therefore, we have prepared different hybrid nanofilms composed of biopolymer matrices (chitosan, pectin, and chitosan-pectin) blended with nanostructured lipid carriers (NLC) loading the eutectic mixture of 5% lidocaine-prilocaine (LDC-PLC), in order to fulfill this gap in the market. These dual systems were processed as hybrid nanofilms by the solvent/casting method, and its mucoadhesive, structural and mechanical properties were detailed. The most appropriate hybrid nanofilm combined the advantages of both pectin (PCT) and NLC components. The resultant material presented sustained LDC-PLC release profile for more than 8 h; permeation across porcine buccal mucosa almost twice higher than control and non-cytotoxicity against 3T3 and HACAT cell lines. Then, the in vivo efficacy of PCT/NLC formulation was compared to biopolymer film and commercial drug, exhibiting the longest-lasting anesthetic effect (> 7 h), assessed by tail flick test in mice. These pectin-based hybrid nanofilms open perspectives for clinical trials and applications beyond Dentistry.

Evaluation of miscibility and polymorphism of synthetic and natural lipids for nanostructured lipid carrier (NLC) formulations by Raman mapping and multivariate curve resolution (MCR).

Nanostructured lipid carriers (NLC) belong to youngest lipid-based nanocarrier class and they have gained increasing attention over the last ten years. NLCs are composed of a mixture of solid and liquid lipids, which solubilizes the active pharmaceutical ingredient, stabilized by a surfactant. The miscibility of the lipid excipients and structural changes (polymorphism) play an important role in the stability of the formulation and are not easily predicted in the early pharmaceutical development. Even when the excipients are macroscopically miscible, microscopic heterogeneities can result in phase separation during storage, which is only detected after several months of stability studies. In this sense, this work aimed to evaluate the miscibility and the presence of polymorphism in lipid mixtures containing synthetic (cetyl palmitate, Capryol 90®, Dhaykol 6040 LW®, Precirol ATO5® and myristyl myristate) and natural (beeswax, cocoa and shea butters, copaiba, sweet almond, sesame and coconut oils) excipients using Raman mapping and multivariate curve resolution - alternating least squares (MCR-ALS) method. The results were correlated to the macroscopic stability of the formulations. Chemical maps constructed for each excipient allowed the direct comparison among formulations, using standard deviation of the histograms and the Distributional Homogeneity Index (DHI). Lipid mixtures of cetyl palmitate/Capryol®; cetyl palmitate/Dhaykol®; myristyl myristate/Dhaykol® and myristyl myristate/coconut oil presented a single histogram distribution and were stable. The sample with Precirol®/Capryol® was not stable, although the histogram distribution was narrower than the samples with cetyl palmitate, indicating that miscibility was not the factor responsible for the instability. Structural changes before and after melting were identified for cocoa butter and shea butter, but not in the beeswax. Beeswax + copaiba oil sample was very homogenous, without polymorphism and stable over 6 months. Shea butter was also homogeneous and, in spite of the polymorphism, was stable. Formulations with cocoa butter presented a wider histogram distribution and were unstable. This paper showed that, besides the miscibility evaluation, Raman imaging could also identify the polymorphism of the lipids, two major issues in lipid-based formulation development that could help guide the developer understand the stability of the NLC formulations.

Natural lipids-based NLC containing lidocaine: from pre-formulation to in vivo studies.

In a nanotechnological approach we have investigated the use of natural lipids in the preparation of nanostructured lipid carriers (NLC). Three different NLC composed of copaiba oil and beeswax, sweet almond oil and shea butter, and sesame oil and cocoa butter as structural matrices were optimized using factorial analysis; Pluronic® 68 and lidocaine (LDC) were used as the colloidal stabilizer and model encapsulated drug, respectively. The optimal formulations were characterized by different techniques (IR-ATR, DSC, and TEM), and their safety and efficacy were also tested. These nanocarriers were able to upload high amounts of the anesthetic with a sustained in vitro release profile for 24h. The physicochemical stability in terms of size (nm), PDI, zeta potential (mV), pH, nanoparticle concentration (particles/mL), and visual inspection was followed during 12months of storage at 25°C. The formulations exhibited excellent structural properties and stability. They proved to be nontoxic in vitro (cell viability tests with Balb/c 3T3 fibroblasts) and significantly improved the in vivo effects of LDC, over the heart rate of zebra fish larvae and in the blockage of sciatic nerve in mice. The results from this study support that the proper combination of natural excipients is promising in DDS, taking advantage of the biocompatibility, low cost, and diversity of lipids.

Analysis of pharmaceutical pellets: an approach using near-infrared chemical imaging.

Pharmaceutical pellets are spherical or nearly spherical multi-unit dosage forms designed to optimize pharmacokinetics and pharmacodynamics features of drug release. The distribution of the pharmaceutical ingredients in the layers and core is a very important parameter for appropriate drug release, especially for pellets manufactured by the process of layer gain. Physical aspects of the sample are normally evaluated by Scanning Electron Microscopy (SEM), but it is in many cases unsuitable to provide conclusive chemical information about the distribution of the pharmaceutical ingredients in both layers and core. On the other hand, methods based on spectroscopic imaging can be very promising for this purpose. In this work, a Near-Infrared Chemical Imaging (NIR-CI) method was developed and applied to the analysis of diclophenac sodium pellets. Since all the compounds present in the sample were known in advance, Classical Least Squares (CLS) was used for calculations. The results have shown that the method was capable of providing chemical information about the distribution of the active ingredient and excipients in the core and coating layers and therefore can be complementary to SEM for the pharmaceutical development of pellets.