Compressibility behavior of pioglitazone hydrochloride in mannitol-based formulations: An investigation using compaction simulator and QbD approach.

This study aimed to investigate the compressibility properties of Pioglitazone Hydrochloride (PGZ) oral dispersible tablets using a compaction simulator. The tablets were prepared and formulated by direct compression method with varying particle sizes of PGZ in mannitol-based formulations, containing Ludiflash® and its corresponding physical mixture. All formulations were compressed at different compaction forces (5kN-20kN). Powders were evaluated for their tablet properties, such as hardness, friability, disintegration time and dissolution rate. Results showed that all formulations exhibited good compressibility properties. The compaction force and choice of excipient played a vital role in formulation performance and drug release profile. With the use of Minitab 19™ an optimized formulation was derived and all predicted outputs was seen to be within range after evaluations. In conclusion, the combined use of the compaction simulator and Minitab 19™ were found to be useful tools in predicting the compressibility properties of PGZ and therefore developing a robust oral dispersible tablet. These findings suggest that the compressibility properties of PGZ oral dispersible tablets can be effectively modified by adjusting the critical process parameters (CPP). Hence, providing valuable insights into the compressibility behavior of PGZ oral dispersible tablets and also aiding in the development of optimized tablet formulations.

The effect of the systemic folic acid intake as an adjunct to scaling and root planing on clinical parameters and homocysteine and C-reactive protein levels in gingival crevicular fluid of periodontitis patients: A randomized placebo-controlled clinical trial.

AIM: To evaluate clinical and biochemical effects of adjunctive systemic folic acid (FA) intake with scaling and root planing (SRP) in periodontitis treatment. MATERIALS AND METHODS: Sixty periodontitis subjects (30 per group) were randomly assigned into study groups and treated with either SRP + placebo (SRP + P) or SRP + folic acid (SRP + F). In addition to clinical parameters (plaque index [PI], gingival index [GI], probing pocket depth [PPD], clinical attachment level [CAL] and gingival recession [GR]), gingival crevicular fluid (GCF) samples were obtained at baseline and post-treatment (PT) periods (one (PT-1), three (PT-3) and six (PT-6) months) for C-reactive protein (CRP) and homocysteine (Hcy) evaluation. RESULTS: Significant time-dependent reduction was detected at all clinical parameters for both groups (p < .001). Compared to SRP + P, CAL was lower in SRP + F at PT-1 (p = .004) and PT-3 (p = .035), whereas GR was lower at only PT-1 (p = .015). GCF volume and CRP did not show inter-group differences, whereas Hcy was higher in SRP + F at PT-3 (p = .044) and PT-6 (p = .041). GCF volume and Hcy showed reduction after treatment in both groups (p < .001). CONCLUSION: Both modalities exhibited clinical improvement and change in biochemical parameters. Adjunctive systemic FA intake may be recommended adjunctive to periodontitis treatment to reveal better outcomes. However, its impact mechanisms should be further enlightened.

Demystifying the potential of lipid-based nanocarriers in targeting brain malignancies.

Drug targeting for brain malignancies is restricted due to the presence of the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB), which act as barriers between the blood and brain parenchyma. Certainly, the limited therapeutic options for brain malignancies have made notable progress with enhanced biological understanding and innovative approaches, such as targeted therapies and immunotherapies. These advancements significantly contribute to improving patient prognoses and represent a promising shift in the landscape of brain malignancy treatments. A more comprehensive understanding of the histology and pathogenesis of brain malignancies is urgently needed. Continued research focused on unraveling the intricacies of brain malignancy biology holds the key to developing innovative and tailored therapies that can improve patient outcomes. Lipid nanocarriers are highly effective drug delivery systems that significantly improve their solubility, bioavailability, and stability while also minimizing unwanted side effects. Surface-modified lipid nanocarriers (liposomes, niosomes, solid lipid nanoparticles, nanostructured lipid carriers, lipid nanocapsules, lipid-polymer hybrid nanocarriers, lipoproteins, and lipoplexes) are employed to improve BBB penetration and uptake through various mechanisms. This systematic review illuminates and covers various topics related to brain malignancies. It explores the different methods of drug delivery used in treating brain malignancies and delves into the benefits, limitations, and types of brain-targeted lipid-based nanocarriers. Additionally, this review discusses ongoing clinical trials and patents related to brain malignancy therapies and provides a glance into future perspectives for treating this condition.

A Novel Semi-Solid Self-Emulsifying Formulation of Aprepitant for Oral Delivery: An In Vitro Evaluation.

Aprepitant is the first member of a relatively new antiemetic drug class called NK1 receptor antagonists. It is commonly prescribed to prevent chemotherapy-induced nausea and vomiting. Although it is included in many treatment guidelines, its poor solubility causes bioavailability issues. A particle size reduction technique was used in the commercial formulation to overcome low bioavailability. Production with this method consists of many successive steps that cause the cost of the drug to increase. This study aims to develop an alternative, cost-effective formulation to the existing nanocrystal form. We designed a self-emulsifying formulation that can be filled into capsules in a melted state and then solidified at room temperature. Solidification was achieved by using surfactants with a melting temperature above room temperature. Various polymers have also been tested to maintain the supersaturated state of the drug. The optimized formulation consists of CapryolTM 90, Kolliphor® CS20, Transcutol® P, and Soluplus®; it was characterized by DLS, FTIR, DSC, and XRPD techniques. A lipolysis test was conducted to predict the digestion performance of formulations in the gastrointestinal system. Dissolution studies showed an increased dissolution rate of the drug. Finally, the cytotoxicity of the formulation was tested in the Caco-2 cell line. According to the results, a formulation with improved solubility and low toxicity was obtained.

Systematic Screening Study for the Selection of Proper Stabilizers to Produce Physically Stable Canagliflozin Nanosuspension by Wet Milling Method.

One of the crucial approaches to managing the low solubility and weak bioavailability of drugs is via nanocrystal technology. Through this technology, drug particles have an increased solubility and a faster dissolution rate due to high surface free energy, which requires an appropriate stabilizer(s) to prevent instabilities during the manufacturing process and storage of the nanosuspension. This study aimed to establish a scientific predictive system for properly selecting stabilizers or to reduce the attempts on a trial-and-error basis in the wet-milling method. In total, 42 experiments were performed to examine the effect of critical material attributes on the wettability of the drug, the saturation solubility in the stabilizer solutions or combinations thereof and the dynamic viscosity of stabilizer solutions. All data were evaluated by Minitab 19® and an optimization study was performed. The optimized formulation at a certain concentration of stabilizer combination was ground by Dyno Mill® with 0.3 mm beads for one hour. The optimized nanosuspension with a particle size of 204.5 nm was obtained in short milling time and offered 3.05- and 3.51 times better dissolution rates than the marketed drug product (Invokana® 100 mg) in pH 4.5 and pH 6.8 as non-sink conditions, respectively. The formulation was monitored for three months at room temperature and 4 °C. The parameters were 261.30 nm, 0.163, -14.1 mV and 261.50 nm, 0.216 and -17.8 mV, respectively. It was concluded that this approach might indicate the appropriate selection of stabilizers for the wet-milling process.

Optimization of the Micellar-Based In Situ Gelling Systems Posaconazole with Quality by Design (QbD) Approach and Characterization by In Vitro Studies.

BACKGROUND: Fungal ocular infections can cause serious consequences, despite their low incidence. It has been reported that Posaconazole (PSC) is used in the treatment of fungal infections in different ocular tissues by diluting the oral suspension, and successful results were obtained despite low ocular permeation. Therefore, we optimized PSC-loaded ocular micelles and demonstrated that the permeation/penetration of PSC in ocular tissues was enhanced. METHODS: The micellar-based in situ gels based on the QbD approach to increase the ocular bioavailability of PSC were developed. Different ratios of Poloxamer 407 and Poloxamer 188 were chosen as CMAs. Tsol/gel, gelling capacity and rheological behavior were chosen as CQA parameters. The data were evaluated by Minitab 18, and the formulations were optimized with the QbD approach. The in vitro release study, ocular toxicity, and anti-fungal activity of the optimized formulation were performed. RESULTS: Optimized in situ gel shows viscoelastic property and becomes gel form at physiological temperatures even when diluted with the tear film. In addition, it has been shown that the formulation had high anti-fungal activity and did not have any ocular toxicity. CONCLUSIONS: In our previous studies, PSC-loaded ocular micelles were developed and optimized for the first time in the literature. With this study, the in situ gels of PSC for ocular application were developed and optimized for the first time. The optimized micellar-based in situ gel is a promising drug delivery system that may increase the ocular permeation and bioavailability of PSC.

In Vitro Evaluation of a Solid Supersaturated Self Nanoemulsifying Drug Delivery System (Super-SNEDDS) of Aprepitant for Enhanced Solubility.

Aprepitant (APR) belongs to Class II of the Biopharmaceutical Classification System (BCS) because of its low aqueous solubility. The objective of the current work is to develop self-nanoemulsifying drug delivery systems (SNEDDS) of APR to enhance its aqueous solubility. Preformulation studies involving screening of excipients for solubility and emulsification efficiency were carried out. Pseudo ternary phase diagrams were constructed with blends of oil (Imwitor® 988), cosolvent (Transcutol® P), and various surfactants (Kolliphor® RH40, Kolliphor® ELP, Kolliphor® HS15). The prepared SNEDDS were characterized for droplet size and nanoemulsion stability after dilution. Supersaturated SNEDDS (super-SNEDDS) were prepared to increase the quantity of loaded APR into the formulations. HPMC, PVP, PVP/VA, and Soluplus® were used as polymeric precipitation inhibitors (PPI). PPIs were added to the formulations at 5% and 10% by weight. The influence of the PPIs on drug precipitation was investigated. In vitro lipolysis test was carried out to simulate digestion of formulations in the gastrointestinal tract. Optimized super-SNEDDS were formulated into free-flowing granules by adsorption on the porous carriers such as Neusilin® US2. In vitro dissolution studies of solid super-SNEDDS formulation revealed an increased dissolution rate of the drug due to enhanced solubility. Consequently, a formulation to improve the solubility and potentially bioavailability of the drug was developed.

Estimating the Optimal Dexketoprofen Pharmaceutical Formulation with Machine Learning Methods and Statistical Approaches.

OBJECTIVES: Orally disintegrating tablets (ODTs) can be utilized without any drinking water; this feature makes ODTs easy to use and suitable for specific groups of patients. Oral administration of drugs is the most commonly used route, and tablets constitute the most preferable pharmaceutical dosage form. However, the preparation of ODTs is costly and requires long trials, which creates obstacles for dosage trials. The aim of this study was to identify the most appropriate formulation using machine learning (ML) models of ODT dexketoprofen formulations, with the goal of providing a cost-effective and timereducing solution. METHODS: This research utilized nonlinear regression models, including the k-nearest neighborhood (k-NN), support vector regression (SVR), classification and regression tree (CART), bootstrap aggregating (bagging), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) methods, as well as the t-test, to predict the quantity of various components in the dexketoprofen formulation within fixed criteria. RESULTS: All the models were developed with Python libraries. The performance of the ML models was evaluated with R2 values and the root mean square error. Hardness values of 0.99 and 2.88, friability values of 0.92 and 0.02, and disintegration time values of 0.97 and 10.09 using the GBM algorithm gave the best results. CONCLUSIONS: In this study, we developed a computational approach to estimate the optimal pharmaceutical formulation of dexketoprofen. The results were evaluated by an expert, and it was found that they complied with Food and Drug Administration criteria.

A Solid Ultra Fine Self-Nanoemulsifying Drug Delivery System (S-SNEDDS) of Deferasirox for Improved Solubility: Optimization, Characterization, and In Vitro Cytotoxicity Studies.

The research work was designed to develop a solid self-nanoemulsifying drug delivery system (S-SNEDDS) of deferasirox (DFX). According to the solubility studies of DFX in different components, Peceol, Kolliphor EL, and Transcutol were selected as excipients. Pseudo-ternary phase diagrams were constructed, and then SNEDDS formation assessment studies and solubility of DFX in selected SNEDDSs formulations were performed. DFX loaded SNEDDS were prepared and characterized. The optimum DFX-SNEDDS formulations were developed. The relative safety of the optimized SNEDDS formulation was examined in a human immortalized myelogenous leukemia cell line, K562 cells, using the MTT cell viability test. Cytotoxicity studies revealed more cell viability (71.44%) of DFX loaded SNEDDS compared to pure DFX (3.99%) at 40 µM. The selected DFX-SNEDDS formulation was converted into S-SNEDDS by adsorbing into porous carriers, in order to study its dissolution behavior. The in vitro drug release studies indicated that DFX release (Q5%) from S-SNEDDS solidified with Neusilin UFL2 was significantly higher (93.6 ± 0.7% within 5 min) compared with the marketed product (81.65 ± 2.10%). The overall results indicated that the S-SNEDDS formulation of DFX could have the potential to enhance the solubility of DFX, which would in turn have the potential to improve its oral bioavailability as a safe novel delivery system.

Quetiapine Fumarate Extended-release Tablet Formulation Design Using Artificial Neural Networks.

OBJECTIVES: This design study was implemented within the scope of the quality by design approach, which included the "International Conference on Harmonization" guidelines. We evaluated the quality of a modified-release tablet formulation of quetiapine fumarate, which was designed using artificial neural networks (ANN), and determined a new formulation that was similar to the reference product. MATERIALS AND METHODS: Twelve different formulations were produced and tested. The reference product's results and our experimental results were used as outputs for the training of the ANN programs of Intelligensys Ltd. RESULTS: Dissolution tests were performed with the new formulation (F13) suggested by the INForm V.4 ANN program in three different pHs of the gastrointestinal system. The compliance of this formulation was confirmed by comparing the results with an f2 similarity test. CONCLUSION: Use of these programs supports research and development processes with multiple evaluation methods and alternative formulations may be determined faster and at lower cost.