Technological advancements have led to the development of wearable devices that can be integrated into everyday accessories, clothing, or be attached to the skin. These devices serve as electronic monitoring tools that wirelessly synchronize with smartphones or computers for long -term data tracking. Wearable devices find applications not only in healthcare but also in sports and clothing industries, allowing for easy tracking of various tasks and storing personal data. The increasing adoption of wearable technologies offers benefits such as improved clinical trials, reduced healthcare costs, and better control of health. The development of computer systems and technologies like IoT, artificial intelligence, and Bluetooth has further advanced the integration and practicality of wearable devices. The devices now range from smart eyeglasses to glucose monitors, enabling measurements of clinical findings, overall fitness, and quality of life. The applications of wearable devices can be categorized into individual measurement devices for personal health monitoring and advanced patient tracking systems for use under healthcare professionals' supervision. The data collected by wearable devices can help compare different treatments and improve their effectiveness. Moreover, wearable technologies have gained importance during the COVID-19 pandemic for remote patient monitoring and social isolation. In the future, wearable devices are expected to play a crucial role in providing personalized preventive health services based on the data they collect. The review article aims to provide a general understanding of wearable technologies that will continue to advance and address consumer needs, particularly in the healthcare field.

This mini-review theoretically illustrates the in silico methods used in the pharmacy field to enhance drug discovery and development and reduce preclinical studies. It is shown that in silico methods are computational-based approaches that study the structure, properties, and activities of molecules using computer simulations and mathematical algorithms. These results highlight the importance of obtaining data that can affect the prediction of in vivo results. Artificial intelligence and machine learning development enhance in silico methods such as quantitative structure-activity relationship, molecular placement, and physiological-based pharmacokinetics, which are usually used. This approach not only saves time and costs but also offers ease of application. Studies conducted to evaluate the use of in silico methods in areas such as pharmacology, toxicology, and pharmaceuticals are provided as examples. It was concluded that over time, in silico methods usage and development increased due to their ability to predict the in vivo performance of the drug.

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. (Created by using Biorender.com licenced version).

QbD offers several unique benefits, including deep material and process understanding, flexibility change within the design space without post-approval, application of effective control strategies, and a more robust and reproducible product. The purpose of this chapter is to identify and highlight the fabrication of novel drug delivery systems under the implementation of the QbD approach. It provides a map of QbD, and its elements (material attributes, process parameters, quality attributes, risk assessment tools, and DoE). It also includes the most common novel drug delivery systems formulated using the QbD approach with examples. The knowledge mentioned in this chapter will facilitate understanding novel drug delivery systems using QbD and encourage increasing these novel systems to reach the market in the near future.

. Selecting the most suitable co-processed excipient (CPE) is crucial in orally disintegrating tablets (ODTs) development. The study evaluated five CPE's (Ludiflash & REG;, Ludipress & REG;, Ludipress & REG; LCE, Pearlitol & REG; 200 SD, and GalenIQTM721) that are commonly used in ODT formulations by dynamic compaction data analy-sis. Heckel plots, Force-displacement (F-D) curves and compaction energy data generated by a compaction simulator upon powder compression were studied. Compaction force and CPE composition exerted the most significant influence on the properties of the tablet and the energies required for compaction. According the Heckel analysis all investigated CPE's had relatively higher resistance to plastic deformation, therefore they can be considered to be intermediate or brittle. F-D analysis revealed GalenIQTM 721 to be plastically lean-ing. Conclusively, this research suggests that the key characteristics of excipients that impact the critical quality attributes of ODTs are their ability to deform, their compressibility, and their tabletability capacity.

Objective: The aim of this study was to examine the behavior of two different modified release polymers at different concentrations in terms of their similarity to a commercial product in the market, and to perform optimization studies with these polymers using artificial intelligence to find the most suitable formulation.Materials and Methods: Hydroxypropyl methyl cellulose K100M and sodium alginate polymers were compressed at three different concentrations with the same pressing force. Tests for tablet weights, tablet hardness, diameter/ thickness values and dissolution rate were conducted. The results were evaluated with Minitab19 TM.Results: Tablet weights were found to be between 0.2142 mg±0.039 mg and 0.2974 mg±0.001 mg. Tablet thickness varied between 3.80 mm±0.00 mm and 5.00 mm±0.00 mm. Hardness values of formulations containing the 20 mg polymer could not be measured. For other polymer concentrations, they were between 22.6 N±10.11 N and 111.4 N±9.50 N. The dissolution results of formulations prepared with HPMC were lower than those of sodium alginate at the same concentration. The obtained data was evaluated with Minitab19 TM, which suggested a 41% sodium alginate concentration as the closest formulation to the reference product.Conclusion: The advantages of artificial intelligence applications are not to be underestimated, and researchers are able to find and obtain results of experiments that they might not be able to conduct. In the light of all these findings, it would not be wrong to say that artificial intelligence will become even more preferable in the coming years.

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.

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.

Formulating poorly water-soluble medications is one of the most crucial challenges encountered in the pharmaceutical industry. Due to this obstacle, the model drug chosen for this research was Nimesulide. The primary goal of this research was to obtain information on the drug's physical and chemical properties, either alone or in combination with excipients, in order design a formulation and create a stable and bioavailable dosage form. Formulations were designed using Flowlac (R) 100 and Avicel (R) 102 as fillers, Kollidon (R) 30 as a binder, Magnesium stearate as a lubricant, and variable concentrations of Kollidon (R) CL and Primojel as superdisintegrants. The tableting process was conducted using a compaction simulator. The Quality by Design (QbD) approach allows formulators to enhance product development with built-in product quality. In this study, to understand the relationship between excipients and compaction force differences on tablet properties, the QbD approach was applied by using a compaction simulator.

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.

The objective of the current study was to develop an optimized formulation for orally disintegrating tablets (ODTs) containing melatonin.Different particle sizes of mannitol (i.e., filler) were used to study the effects on dissolution and tablet properties using a quality by design (QbD) approach.The quality target product profile was identified, then critical quality attributes (CQAs) were determined.Risk assessment was performed using the Failure Mode Effect Analysis (FMEA) method to identify and rank critical material attributes and process parameters.Thirty-four formulations were prepared and tested.Box-Behnken design (BBD) with response surface methodology was applied to assess the effect of independent factors on CQAs.Finally, the most suitable formulation in terms of tablet properties was determined with Minitab.Specification tests were applied to confirm that the optimized formula met USP requirements.Mannitol with a small particle size had the fastest disintegration time and dissolution rate in ODT formulations containing melatonin.

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.

The objective of this study was to develop and validate the stability-indicating method for newly developed Extended-Release tablet formulation of Ranolazine.First, new Ranolazine tablet formulation was developed.These tablets were analyzed by using a High-Performance Liquid Chromatography system with a UV detector at 220 nm wavelength and by using C8-3 column (150 mm x 4.6 mm i.d; 5 μm particle size).The injection volume of the system was 10 μl.The validation parameters; Selectivity, linearity, accuracy, robustness, precision and limit of quantification and detection parameters were proved good results.A highly sensitive and simple HPLC-UV analytical method of the Ranolazine tablet formulation was developed in accordance with ICH Guideline Q2 and Q3.

Deferasirox (DFR) is an oral tridentate iron chelator effective for reduction of body iron in ironoverloaded patients with transfusion-dependent anemias [1]. It is a highly lipophilic molecule (log P: 3.52) which is classified as BCS Class II drug substance [2]. Self-nanoemulsifying drug delivery systems (SNEDDs) are isotropic mixtures of drug, oil and hydrophilic surfactants and co-surfactant/co-solvents. In recent years, SNEDDs gained more attention in the solubility enhancement of lipophilic molecule hence enhancing their oral bioavailability. The selection of appropriate components in the SNEDDs formulation is crucial for development of a successful formulation. The goal of this work is to select and to screen appropriate components for the optimization of DFR loaded SNEDDs formulations. In this respect, different SNEDDs formulations were prepared and pseudo-ternary phase diagrams were constructed. 2. Materials and Methods

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.

Background and Aims: The study aimed to design a Fixed-dose tablet formulation of Metformine and Repaglinide. Methods: Wet granulation method was used to prepare tablet formulations. Characterization studies and dissolution studies were performed. Results: A stable formulation was developed according to the requirements of the pharmacopoeia criteria. This new formulsation dissolution results showed that Repaglinide and Metformin HCl dissolved more than 85% from film tablets at 15 minutes. Conclusion: Thus, an alternative product to the market product was developed.

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 time-reducing 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 R-2 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.

Although the first application of Quality by Design (QbD) concept started for product development studies, the number of studies regarding its application to analytical development has been increased recently.Basically, QbD strategy in both formulation development and analytic studies are identical logically and conceptually, but they have somedifferences in terms of its terminology and application.Essential terminology and approach differences in this concept are; the determination of the analytic target profile, critical method characteristics, critical process parameters, and the determination of the method study area.However, the risk evaluation method which is necessary for the appropriate application of quality by design is also an inseparable part of the analytical quality by design.Despite those terminological differences, developing a qualitybased method with the analytical design that contributes to research with an appropriately applied risk-based design quality approach and provides multiple advantages that will be noticed each and every time, will be useful both for researchers and authorities who investigate license documentation and changes.Therefore, the terminology which is used for analytic quality by design and appropriate risk evaluation approaches are explained in this study.