Thermodynamic study on solubility of brain tumor drug in supercritical solvent: Temozolomide case study

Solubility of lumiracoxib in supercritical carbon dioxide

This study aims to use a static-based solubility method for measuring the solubility of lumiracoxib at a temperature of 308-338 K and pressure of 120-400 bar for the first time. The obtained solubility data for lumiracoxib is between 4.74 × 10-5 and 3.46 × 10-4 (mole fraction) for the studied ranges of pressure and temperature. The solubility values reveal that the lumiracoxib experiences a crossover pressure of about 160 bar. Moreover, the measured solubility data of these two drugs are correlated with density-based semi-empirical correlations namely Bartle et al., Mendez-Santiago-Teja, Kumar and Johnstone, Chrastil and modified Chrastil models with an average absolute relative deviation of 10.7%, 9.5%, 9.8%, 7.8%, and 8.7% respectively for lumiracoxib. According to these findings, it is obvious that all of the examined models are rather accurate and there is no superiority between these models for both examined drugs although the Chrastil model is slightly better in the overall view.

Computational simulation and target prediction studies of solubility optimization of decitabine through supercritical solvent

Computational analysis of drug solubility was carried out using machine learning approach. The solubility of Decitabine as model drug in supercritical CO₂ was studied as function of pressure and temperature to assess the feasibility of that for production of nanomedicine to enhance the solubility. The data was collected for solubility optimization of Decitabine at the temperature 308-338 K, and pressure 120-400 bar used as the inputs to the machine learning models. A dataset of 32 data points and two inputs (P and T) have been applied to optimize the solubility. The only output is Y = solubility, which is Decitabine mole fraction solubility in the solvent. The developed models are three models including Kernel Ridge Regression (KRR), Decision tree Regression (DTR), and Gaussian process (GPR), which are used for the first time as a novel model. These models are optimized using their hyper-parameters tuning and then assessed using standard metrics, which shows R²-score, KRR, DTR, and GPR equal to 0.806, 0.891, and 0.998. Also, the MAE metric shows 1.08E-04, 7.40E-05, and 9.73E-06 error rates in the same order. The other metric is MAPE, in which the KRR error rate is 4.64E-01, DTR shows an error rate equal to 1.63E-01, and GPR as the best mode illustrates 5.06E-02. Finally, analysis using the best model (GPR) reveals that increasing both inputs results in an increase in the solubility of Decitabine. The optimal values are (P = 400, T = 3.38E + 02, Y = 1.07E-03).

Liposomal-Based Formulations: A Path from Basic Research to Temozolomide Delivery Inside Glioblastoma Tissue

Glioblastoma (GBM) is a lethal brain cancer with a very difficult therapeutic approach and ultimately frustrating results. Currently, therapeutic success is mainly limited by the high degree of genetic and phenotypic heterogeneity, the blood brain barrier (BBB), as well as increased drug resistance. Temozolomide (TMZ), a monofunctional alkylating agent, is the first line chemotherapeutic drug for GBM treatment. Yet, the therapeutic efficacy of TMZ suffers from its inability to cross the BBB and very short half-life (~2 h), which requires high doses of this drug for a proper therapeutic effect. Encapsulation in a (nano)carrier is a promising strategy to effectively improve the therapeutic effect of TMZ against GBM. Although research on liposomes as carriers for therapeutic agents is still at an early stage, their integration in GBM treatment has a great potential to advance understanding and treating this disease. In this review, we provide a critical discussion on the preparation methods and physico-chemical properties of liposomes, with a particular emphasis on TMZ-liposomal formulations targeting GBM developed within the last decade. Furthermore, an overview on liposome-based formulations applied to translational oncology and clinical trials formulations in GBM treatment is provided. We emphasize that despite many years of intense research, more careful investigations are still needed to solve the main issues related to the manufacture of reproducible liposomal TMZ formulations for guaranteed translation to the market.

A critical review on the particle generation and other applications of rapid expansion of supercritical solution

The novel particle generation processes of Active Pharmaceutical Ingredient (API)/drug have been extensively explored in recent decades due to their wide-range applications in the pharmaceutical industry. The Rapid Expansion of Supercritical Solutions (RESS) is one of the promising techniques to obtain the fine particles (micro to nano-size) of APIs with narrow particle size distribution (PSD). In RESS, supercritical carbon dioxide (SC CO₂) and API are used as solvent and solute respectively. In this literature survey, the application of RESS in the formation of fine particles is critically reviewed. Solubility of API in SC CO₂ and supersaturation are the key factors in tuning the particle size. The different approaches to model and predict the solubility of API in SC CO₂ are discussed. Then, the effect of process parameters on mean particle size and the particle size distribution are interpreted in the context of solubility and supersaturation. Furthermore, the less-explored applications of RESS in preparation of solid-lipid nanoparticles, liposome, polymorphic conversion, cocrystallization and inclusion complexation are compared with traditional processes. The solubility enhancement of API in SC CO₂ using co-solvent and its applications in particle generation are explored in published literature. The development and modifications in the conventional RESS process to overcome the limitations of RESS are presented. Finally, the perspective on RESS with special attention to its commercial operation is highlighted.

Resource recovery from landfill leachate: An experimental investigation and perspectives

This work investigates the performances of coconut shell waste-based activated carbon (CSWAC) adsorption in batch studies for removal of ammoniacal nitrogen (NH₃-N) and refractory pollutants (as indicated by decreasing COD concentration) from landfill leachate. To valorize unused resources, coconut shell, recovered and recycled from agricultural waste, was converted into activated carbon, which can be used for leachate treatment. The ozonation of the CSWAC was conducted to enhance its removal performance for target pollutants. The adsorption mechanisms of refractory pollutants by the adsorbent are proposed. Perspectives on nutrient recovery technologies from landfill leachate from the view-points of downstream processing are presented. Their removal efficiencies for both recalcitrant compounds and ammoniacal nitrogen were compared to those of other techniques reported in previous work. It is found that the ozonated CSWAC substantially removed COD (i.e. 76%) as well as NH₃-N (i.e. 75%), as compared to the CSWAC without pretreatment (i.e. COD: 44%; NH₃-N: 51%) with NH₃-N and COD concentrations of 2750 and 8500 mg/L, respectively. This reveals the need of ozonation for the adsorbent to improve its performance for the removal of COD and NH₃-N at optimized reactions: 30 g/L of CSWAC, pH 8, 200 rpm of shaking speed and 20 min of reaction time. Nevertheless, treatment of the leachate samples using the ozonated CSWAC alone was still unable to result in treated effluents that could meet the COD and NH₃-N discharge standards below 200 and 5 mg/L, respectively, set by legislative requirements. This reveals that another treatment is necessary to be undertaken to comply with the requirement of their effluent limit.