Solubility-dependent complexation of active pharmaceutical ingredients with trimethyl-β-cyclodextrin under supercritical fluid condition

The effect of the solubility of active pharmaceutical ingredients (APIs) in supercritical carbon dioxide (SC-CO₂) on their complexation behavior with trimethyl-β-cyclodextrin (TM-β-CD) has been investigated. Flurbiprofen or naproxen, the solubility of which is lower than that of ibuprofen, was mixed with TM-β-CD and the complexation phenomena on SC-CO₂ processing was evaluated using powder X-ray diffraction, differential scanning calorimetry and IR measurement. Drug complexation depended both on SC-CO₂ treatment time and on drug solubility in CO₂. The inclusion complex formation of flurbiprofen with TM-β-CD proceeded slowly compared with the case of ibuprofen. The slower complexation behavior was also observed when naproxen was used as the guest molecule. These results indicate that dissolution of drug molecules in SC-CO₂ is a rate-determining step for the inclusion complex formation with TM-β-CD and that complexation proceeds after dissolving the both components in SC-CO₂.     

Measurement and modeling of metoclopramide hydrochloride (anti-emetic drug) solubility in supercritical carbon dioxide

Knowledge of drug solubility data in supercritical carbon dioxide (SC-CO₂) is a fundamental step in producing nano and microparticles through supercritical fluid technology. In this work, for the first time, the solubility of metoclopramide hydrochloride (MCP) in SC-CO₂ was measured in pressure and temperature range of 12 to 27 MPa and 308 to 338 K, respectively. The results represented a range mole fractions of 0.15 × 10^-5 to 5.56 × 10^-5. To expand the application of the obtained data, six semi-empirical models and three models based on the Peng-Robinson equation of state (PR + VDW, PR + WS + Wilson and PR + MHV1 + COSMOSAC) with different mixing rules and various ways to describe intermolecular interactions were investigated. Furthermore, total enthalpy, sublimation enthalpy and solvation enthalpy relevant to MCP solvating in SC-CO₂ were estimated.     

Solubility of amphenicol bacteriostats in CO2

The solubilities of three veterinary amphenicol bacteriostats, chloramphenicol, florfenicol and thiamphenicol, were measured in supercritical carbon dioxide (SC-CO₂) by a re-circulating method at temperatures of 313.15 and 333.15 K and pressures ranging from 11.0 to 49.0 MPa. These compounds displayed very limited solubility in SC-CO₂ (10⁻⁵ to 10⁻⁷ mole fraction) over the range of experimental conditions. Chloramphenicol had the highest observed solubility of the three amphenicols, while the solubilities of florfenicol and thiamphenicol were almost an order of magnitude lower. The experimental solubility data were correlated with seven known density-based models. The density models (ln y versus ln ρ or ln ρ_r) gave better correlation than the semi-log scale of ln y versus ρ_r. Four models for ln E versus density correlations also gave better correlation than the semi-log scale of ln y versus ρ_r by introducing the enhancement factor E. The correlation accuracy of all the seven models mainly depends on the system investigated, measured density and temperature range.     

Theoretical and experimental study on Chloroquine drug solubility in supercritical carbon dioxide via the thermodynamic,multi-layer perceptron neural network (MLPNN), and molecular modeling

The design and development of supercritical carbon dioxide (sc-CO₂) based processes for production of pharmaceutical micro/nanoparticles is one of the interesting research topics of pharmaceutical industries owing to its attractive advantages. The solubility of drugs in sc-CO₂ at different temperatures and pressures is an essential parameter which should be determined for this purpose. Chloroquine as a traditional antirheumatic and antimalarial agent is approved as an effective drug for the treatment of Covid-19. Pishnamazi et al. (2021) measured the solubility of this drug in sc-CO₂ at the pressure range of 120–400 bar and temperature range of 308–338 K, and correlated the obtained data using some empirical models. In this work, a comprehensive computational approach was developed to more accurately study the supercritical solubility of Chloroquine. The thermodynamic models include two equations-of-state based models (Peng-Robinson and Soave-Redlich-Kowang) and two activity coefficient-based models (modified Wilson's and UNIQUAC)), as well as, a multi-layer perceptron neural network (MLPNN)) were used for this purpose. Also, molecular modeling was performed to study the electronic structure of Chloroquine and identify the potential centers of intermolecular interactions during the dissolution process. According to the obtained results, all of the theoretical models can predict Chloroquine solubility in sc-CO₂ with acceptable accuracy. Among these models, the MLPNN model possesses the highest precision with the lowest average absolute relative deviation (AARD%) of 1.76 % and the highest R_adj value of 0.999.     

Effect of supercritical CO2 on bulk hydrogenation of nitrile butadiene rubber catalyzed by RhCl(PPh3)3

The effect of supercritical (SC) CO₂ on the bulk hydrogenation of NBR entrapped with the catalyst (RhCl(PPh₃)₃) was investigated under various reaction times, reaction temperatures, hydrogen pressures and loadings of the catalyst and the thicknesses of the polymer films. CO₂ helps in improving the transport behaviour of catalyst in polymer matrices, as well as helping to move catalyst into or out of the polymer. A method for the measurement of the dissolution extent or the apparent solubility of the Rh based catalyst in SC-CO₂ was developed. It is found that high temperatures and high SC-CO₂ densities would enhance the apparent solubility. Cosolvents, such as acetone, are also found to increase the apparent solubility. Details on the hydrogenation process are also presented.     

Measurement and correlation of antifungal drugs solubility in pure supercritical CO2 using semiempirical models

In the present study the solubilities of two antifungal drugs of ketoconazole and clotrimazole in supercritical carbon dioxide were measured using a simple static method. The experimental data were measured at (308 to 348) K, over the pressure range of (12.2 to 35.5) MPa. The mole fraction solubilities ranged from 0.2 · 10^?6 to 17.45 · 10^?5. In this study five density based models were used to calculate the solubility of drugs in supercritical carbon dioxide. The density based models are Chrastil, modified Chrastil, Bartle, modified Bartle and Mendez-Santiago and Teja (M–T). Interaction parameters for the studied models were obtained and the percentage of average absolute relative deviation (AARD%) in each calculation was displayed. The correlation results showed good agreement with the experimental data. A comparison among the five models revealed that the Bartle and its modified models gave much better correlations of the solubility data with an average absolute relative deviation (AARD%) ranging from 4.8% to 6.2% and from 4.5% to 6.3% for ketoconazole and clotrimazole, respectively. Using the correlation results, the heat of drug–CO₂ solvation and that of drug vaporization was separately approximated in the range of (?22.1 to ?26.4 and 88.3 to 125.9) kJ · mol^?1.     

Multiple machine learning models for prediction of CO2 solubility in potassium and sodium based amino acid salt solutions

In this work, we developed artificial intelligence-based models for prediction and correlation of CO₂ solubility in amino acid solutions for the purpose of CO₂ capture. The models were used to correlate the process parameters to the CO₂ loading in the solvent. Indeed, CO₂ loading/solubility in the solvent was considered as the sole model’s output. The studied solvent in this work were potassium and sodium-based amino acid salt solutions. For the predictions, we tried three potential models, including Multi-layer Perceptron (MLP), Decision Tree (DT), and AdaBoost-DT. In order to discover the ideal hyperparameters for each model, we ran the method multiple times to find out the best model. R² scores for all three models exceeded 0.9 after optimization confirming the great prediction capabilities for all models. AdaBoost-DT indicated the highest R² Score of 0.998. With an R² of 0.98, Decision Tree was the second most accurate one, followed by MLP with an R² of 0.9.     

Formulation optimization and in situ absorption in rat intestinal tract of quercetin-loaded microemulsion

A new microemulsion system has been developed to increase the solubility and oral absorption of quercetin, a poorly water-soluble drug. The formulation of quercetin-loaded microemulsion was optimized by a simplex lattice experiment design. The optimized microemulsion formulation consisted of oil (7%, w/w), surfactant (48%, w/w), and cosurfactant (45%, w/w). Under this condition, the mean droplet diameter of microemulsion was 38.9 nm and solubility of quercetin in the microemulsion was 4.138 mg/ml. The in situ absorption property of quercetin-loaded microemulsion in rat intestine was studied and the results showed there was significant difference in absorption parameters such as K_a, t_1/2 and uptake percentages between microemulsion and micelle solution containing quercetin. The study on absorption percentage in different regions of rat intestine attested that the colon had the best permeability, followed by ileum, duodenum in order. It can be concluded that microemulsion can improve the solubility and oral absorption of quercetin, a poorly water-soluble drug.     

Ibuprofen-Cyclodextrin Inclusion Complex Formation using Supercritical Carbon Dioxide

Supercritical carbon dioxide (SC-CO₂) processing was performed with mixtures of cyclodextrins (CDs) and ibuprofen (IBP) to create inclusion complexes of ibuprofen and CD. Mixtures of IBP and trimethyl-β-CD showed new powder X-ray diffraction peaks after SC-CO₂ processing, although samples after processing with β-CD showed identical X-ray diffraction patterns with the physical mixture. The differential scanning calorimetry curves of samples after processing with trimethyl-β-CD showed no fusion peak of IBP and a new melting peak at around 185 °C. The physicochemical properties are similar to the co-precipitated samples of IBP and trimethyl-β-CD. Therefore, inclusion complex between IBP and trimethyl-β-CD was successfully prepared using SC-CO₂ technique. No inclusion formation was found when nitrogen was used as the supercritical fluid. Complexation of IBP and CD would not occur only on a high-pressure condition. The solubility of cyclodextrin into SC-CO₂ might play an important role in the formation of the inclusion complex.     

Inclusion complexes of fluconazole with β-cyclodextrin: physicochemical characterization and in vitro evaluation of its formulation

Fluconazole (FZ) is a triazole antifungal drug administered orally or intravenously. It is employed for the treatment of mycotic infections. However, the efficacy of FZ is limited with its poor aqueous solubility and low dissolution rate. One of the important pharmaceutical advantages of cyclodextrins is to improve pharmacological efficacy of drugs due to increasing their aqueous solubility. The aim of present study was to prepare an inclusion complex of FZ and β-cyclodextrin (β-CD) to improve the physicochemical and biopharmaceutical properties of FZ. The effects of β-CD on the solubility of FZ were investigated according to the phase solubility technique. Complexes were prepared with 1:1 M ratio by different methods namely, freeze-drying, spray-drying, co-evaporation and kneading. For the characterization of FZ/β-CD complex, FZ amount, practical yield %, thermal, aqueous solubility, XRD, FT-IR and NMR (¹H and ¹³C) analysis were performed. In vitro dissolution from hard cellulose capsules containing FZ/β-CD complexes was compared to pure FZ and its commercial capsules and evaluated by f₁ (difference) and f₂ (similarity) factors. Paddle method defined in USP 31 together with high pressure liquid chromatographic method were used in in vitro dissolution experiments. It was found that solubility enhancement by FZ/β-CD complexes depends on the type of the preparation method. High release of active agent from hard cellulose capsules prepared with β-CD complexes compared to commercial capsules was attributed to the interactions between β-CD and active agent, high energetic amorphous state and inclusion complex formation.     

Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization

Nowadays, supercritical fluid technology (SFT) has been an interesting scientific subject in disparate industrial-based activities such as drug delivery, chromatography, and purification. In this technology, solubility plays an incontrovertible role. Therefore, achieving more knowledge about the development of promising numerical/computational methods of solubility prediction to validate the experimental data may be advantageous for increasing the quality of research and therefore, the efficacy of novel drugs. Decitabine with the chemical formula C₈H₁₂N₄O₄ is a chemotherapeutic agent applied for the treatment of disparate bone-marrow-related malignancies such as acute myeloid leukemia (AML) by preventing DNA methyltransferase and activation of silent genes. This study aims to predict the optimum value of decitabine solubility in CO₂SCF by employing different machine learning-based mathematical models. In this investigation, we used AdaBoost (Adaptive Boosting) to boost three base models such as Linear Regression (LR), Decision Tree (DT), and GRNN. We used a dataset that has 32 sample points to make solubility models. One of the two input features is P (bar) and the other is T (k). ADA-DT (Adaboost Algorithm-Decision Tree), ADA-LR (Adaboost Algorithm-Linear Regresion), and ADA-GRNN (Generative Regression Neural Network) models showed MAE of 6.54 × 10^?5, 4.66 × 10^?5, and 8.35 × 10^?5, respectively. Also, in terms of R-squared score, these models have 0.986, 0.983, and 0.911 scores, respectively. ADA-LR was selected as the primary model according to numerical and visual analysis. Finally, the optimal values are (P = 400 bar, T = 3.38 K × 102, Y = 1.064 × 10^?3 mol fraction) using this model.     

Optimization of Fenoprofen solubility within green solvent through developing a novel and accurate GSO-GPR predictive model

Indisputable importance of drug solubility in various industrial perspectives has motivated the scientists to evaluate different techniques to improve it. Fenoprofen is a significant nonsteroidal anti-inflammatory drug (NSAID), that is the orally administered to relieve mild to moderate pain and the unfavorable symptoms of osteoarthritis and rheumatoid arthritis (i.e., inflammation and stiffness). Supercritical fluids (SCFs) belong to a certain type of fluids, in which their temperature and pressure are higher than the critical point. This property allows the CO₂SCF to simultaneously possess the characteristics of both a liquid and a gas. The prominent target of this paper is to mathematically develop three predictive models via machine learning (ML) technique to optimize the solubility of Fenoprofen in CO₂SCF. In this study, we have 32 data vectors in each dataset, including two input features of pressure and temperature. The output target is solubility, which we are going to model and analyze. Models are constructed through the use of Modular ANN (MANN), Gaussian processes regression (GPR), and the K-Nearest Neighbor technique (KNN) in this body of work. The glowworm swarm optimization (GSO) swarm-based method is utilized in order to carry out the process of model optimization. The root mean squared error (RMSE) rates for GSO-KNN, GSO-MANN, and GSO-GPR are respectively 5.25E-04, 5.46E-04, and 3.01E-05. The aforementioned models were also judged according to a number of other criteria, and since the GSO-GPR model was found to be the most effective according to all of these standards, it is being treated as the conclusive model of this investigation. In addition, the maximum error has been brought down to 5.02E-05 with the help of this model, which has an R2-score of 0.999.     

Improvement of opipramol base solubility by complexation with β-cyclodextrin

Opipramol (OPI), a tricyclic antidepressant and anxiolytic compound, is administered orally in the form of a dihydrochloride. Salt form of the drug has a higher solubility in water and hence bioavailability and stability. A similar effect can be achieved by closing the hydrophobic part of the drug molecule in the cyclodextrin cavity. The paper presents opipramol inclusion complexes with beta-cyclodextrin (β-CD) in 1:1 molar ratio. Studies on the formation of inclusion complexes were carried out both in solution and in the solid state. The formation and physicochemical characterisation of the complexes were determined by UV spectroscopic measurement (UV–vis), Fourier Transform Infrared (FTIR) Spectroscopy, ¹H Nuclear Magnetic Resonance (¹H NMR, 2D NOESY NMR), thermoanalytical methods (TGA – Termogravimetric analysis, DSC – differential scanning calorimetry), X-ray diffractometry (XRD) and scanning electron microscopy (SEM). The phase solubility profile with β-CD was classified as the A_N- type, indicating the formation of the inclusion complex with a drug.     

Rational Approaches for Drug Designing Against Leishmaniasis

Leishmaniasis has been ignored for many years mainly because it plagues remote and poor areas. However, recently, it has drawn attention of several investigators, and active research is going on for antileishmanial drug discovery. The current available drugs have high failure rates and significant side effects. Recently, liposomal preparations of amphotericin B are available and have proved to be a better drug, but they are very expensive. Miltefosine is one of the few orally administered drugs that are effective against Leishmania. However, it has exhibited teratogenicity, hence, should not be administered to pregnant women. Thus, the search for novel and improved antileishmanial drugs continue. A rational approach to design and develop new antileishmanials can be to identify several metabolic and biochemical differences between host and parasite that can be exploited as drug target. Moreover, many natural products also have significant antileishmanial activity and are yet to be exploited. In the current review, we aim to bring together various drug targets of Leishmania, recent development in the field, future prospects, and hope in the area.     

Determination of the composition,encapsulation efficiency and loading capacity in protein drug delivery systems using circular dichroism spectroscopy

Peptides and proteins have become very promising drug candidates in recent decades due to their unique properties. However, the application of these drugs has been limited by their high enzymatic susceptibility, low membrane permeability and poor bioavailability when administered orally. Considerable efforts have been made to design and develop drug delivery systems that could transport peptides and proteins to targeted area. Although it is of great importance to determine the composition after loading a drug to the carrier, the ability to do so is significantly limited by current analytical methods. In this letter, five important proteins, α₁-antitrypsin, hemoglobin human, human serum albumin, human transferrin and r-globulin were chemically conjugated to two model drug carriers, namely carbon dots and polymer O-(2-carboxyethyl) polyethylene glycol. A simple yet convenient method based on circular dichroism spectroscopy was developed to determine the compositions of the various protein-carrier conjugates.     

Factors Contributing to Solubility Synergism of Some Basic Drugs with β-Cyclodextrin in Ternary Molecular Complexes

Ternary complexes exploiting solubility synergism (SSn) between basic drugs and β-cyclodextrin (β-CD) in the presence of an organic hydoxy acid have been reported to provide the pharmaceutical technology with highly soluble ternary complexes, even with the least soluble β-CD. In this work, phase solubility techniques were used to study factors affecting SSn in aqueous solution, which may help in understanding the mechanism involved in ternary complex formation in solution, under equilibrium conditions. The equilibrium solubility of both β-CD and each of 8 structurally unrelated drugs were measured in tandem in the presence of different acid types at low and high pHs, and at different time intervals over a period of 1–40 days. The results indicate that SSn is evident regardless of acid type (organic and inorganic) at low pH, but the extent of SSn is acid type dependant and is limited by the drug salt solubility product constant (pK _sp). Among different drugs, no apparent trend exists between drug salt solubility and the extent of SSn, but lowering drug salt solubility by increasing pH depresses SSn. The results also reveal no apparent trend between the magnitude of the complex formation constant (K _ij) and SSn. For example, drugs of low K _ij values such as astemizole, cisapride and sildenafil do not show any SSn, yet ketotifen and pizotifen, which also have low K _ij values, exhibit substantial SSn. However, the solublizing power of β-CD represented by the slope of phase solubility diagram can be used as a marker for SSn (slopes exceeding 0.4 induce SSn).     

Binary and ternary solubilities of disperse dyes and their blend in supercritical carbon dioxide

Binary and ternary solubilities of C.I. Disperse Blue 134 (1,4-bis(isopropylamino)anthraquinone) C.I. Disperse Yellow 16 (3-methyl-1-phenyl-5-pyrazolone) and their dye mixture in supercritical carbon dioxide (SC-CO₂) were measured by a flow-type apparatus. The solubility measurements were carried out at the pressure ranges from 10.0 to 25.0 MPa for the binary systems at the temperatures from 323.15 to 383.15 K and for the ternary system at 383.15 K. An empirical equation was used to correlate the experimental binary solubilities of the dyes in terms of the density of carbon dioxide. To represent accurately the binary solubility of the dyes in terms of temperature and pressure, we used a modified Peng–Robinson–Stryjek–Vera equation of state (PRSV EOS). The ternary solubilities of the dye blend could be predicted successfully from binary parameters with the modified PRSV EOS.     

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters†

Physical encapsulation of drugs into polymer micelles is a common method of loading hydrophobic drugs. Methoxy polyethylene glycol‐poly(D,L‐lactide) (mPEG‐PDLLA) is one of the most commonly used drug carrier. At present, whether a carrier is suitable for the loading of a certain drug is determined by drug loading experiments. This process costs a lot of time. Therefore, an efficient predicting method to avoid time‐consuming tests is critical. In this study, we prepared mPEG_5k‐PDLLA_5k and used it to load a series of drugs. Three parameters were used to test the miscibility of mPEG_5k‐PDLLA_5k with drugs, including absolute difference in Hildebrand solubility parameters (|Δδ|), Flory–Huggins interaction parameter (χ) and the distance (D value) calculated from the two‐dimensional solubility parameters. We found the two‐dimensional solubility parameters obtained from JB2013 group contribution (GC) method was useful. By comparing the drug loading content (DLC) with the D value, we found that when the D value was less than 5.0 (MJ/m³)^1/2, the miscibility of drug and mPEG_5k‐PDLLA_5k was good and drug loading capability was high; when the D value was more than 8.0 (MJ/m³)^1/2, the drug was barely loaded. Thus, this work provided a rationale to qualitatively predict the loading capability of mPEG_5k‐PDLLA_5k for hydrophobic drugs.     

Structure based virtual screening of the Ebola virus trimeric glycoprotein using consensus scoring

Ebola virus (EBOV) causes zoonotic viral infection with a potential risk of global spread and a highly fatal effect on humans. Till date, no drug has gotten market approval for the treatment of Ebola virus disease (EVD), and this perhaps allows the use of both experimental and computational approaches in the antiviral drug discovery process. The main target of potential vaccines that are recently undergoing clinical trials is trimeric glycoprotein (GP) of the EBOV and its exact crystal structure was used in this structure based virtual screening study, with the aid of consensus scoring to select three possible hit compounds from about 36 million compounds in MCULE’s database. Amongst these three compounds, (5R)-5-[[5-(4-chlorophenyl)-1,2,4-oxadiazol-3-yl]methyl]-N-[(4-methoxyphenyl)methyl]-4,5-dihydroisoxazole-3-carboxamide (SC-2, C₂₁H₁₉ClN₄O₄) showed good features with respect to drug likeness, ligand efficiency metrics, solubility, absorption and distribution properties and non-carcinogenicity to emerge as the most promising compound that can be optimized to lead compound against the GP EBOV. The binding mode showed that SC-2 is well embedded within the trimeric chains of the GP EBOV with molecular interactions with some amino acids. The SC-2 hit compound, upon its optimization to lead, might be a good potential candidate with efficacy against the EBOV pathogen and subsequently receive necessary approval to be used as antiviral drug for the treatment of EVD.