Numerical optimization of drug solubility inside the supercritical carbon dioxide system using different machine learning models

Article Chemistry, Multidisciplinary

Determination of the solubility of rivaroxaban (anticoagulant drug, for the treatment and prevention of blood clotting) in supercritical carbon dioxide: Experimental data and correlations

Gholamhossein Sodeifian et al.

Summary: This study investigated the solubility of the anticoagulant drug rivaroxaban in supercritical carbon dioxide and examined the correlation of the drug solubility data using different models and equations.

ARABIAN JOURNAL OF CHEMISTRY (2023)

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Article Thermodynamics

Green processing based on supercritical carbon dioxide for preparation of nanomedicine: Model development using machine learning and experimental validation

Saad M. Alshahrani et al.

Summary: This study investigated the solubility data of ANA (Anastrozole) drug in a supercritical solvent and developed models to predict the solubility values. The aim was to provide a predictive methodology for determining drug solubility in various operational parameters for green pharmaceutical manufacturing. The models used temperature and pressure as inputs and employed three different models based on support vector regression. After optimization, all three models showed a coefficient of determination (R2) higher than 0.98. Additionally, considering RMSE, the error rates for Ada-Boosted SVR, Bagging SVR, and SVR were 2.31E-01, 4.31E-01, and 5.01E-01, respectively.

CASE STUDIES IN THERMAL ENGINEERING (2023)

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Article Chemistry, Physical

Solid solubility measurement of haloperidol in supercritical carbon dioxide and nanonization using the rapid expansion of supercritical solutions process

Salal Hasan Khudaida et al.

Summary: This study aimed to improve the dissolution rate of haloperidol by nanonization using the rapid expansion of supercritical solution (RESS) process. The solubility data of haloperidol in supercritical CO2 were measured and correlated, and the effects of operating parameters were compared and discussed. The crystal habit of haloperidol was modified and the mean particle size was reduced to 300 nm. The dissolution rate of haloperidol was enhanced by 74 times after the RESS processing.

JOURNAL OF SUPERCRITICAL FLUIDS (2023)

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Article Chemistry, Physical

Using the supercritical carbon dioxide as the solvent of Nystatin: Studying the effect of co-solvent, experimental and correlating

Seyed Ali Sajadian et al.

Summary: The solubility of Nystatin in supercritical CO2 was determined at different temperatures and pressures, with or without ethanol as a co-solvent. The solubility values were measured and found to be significantly increased by the addition of a co-solvent. The highest solubility of Nystatin was observed in the Nystatin-Ethanol-CO2 system, which was 24 times greater than the solubility in pure supercritical carbon dioxide.

JOURNAL OF SUPERCRITICAL FLUIDS (2023)

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Article Chemistry, Physical

An advanced computational method for studying drug nanonization using green supercritical-based processing for improvement of pharmaceutical bioavailability in aqueous media

Hua Xiao Li et al.

Summary: In this study, various non-mechanistic based models were implemented and compared for predicting drug solubility in supercritical solvent. The models were built using data collected from references and considering different operational circumstances. Small data sets have always been a challenge for machine learning models, so this study focused on models compatible with very small solubility data of drugs. The results showed that the ET model had the best accuracy in predicting drug solubility with a score of 0.9999 on the R2 criterion.

JOURNAL OF MOLECULAR LIQUIDS (2023)

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Article Chemistry, Physical

Analysis experimental and modeling of the solubility of an antiepileptic drug, Levetiracetam, in supercritical solvent

Ahmad J. Obaidullah et al.

Summary: This study investigates the solubility of Levetiracetam in supercritical carbon dioxide (scCO2) and models the process using various theoretical models. The results show acceptable precision and provide valuable data for the formulation of efficient drug delivery systems.

JOURNAL OF MOLECULAR LIQUIDS (2023)

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Article Chemistry, Physical

A global model for simulation of drug solubility in mono-solvents at different temperatures

Abolghasem Jouyban

Summary: A globally trained equation is proposed for calculating drug solubility in mono-solvents at different temperatures. The equation extends the van't Hoff model and includes input variables of Abraham, Hansen, Catalan, and Laurence parameters. The accuracy of the equation is studied by comparing the calculated and experimental values, showing its applicability in process design computations in the pharmaceutical industry.

JOURNAL OF MOLECULAR LIQUIDS (2023)

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Article Thermodynamics

Advanced modeling and intelligence-based evaluation of pharmaceutical nanoparticle preparation using green supercritical processing: Theoretical assessment of solubility

Amr S. Abouzied et al.

Summary: Modeling and simulations using machine learning techniques were conducted to determine the solubility of pharmaceuticals in supercritical solvents for green processing in pharmaceutics. Drug nanoparticles were formed and controlled to improve solubility and bioavailability. Three novel models, HHO-MLP, HHO-RR, and HHO-KNN, were developed for theoretical determination of solubility using temperature and pressure as inputs. The HHO-MLP model showed the best performance, with R2 of 0.995, RMSE of 0.194, and maximum error of 0.327. The findings can be used to estimate solubility over a wide range of temperature and pressure.

CASE STUDIES IN THERMAL ENGINEERING (2023)

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Article Thermodynamics

Implementing and tuning machine learning-based models for description of solubility variations of nanomedicine in supercritical solvent for development of green processing

Ahmad J. Obaidullah

Summary: This study utilizes machine learning models to describe the solubility of medicine and density of solvent in supercritical solvents such as CO2. The AdaBoost algorithm is used to boost the performance of base regression models, and the Hunter-Prey Optimization technique is employed to tune the hyper-parameters of these models. The results show that AdaBoost with GPR is the best model for predicting both the mole fraction and density.

CASE STUDIES IN THERMAL ENGINEERING (2023)

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Article Chemistry, Physical

Machine learning aided pharmaceutical engineering: Model development and validation for estimation of drug solubility in green solvent

Di Meng et al.

Summary: This research paper uses regression models and Glowworm Swarm Optimization to predict the solubility and density of Nystatin in SC-CO2. The results show that GSO-MLP and GSO-KNN have superior performance in predicting solubility and density. This study provides valuable insights for pharmaceutical and materials science research.

JOURNAL OF MOLECULAR LIQUIDS (2023)

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Article Pharmacology & Pharmacy

Overview and thermodynamic modelling of deep eutectic solvents as co-solvents to enhance drug solubilities in water

Atefeh Zarei et al.

Summary: This study provides an overview of solubility studies involving Deep Eutectic Solvents (DES) in drug dissolution and suggests the thermodynamic models to tackle the phase equilibrium modeling of such systems. The results indicate that DESs are effective co-solvents and NRTL model shows better performance in predicting solubility.

EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS (2023)

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Article Thermodynamics

Experimental and modeling investigation of Glibenclamide solubility in supercritical carbon dioxide

Nadia Esfandiari et al.

Summary: This article investigates the solubility of Glibenclamide in supercritical fluid for the first time. Six empirical models were used to analyze the correlation, and the results showed that Sodeifian et al. and MST models exhibited the highest accuracy.

FLUID PHASE EQUILIBRIA (2022)

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Article Chemistry, Multidisciplinary

Experimental analysis and thermodynamic modelling of lenalidomide solubility in supercritical carbon dioxide

Seyed Ali Sajadian et al.

Summary: This study experimentally determined the solubility of the anti-cancer drug Lenalidomide in supercritical carbon dioxide (sc-CO2) and analyzed the data using different theoretical models. The results showed that the modified Wilson's model provided an accurate correlation for the solubility of LND in sc-CO2, while the SRK-EoS did not show satisfactory accuracy.

ARABIAN JOURNAL OF CHEMISTRY (2022)

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Article Chemistry, Physical

Theoretical investigations on the manufacture of drug nanoparticles using green supercritical processing: Estimation and prediction of drug solubility in the solvent using advanced methods

Mohammed A. S. Abourehab et al.

Summary: We studied a novel green methodology for preparing nanomedicine without using organic solvents. Supercritical gas was used as the solvent, enhancing drug efficacy. Machine learning models were used to predict the solubility of a drug in supercritical carbon dioxide, and the PSVR model was determined to be the most accurate. This research provides robust and accurate models for predicting pharmaceutical solubility in different solvents and operational ranges.

JOURNAL OF MOLECULAR LIQUIDS (2022)

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Article Chemistry, Physical

Machine learning model for prediction of drug solubility in supercritical solvent: Modeling and experimental validation

Feifei An et al.

Summary: We developed a simulation methodology based on machine learning techniques to simulate pharmaceutical solubility in a supercritical solvent for nanodrug production. By fine-tuning the hyper-parameters using the Bat algorithm, the accuracy of the models has been significantly improved. GRNN model was selected as the primary model for the solubility prediction.

JOURNAL OF MOLECULAR LIQUIDS (2022)

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Review Computer Science, Artificial Intelligence

Harmony search algorithm and related variants: A systematic review

Feng Qin et al.

Summary: This article systematically reviews the harmony search (HS) algorithm and its variants from three aspects: describing the basic HS principle, discussing the impact of HS improvement on algorithm performance, and analyzing the characteristics and applications of HS variants. It is found that the improvement of HS mainly focuses on parameter enhancement and the integration with other metaheuristic algorithms, providing future directions for enhancing HS.

SWARM AND EVOLUTIONARY COMPUTATION (2022)

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Article Chemistry, Physical

Machine learning based simulation of an anti-cancer drug (busulfan) solubility in supercritical carbon dioxide: ANFIS model and experimental validation

Huimin Zhu et al.

Summary: In this study, a novel machine learning method based on ANFIS was developed for predicting drug solubility in supercritical solvents. The model showed high accuracy in both training and testing steps, indicating its potential for accurately predicting drug solubility and improving drug efficacy.

JOURNAL OF MOLECULAR LIQUIDS (2021)

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Article Chemistry, Physical