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Solubility

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Mathematical modeling and numerical simulation of supercritical processing of drug nanoparticles optimization for green processing: AI analysis.

PloS one
In recent decades, unfavorable solubility of novel therapeutic agents is considered as an important challenge in pharmaceutical industry. Supercritical carbon dioxide (SCCO2) is known as a green, cost-effective, high-performance, and promising solven...

Sludge bound-EPS solubilization enhance CH bioconversion and membrane fouling mitigation in electrochemical anaerobic membrane bioreactor: Insights from continuous operation and interpretable machine learning algorithms.

Water research
Bound extracellular polymeric substances (EPS) are complex, high-molecular-weight polymer mixtures that play a critical role in pore clogging, foulants adhesion, and fouling layer formation during membrane filtration, owing to their adhesive properti...

A comprehensive study of pharmaceutics solubility in supercritical solvent through diverse thermodynamic and hybrid Machine learning approaches.

International journal of pharmaceutics
The pharmaceutical industry is increasingly drawn to the research of innovative drug delivery systems through the use of supercritical CO (scCO)-based techniques. Measuring the solubility of drugs in scCO at varying conditions is a crucial parameter ...

Advancing pharmaceutical Intelligence via computationally Prognosticating the in-vitro parameters of fast disintegration tablets using Machine Learning models.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
The field of Machine Learning (ML) has garnered significant attention, particularly in healthcare for predicting disease severity. Recently, the pharmaceutical sector has also adopted ML techniques in various stages of drug development. Tablets are t...

Intelligence computational analysis of letrozole solubility in supercritical solvent via machine learning models.

Scientific reports
Supercritical fluids (SCFs) can be used to prepare drugs nanoparticles with improved solubility. SCFs have shown superior advantages in pharmaceutical industry as an environmentally friendly alternative to toxic/harmful organic solvents. They possess...

Prediction of Solubility of Proteins in Escherichia coli Based on Functional and Structural Features Using Machine Learning Methods.

The protein journal
Protein solubility is a critical parameter that determines the stability, activity, and functionality of proteins, with broad and far-reaching implications in biotechnology and biochemistry. Accurate prediction and control of protein solubility are e...

Machine learning driven bioequivalence risk assessment at an early stage of generic drug development.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
BACKGROUND: Bioequivalence risk assessment as an extension of quality risk management lacks examples of quantitative approaches to risk assessment at an early stage of generic drug development. The aim of our study was to develop a model-based approa...

Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors.

Molecular pharmaceutics
Monoclonal antibodies (mAbs) have found extensive applications and development in treating various diseases. From the pharmaceutical industry's perspective, the journey from the design and development of mAbs to clinical testing and large-scale produ...

Phosphate-solubilizing fungus (PSF) - mediated phosphorous solubilization and validation through Artificial intelligence computation.

World journal of microbiology & biotechnology
Phosphate-solubilizing fungus (PSF) strain alaromyces funiculosus was investigated for phosphorus solubilization, utilizing a range of pH levels and phosphate sources, followed by data confirmation through artificial intelligence modeling. T. funicul...

Data-driven insights into the properties of liquisolid systems based on machine learning algorithms.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Liquisolid systems (LS) represent a formulation approach where liquid drug or its dispersion is transformed into a powder with good flowability and compactibility, leading to enhanced drug dissolution and bioavailability. Many research groups have fo...