AIMC Topic: Solubility

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Predicting Melting Points of Organic Molecules: Applications to Aqueous Solubility Prediction Using the General Solubility Equation.

Molecular informatics
In this work we make predictions of several important molecular properties of academic and industrial importance to seek answers to two questions: 1) Can we apply efficient machine learning techniques, using inexpensive descriptors, to predict meltin...

Optimization of controlled release nanoparticle formulation of verapamil hydrochloride using artificial neural networks with genetic algorithm and response surface methodology.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
This study was performed to optimize the formulation of polymer-lipid hybrid nanoparticles (PLN) for the delivery of an ionic water-soluble drug, verapamil hydrochloride (VRP) and to investigate the roles of formulation factors. Modeling and optimiza...

Measurement and ANN prediction of pH-dependent solubility of nitrogen-heterocyclic compounds.

Chemosphere
Based on the solubility of 25 nitrogen-heterocyclic compounds (NHCs) measured by saturation shake-flask method, artificial neural network (ANN) was employed to the study of the quantitative relationship between the structure and pH-dependent solubili...

A nanoparticulate drug-delivery system for glaucocalyxin A: formulation, characterization, increased in vitro, and vivo antitumor activity.

Drug delivery
Glaucocalyxin A (GLA) is a phytochemical component with multiple pharmacological activities; however, glaucocalyxin A's wider use has been restricted by its poor solubility. In this study, GLA nanosuspensions were prepared with precipitation-combined...

Comparison of novel granulated pellet-containing tablets and traditional pellet-containing tablets by artificial neural networks.

Pharmaceutical development and technology
Novel granulated pellets technique was adopted to prepare granulated pellet-containing tablets (GPCT). GPCT and traditional pellet-containing tablets (PCT) were prepared according to 29 formulations devised by the Design Expert 7.0, with doxycycline ...

Design Space Exploration and Machine Learning Prediction of Hydrofluorocarbon Solubility in Ionic Liquids for Refrigerant Separation.

Journal of chemical information and modeling
Ionic liquids (ILs) are promising solvents for the separation of hydrofluorocarbon (HFC) mixtures due to their tunable solvation properties and negligible vapor pressure. We present a computational study of -32 and -125 solubility in over 341,000 ILs...

Development of machine learning models for estimation of disintegration time on fast-disintegrating tablets.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
The disintegration time for solid dosage oral formulations is directly influenced by diverse factors such as molecular properties, physical characteristics, excipient compositions, and formulation-specific attributes. This research addresses the chal...

Advancing Amorphous Solid Dispersions Design: Insights into Dissolution Kinetics via Thermodynamic Descriptor and Machine Learning.

Molecular pharmaceutics
Amorphous solid dispersions (ASD) are an effective strategy for enhancing the solubility and bioavailability of poorly soluble drugs. However, designing and optimizing ASD formulations often rely on extensive dissolution experiments without sufficie...

Predicting the solubility of drugs in supercritical carbon dioxide using machine learning and atomic contribution.

European journal of pharmaceutics and biopharmaceutics : official journal of Arbeitsgemeinschaft fur Pharmazeutische Verfahrenstechnik e.V
The pharmaceutical sector is aware of supercritical CO (SC-CO) as a possible replacement for problematic organic solvents. Using a novel artificial intelligence (AI) strategy to predict drug solubility using the SC-CO system mathematically has been d...