AIMC Topic: Solubility

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Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface.

AAPS PharmSciTech
Nifedipine (NIF) is a dihydropyridine calcium channel blocker primarily used to treat conditions such as hypertension and angina. However, its low solubility and low bioavailability limit its effectiveness in clinical practice. Here, we developed a c...

POxload: Machine Learning Estimates Drug Loadings of Polymeric Micelles.

Molecular pharmaceutics
Block copolymers, composed of poly(2-oxazoline)s and poly(2-oxazine)s, can serve as drug delivery systems; they form micelles that carry poorly water-soluble drugs. Many recent studies have investigated the effects of structural changes of the polyme...

Comparative Analysis of Chemical Descriptors by Machine Learning Reveals Atomistic Insights into Solute-Lipid Interactions.

Molecular pharmaceutics
This study explores the research area of drug solubility in lipid excipients, an area persistently complex despite recent advancements in understanding and predicting solubility based on molecular structure. To this end, this research investigated no...

Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation.

International journal of pharmaceutics
A novel approach based on supervised machine-learning is proposed to predict the solubility of drugs and drug-like molecules in mixtures of organic solvents. Similar to quantitative structure-property relationship (QSPR) models, different solvent typ...

Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen.

Molecules (Basel, Switzerland)
Deep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or bet...

Enhancing Protein Solubility via Glycosylation: From Chemical Synthesis to Machine Learning Predictions.

Biomacromolecules
Glycosylation is a valuable tool for modulating protein solubility; however, the lack of reliable research strategies has impeded efficient progress in understanding and applying this modification. This study aimed to bridge this gap by investigating...

A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests.

BMC medical informatics and decision making
BACKGROUND: The pharmaceutical industry is continually striving to innovate drug development and formulation processes. Orally disintegrating tablets (ODTs) have gained popularity due to their quick release and patient-friendly characteristics. The c...

Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D
In June 2022, EU-OS came to the decision to make public a solubility data set of 100+K compounds obtained from several of the EU-OS proprietary screening compound collections. Leveraging on the interest of SLAS for screening scientific development it...

Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.

International journal of pharmaceutics
Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutical industry. These can offer a versatile tool for continuous manufacturing while supporting the framework of process analytical technology, quality-by...

Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Biophysical journal
Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming....