AIMC Topic: Solubility

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

Biomacromolecules Apr 10, 2024
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...
Machine Learning Molecular Dynamics Simulation Solubility Glycoproteins Glycosylation
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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 Mar 27, 2024
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...
Excipients Hardness Tablets Humans Artificial Intelligence Solubility
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Outline and background for the EU-OS solubility prediction challenge.

SLAS discovery : advancing life sciences R & D Mar 20, 2024
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...
Drug Discovery Solubility Machine Learning Cheminformatics Humans
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Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.

International journal of pharmaceutics Mar 17, 2024
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...
Tablets Solubility Neural Networks, Computer Multivariate Analysis Meloxicam Drug Industry
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Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Biophysical journal Mar 4, 2024
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....
Thermodynamics Solvents Deep Learning Solubility Molecular Dynamics Simulation
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The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge.

SLAS discovery : advancing life sciences R & D Feb 3, 2024
The EUOS/SLAS challenge aimed to facilitate the development of reliable algorithms to predict the aqueous solubility of small molecules using experimental data from 100 K compounds. In total, hundred teams took part in the challenge to predict low, m...
Solubility Neural Networks, Computer Consensus Algorithms Databases, Chemical
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Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation.

Computers in biology and medicine Jan 3, 2024
Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite tremendous effort, machine learning prediction of protein solubility changes upon mutation remains a c...
Machine Learning Amino Acid Sequence Mutation Solubility
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Rapid screening of ternary amorphous formulations by a spray drying robot.

International journal of pharmaceutics Dec 23, 2023
Spray drying is commonly used for producing amorphous solid dispersions to improve drug solubility. The development of such formulations typically relies on comprehensive excipient and composition screening, which requires the preparation of many spr...
Drug Compounding Spray Drying Solubility Robotics Polymers
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Ensemble Geometric Deep Learning of Aqueous Solubility.

Journal of chemical information and modeling Nov 21, 2023
Geometric deep learning is one of the main workhorses for harnessing the power of big data to predict molecular properties such as aqueous solubility, which is key to the pharmacokinetic improvement of drug candidates. Two ensembles of graph neural n...
Water Solubility Deep Learning Thermodynamics Neural Networks, Computer
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Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

European journal of drug metabolism and pharmacokinetics Oct 21, 2023
BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) categorizes drugs into four classes on the basis of their solubility and metabolism. This framework allows for the study of the pharmacokinetics of transpor...
Solubility Pharmaceutical Preparations Biopharmaceutics Neural Networks, Computer Drug Interactions
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