AIMC Topic: Solvents
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures.
Scientific reports
Aug 7, 2025
Analysis of small-molecule drug solubility in binary solvents at different temperatures was carried out via several machine learning models and integration of models to optimize. We investigated the solubility of rivaroxaban in both dichloromethane a...
Uncertainty-Informed Screening for Safer Solvents Used in the Synthesis of Perovskites via Language Models.
Journal of chemical information and modeling
Jul 22, 2025
Automated data curation for niche scientific topics, where data quality and contextual accuracy are paramount, poses significant challenges. Bidirectional contextual models such as BERT and ELMo excel in contextual understanding and determinism. Howe...
Temperature-Dependent Small-Molecule Solubility Prediction Using MoE-Enhanced Directed Message Passing Neural Networks.
Journal of chemical information and modeling
Jul 10, 2025
Solubility prediction is crucial for drug development and materials science, yet existing models struggle with generalizability across diverse solvents and temperatures. This study develops a novel solubility prediction model, DMPNN-MoE, which integr...
Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models.
Scientific reports
Jun 4, 2025
For analysis of crystallization, the solubility of drug in solvents should be correlated to input parameters. In this investigation, the solubility of salicylic acid as drug model in a variety of solvents is predicted through the utilization of multi...
Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique.
Scientific reports
Jun 3, 2025
This study develops and evaluates advanced hybrid machine learning models-ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)-optimized via the Black Widow Optim...
Ecofriendly Extraction of Polyphenols from Leaves Coupled with Response Surface Methodology and Artificial Neural Network-Genetic Algorithm.
Molecules (Basel, Switzerland)
May 28, 2025
This study aimed to optimize a novel deep eutectic solvents (DESs)-assisted extraction process for polyphenols in the leaves of (AGPL) with response surface methodology (RSM) and a genetic algorithm-artificial neural network (GA-ANN). Under the infl...
CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis.
Journal of chemical information and modeling
May 22, 2025
Some functional proteins undergo conformational changes to expose hidden binding sites when a binding molecule approaches their surface. Such binding sites are called cryptic sites and are important targets for drug discovery. However, it is still di...
Optimization of polyphenols extraction by deep eutectic solvent from broccoli stem and characterization of their composition and antioxidative effects.
Scientific reports
May 8, 2025
Broccoli stem is known to possess abundant polyphenols. To efficiently extract polyphenols from broccoli stems, we herein describe an updated deep eutectic solvent extraction (DESE) method. Response surface modeling was utilized for optimization of t...
Computational intelligence modeling and optimization of small molecule API solubility in supercritical solvent for production of drug nanoparticles.
Scientific reports
Apr 28, 2025
Artificial Intelligence (AI) is applied in this research for the analysis of a novel green method for production of nanomedicine. The method is based on supercritical solvent for production of drug nanoparticles in which the AI was used to estimate t...
A Flexible and Adhesive Strain Sensor Based on Deep Eutectic Solvents for Deep Learning-Assisted Signal Recognition.
ACS applied materials & interfaces
Apr 24, 2025
Flexible wearable electronic devices have garnered significant interest due to their inherent properties, serving as replacements for traditional rigid metal conductors in personal healthcare monitoring, human motion detection, and sensory skin appli...
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