This study introduces a sophisticated predictive framework for determining drug solubility and activity values in formulations via machine learning. The framework utilizes a comprehensive dataset consisting of more than 12,000 data rows and 24 input ...
Journal of chemical information and modeling
Jun 5, 2025
Determining accurate drug dissolution processes in the gastrointestinal tract is critical in drug discovery as dissolution profiles provide essential information for estimating the bioavailability of orally administered drugs. While various methods h...
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...
Drug-target interactions (DTIs) play a critical role in drug discovery and repurposing. Deep learning-based methods for predicting drug-target interactions are more efficient than wet-lab experiments. The extraction of original and substructural feat...
IEEE journal of biomedical and health informatics
May 6, 2025
It is well recognized that abnormal miRNA expression can result in drug resistance and pose a challenge to miRNA-based treatments. However, the drug-miRNA associations (DMA) are still incompletely understood. Conventional biological experiments have ...
The development of universal machine learning potentials (MLP) for small organic and drug-like molecules requires large, accurate datasets that span diverse chemical spaces. In this study, we introduce the QDπ dataset which incorporates data taken fr...
PURPOSE: Predicting powder blend flowability is necessary for pharmaceutical manufacturing but challenging and resource-intensive. The purpose was to develop machine learning (ML) models to help predict flowability across multiple flow categories, id...
Journal of pharmacokinetics and pharmacodynamics
Apr 16, 2025
The human milk/plasma (M/P) drug concentration ratio is crucial in pharmacology, especially for breastfeeding mothers undergoing treatment. It determines the extent to which drugs ingested by the mother pass into breast milk, potentially affecting th...
SAR and QSAR in environmental research
Apr 7, 2025
Drug discovery's success lies in potent inhibition against a target and optimum pharmacokinetic and toxicokinetic properties of drug molecules. Membrane permeability is a crucial factor in determining the absorption, distribution, metabolism, and exc...
Journal of chemical information and modeling
Apr 3, 2025
This study investigates the application of a deep learning (DL) model, specifically a message-passing neural network (MPNN) implemented through Chemprop, to predict the persistence, bioaccumulation, and toxicity (PBT) characteristics of compounds, wi...
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