Recent advances in artificial intelligence (AI) and machine learning (ML) are revolutionizing nanopharmaceutical development by enabling data-driven formulation design, process optimization, and prediction of biological performance. AI encompasses co...
Recently, pharmaceutical cocrystal technology has garnered considerable global attention because of its innovativeness and environmental sustainability. This technology effectively enhances the bioavailability of poorly soluble drugs and optimizes th...
Journal of computer-aided molecular design
Dec 29, 2025
Integrating the techniques of deep learning, particularly graph neural network models, has made a significant advancement in drug discovery by facilitating effective exploration of chemical spaces and precise prediction of molecular properties. This ...
When the medicine-picking robot grasps drugs, its flexibility and accuracy in grasping detection mainly depend on the precision of visual guidance for the robot. The result of grasping detection directly determines whether the grasping task can be su...
Journal of chemical information and modeling
Dec 21, 2025
Absorption, distribution, metabolism, and excretion (ADME) properties are among the key factors in determining the success of lead discovery and optimization campaigns. Fast and accurate prediction of molecular ADME profiles is hence of particular in...
Journal of chemical information and modeling
Dec 17, 2025
The accurate identification of drug-target interactions is crucial for shortening the timeline and lowering the expenses of pharmaceutical research, as the discovery of novel drugs remains a highly complex, resource-intensive, and lengthy endeavor. D...
Journal of chemical information and modeling
Dec 17, 2025
In recent years, deep learning techniques have made significant advances in drug-target affinity (DTA) prediction. However, existing models still have considerable room for improvement in prediction accuracy, robustness, and generalization ability. T...
Journal of chemical information and modeling
Dec 10, 2025
We evaluate the feasibility of using co-folding models for synthetic data augmentation in training machine learning-based scoring functions (MLSFs) for binding affinity prediction. Our results show that performance gains depend critically on the stru...
Environmental geochemistry and health
Dec 10, 2025
Pharmaceutical pollutants are increasingly recognized as emerging contaminants in aquatic environments. Their persistence, bioactivity, and resistance to conventional treatment processes raise ecological and human health concerns, including the sprea...
Journal of chemical information and modeling
Dec 9, 2025
Accurate prediction of drug-target interactions (DTIs) is essential for drug discovery and repurposing. Despite recent advances, deep learning models often exhibit limited generalization under realistic cold-start scenarios and suffer from poor inter...
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