AIMC Topic: Pharmaceutical Preparations

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Drug-Target Affinity Prediction Based on Topological Enhanced Graph Neural Networks.

Journal of chemical information and modeling Mar 31, 2025
Graph neural networks (GNNs) have achieved remarkable success in drug-target affinity (DTA) analysis, reducing the cost of drug development. Unlike traditional one-dimensional (1D) sequence-based methods, GNNs leverage graph structures to capture ric...
Neural Networks, Computer Graph Neural Networks Drug Discovery Proteins Pharmaceutical Preparations
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Application of Machine Learning and Mechanistic Modeling to Predict Intravenous Pharmacokinetic Profiles in Humans.

Journal of medicinal chemistry Mar 27, 2025
Accurate prediction of new compounds' pharmacokinetic (PK) profile in humans is crucial for drug discovery. Traditional methods, including allometric scaling and mechanistic modeling, rely on parameters from or testing, which are labor-intensive an...
Humans Machine Learning Drug Discovery Pharmaceutical Preparations Administration, Intravenous Models, Biological Pharmacokinetics
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SS-DTI: A deep learning method integrating semantic and structural information for drug-target interaction prediction.

Journal of bioinformatics and computational biology Mar 25, 2025
Drug-target interaction (DTI) prediction is pivotal in drug discovery and repurposing, providing a more efficient alternative to traditional wet-lab experiments by saving time and resources and expediting the identification of potential targets. Curr...
Semantics Drug Discovery Neural Networks, Computer Deep Learning Drug Repositioning Computational Biology Pharmaceutical Preparations Proteins
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Employing Automated Machine Learning (AutoML) Methods to Facilitate the ADMET Properties Prediction.

Journal of chemical information and modeling Mar 14, 2025
The rationale for using ADMET prediction tools in the early drug discovery paradigm is to guide the design of new compounds with favorable ADMET properties and ultimately minimize the attrition rates of drug failures. Artificial intelligence (AI) in ...
Pharmaceutical Preparations Automation Machine Learning Algorithms Computer Simulation Drug Discovery
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AI-aided chronic mixture risk assessment along a small European river reveals multiple sites at risk and pharmaceuticals being the main risk drivers.

Environment international Mar 13, 2025
The vast amount of registered chemicals leads to a high diversity of substances occurring in the environment and the creation of new substances outpaces chemical risk assessment as well as monitoring strategies. Hence, risk assessment strategies need...
Rivers Germany Pharmaceutical Preparations Animals Risk Assessment Environmental Monitoring Water Pollutants, Chemical Artificial Intelligence
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GramSeq-DTA: A Grammar-Based Drug-Target Affinity Prediction Approach Fusing Gene Expression Information.

Biomolecules Mar 12, 2025
Drug-target affinity (DTA) prediction is a critical aspect of drug discovery. The meaningful representation of drugs and targets is crucial for accurate prediction. Using 1D string-based representations for drugs and targets is a common approach that...
Drug Discovery Humans Neural Networks, Computer Pharmaceutical Preparations
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Development of hybrid robust model based on computational modeling and machine learning for analysis of drug sorption onto porous adsorbents.

Scientific reports Mar 12, 2025
This study investigates the utilization of three regression models, i.e., Kernel Ridge Regression (KRR), nu-Support Vector Regression ([Formula: see text]-SVR), and Polynomial Regression (PR) for the purpose of forecasting the concentration (C) of a ...
Adsorption Porosity Pharmaceutical Preparations Algorithms Computer Simulation Machine Learning
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Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization.

Molecular pharmaceutics Mar 7, 2025
The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds is critical to the drug discovery process. As such, machine learning (ML) models for ADME are widely used for prioritizing the design and synthesis o...
Deep Learning Pharmaceutical Preparations Neural Networks, Computer Drug Discovery Humans
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PocketDTA: A pocket-based multimodal deep learning model for drug-target affinity prediction.

Computational biology and chemistry Mar 6, 2025
Drug-target affinity prediction is a fundamental task in the field of drug discovery. Extracting and integrating structural information from proteins effectively is crucial to enhance the accuracy and generalization of prediction, which remains a sub...
Humans Neural Networks, Computer Proteins Pharmaceutical Preparations Drug Discovery Deep Learning
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Enhancing Predictions of Drug Solubility Through Multidimensional Structural Characterization Exploitation.

IEEE journal of biomedical and health informatics Mar 6, 2025
Solubility is not only a significant physical property of molecules but also a vital factor in small-molecule drug development. Determining drug solubility demands stringent equipment, controlled environments, and substantial human and material resou...
Pharmaceutical Preparations Solubility Humans Neural Networks, Computer
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