AIMC Topic: Pharmacokinetics

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Another string to your bow: machine learning prediction of the pharmacokinetic properties of small molecules.

Expert opinion on drug discovery May 10, 2024
INTRODUCTION: Prediction of pharmacokinetic (PK) properties is crucial for drug discovery and development. Machine-learning (ML) models, which use statistical pattern recognition to learn correlations between input features (such as chemical structur...
Humans Machine Learning Animals Pharmaceutical Preparations Models, Biological Pharmacokinetics Drug Discovery Drug Development
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Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Journal of chemical information and modeling Apr 2, 2024
Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one of the key factors for the successful marketing of drug candidates. Therefore, predicting half-life...
Quantitative Structure-Activity Relationship Small Molecule Libraries Machine Learning Half-Life Support Vector Machine Pharmacokinetics Pharmaceutical Preparations
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Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.

Expert opinion on drug metabolism & toxicology Mar 20, 2024
INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hamp...
Models, Biological Pharmacokinetics Drug Development Models, Molecular Pharmaceutical Preparations Drug Discovery Pharmacogenetics Machine Learning Computer Simulation Reproducibility of Results Drug Design Precision Medicine Humans Artificial Intelligence
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Deep-NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data.

CPT: pharmacometrics & systems pharmacology Mar 11, 2024
Noncompartmental analysis (NCA) is a model-independent approach for assessing pharmacokinetics (PKs). Although the existing NCA algorithms are very well-established and widely utilized, they suffer from low accuracies in the setting of sparse PK samp...
Pharmaceutical Preparations Models, Biological Pharmacokinetics Deep Learning Drug Development Algorithms Computer Simulation Humans
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Predicting Pharmacokinetics of Drugs Using Artificial Intelligence Tools: A Systematic Review.

European journal of drug metabolism and pharmacokinetics Mar 8, 2024
BACKGROUND AND OBJECTIVE: Pharmacokinetic studies encompass the examination of the absorption, distribution, metabolism, and excretion of bioactive compounds. The pharmacokinetics of drugs exert a substantial influence on their efficacy and safety. C...
Humans Artificial Intelligence Pharmaceutical Preparations Models, Biological Pharmacokinetics Animals Area Under Curve
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Transfer learning empowers accurate pharmacokinetics prediction of small samples.

Drug discovery today Mar 8, 2024
Accurate assessment of pharmacokinetic (PK) properties is crucial for selecting optimal candidates and avoiding downstream failures. Transfer learning is an innovative machine learning approach enabling high-throughput prediction with limited data. R...
Pharmacokinetics Machine Learning Drug Design
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Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.

Drug metabolism and pharmacokinetics Feb 17, 2024
Population pharmacokinetics/pharmacodynamics (pop-PK/PD) consolidates pharmacokinetic and pharmacodynamic data from many subjects to understand inter- and intra-individual variability due to patient backgrounds, including disease state and genetics. ...
Humans Pharmacokinetics Machine Learning Models, Biological
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A pharmacokinetic-pharmacodynamic model based on the SSA-1DCNN-Attention network and the semicompartment method.

Biotechnology & genetic engineering reviews Apr 5, 2023
To solve the problem of inaccurate prediction caused by the lack of representativeness of samples due to the small sample size of the collected clinical data when using machine learning methods to predict drug concentration in plasma and describe the...
Models, Biological Saponins Cynanchum Pharmacokinetics Mice Disease Models, Animal Epilepsy Algorithms Animals Neural Networks, Computer Machine Learning
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Systematic Evaluation of Local and Global Machine Learning Models for the Prediction of ADME Properties.

Molecular pharmaceutics Feb 6, 2023
Machine learning (ML) has become an indispensable tool to predict absorption, distribution, metabolism, and excretion (ADME) properties in pharmaceutical research. ML algorithms are trained on molecular structures and corresponding ADME assay data to...
Algorithms Drug Discovery Molecular Structure Machine Learning Quantitative Structure-Activity Relationship Pharmaceutical Preparations Pharmacokinetics
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Computational Predictions of Nonclinical Pharmacokinetics at the Drug Design Stage.

Journal of chemical information and modeling Jan 3, 2023
Although computational predictions of pharmacokinetics (PK) are desirable at the drug design stage, existing approaches are often limited by prediction accuracy and human interpretability. Using a discovery data set of mouse and rat PK studies at Roc...
Administration, Intravenous Rats Animals Humans Pharmaceutical Preparations Drug Design Neural Networks, Computer Biological Availability Models, Biological Pharmacokinetics
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