AI Medical Compendium Journal:
Journal of pharmacokinetics and pharmacodynamics

Showing 1 to 10 of 15 articles

Machine learning approaches for assessing medication transfer to human breast milk.

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...
Female Humans Bayes Theorem Milk, Human Pharmaceutical Preparations Neural Networks, Computer Machine Learning Breast Feeding Support Vector Machine Algorithms Principal Component Analysis
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Model-informed approach to estimate treatment effect in placebo-controlled clinical trials using an artificial intelligence-based propensity weighting methodology to account for non-specific responses to treatment.

Journal of pharmacokinetics and pharmacodynamics Dec 10, 2024
In randomized, placebo controlled clinical trials (RCT) in major depressive disorders (MDD), treatment response (TR) is estimated by the change from baseline at study-end (EOS) of the scores of clinical scales used for assessing disease severity. Tre...
Humans Artificial Intelligence Propensity Score Antidepressive Agents Placebo Effect Models, Statistical Randomized Controlled Trials as Topic Depressive Disorder, Major Treatment Outcome
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Generative models for synthetic data generation: application to pharmacokinetic/pharmacodynamic data.

Journal of pharmacokinetics and pharmacodynamics Aug 27, 2024
The generation of synthetic patient data that reflect the statistical properties of real data plays a fundamental role in today's world because of its potential to (i) be enable proprietary data access for statistical and research purposes and (ii) i...
Humans Neural Networks, Computer Pharmacokinetics Deep Learning Models, Statistical
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pyDarwin machine learning algorithms application and comparison in nonlinear mixed-effect model selection and optimization.

Journal of pharmacokinetics and pharmacodynamics Jun 28, 2024
Forward addition/backward elimination (FABE) has been the standard for population pharmacokinetic model selection (PPK) since NONMEM® was introduced. We investigated five machine learning (ML) algorithms (Genetic algorithm [GA], Gaussian process [GP]...
Nonlinear Dynamics Pharmacokinetics Humans Machine Learning Computer Simulation Models, Biological Algorithms
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Learning pharmacometric covariate model structures with symbolic regression networks.

Journal of pharmacokinetics and pharmacodynamics Oct 21, 2023
Efficiently finding covariate model structures that minimize the need for random effects to describe pharmacological data is challenging. The standard approach focuses on identification of relevant covariates, and present methodology lacks tools for ...
Time Factors Propofol Humans Neural Networks, Computer
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Application of machine learning based methods in exposure-response analysis.

Journal of pharmacokinetics and pharmacodynamics Mar 11, 2022
Robust estimation of exposure response analysis relies on correct specification of the model structure with traditional parametric approach. However, the assumptions of the handcrafted model may not always hold or verifiable. Here, we conducted a sim...
Machine Learning Logistic Models Propensity Score Computer Simulation
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Population pharmacokinetic model selection assisted by machine learning.

Journal of pharmacokinetics and pharmacodynamics Oct 27, 2021
A fit-for-purpose structural and statistical model is the first major requirement in population pharmacometric model development. In this manuscript we discuss how this complex and computationally intensive task could benefit from supervised machine ...
Neural Networks, Computer Models, Statistical Machine Learning Algorithms
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Fast screening of covariates in population models empowered by machine learning.

Journal of pharmacokinetics and pharmacodynamics May 21, 2021
One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from sup...
ROC Curve Support Vector Machine Bayes Theorem Drug Evaluation, Preclinical Models, Statistical Machine Learning Algorithms Humans Neural Networks, Computer Pharmacokinetics
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Reduction of quantitative systems pharmacology models using artificial neural networks.

Journal of pharmacokinetics and pharmacodynamics Mar 2, 2021
Quantitative systems pharmacology models are often highly complex and not amenable to further simulation and/or estimation analyses. Model-order reduction can be used to derive a mechanistically sound yet simpler model of the desired input-output rel...
Systems Biology Dose-Response Relationship, Drug Humans Neural Networks, Computer Blood Coagulation Models, Statistical Anticoagulants International Normalized Ratio Pharmacology
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A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Journal of pharmacokinetics and pharmacodynamics Oct 26, 2020
Deep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven domains such as biology ...
Treatment Outcome Models, Biological Precision Medicine Drug Therapy Humans Deep Learning Biological Variation, Population Computer Simulation Datasets as Topic
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