AIMC Topic: Pharmacokinetics

Clear Filters Showing 41 to 50 of 66 articles

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors.

CPT: pharmacometrics & systems pharmacology Jul 26, 2021
Model-informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowled...
Anti-Bacterial Agents Female Aged Aged, 80 and over Humans Machine Learning Models, Biological Vancomycin Drug Dosage Calculations Pharmacokinetics Adult Male Middle Aged Bayes Theorem
View on PubMed DOI

Machine learning models for classification tasks related to drug safety.

Molecular diversity Jun 10, 2021
In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015-2021). The study fo...
Machine Learning Tissue Distribution Algorithms ERG1 Potassium Channel Models, Molecular Drug Design Humans Drug-Related Side Effects and Adverse Reactions Support Vector Machine Neural Networks, Computer Pharmacokinetics Quantitative Structure-Activity Relationship
View on PubMed DOI

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...
Humans Neural Networks, Computer Machine Learning Algorithms Drug Evaluation, Preclinical ROC Curve Pharmacokinetics Support Vector Machine Models, Statistical Bayes Theorem
View on PubMed DOI

Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology.

Molecules (Basel, Switzerland) Apr 28, 2021
Oral bioavailability (F) is an essential determinant for the systemic exposure and dosing regimens of drug candidates. F is determined by numerous processes, and computational predictions of human estimates have so far shown limited results. We descr...
Pharmaceutical Preparations Models, Biological Drug Evaluation, Preclinical Supervised Machine Learning Humans Machine Learning Computer Simulation Administration, Oral Biological Availability Pharmacokinetics Quantitative Structure-Activity Relationship
View on PubMed DOI

Predicting drug metabolism and pharmacokinetics features of in-house compounds by a hybrid machine-learning model.

Drug metabolism and pharmacokinetics Apr 20, 2021
We constructed machine learning-based pharmacokinetic prediction models with very high performance. The models were trained on 26138 and 16613 compounds involved in metabolic stability and cytochrome P450 inhibition, respectively. Because the compoun...
Inactivation, Metabolic Reproducibility of Results Drug Discovery Predictive Value of Tests Pharmaceutical Preparations Cytochrome P-450 Enzyme System Pharmacokinetics Quantitative Structure-Activity Relationship Metabolic Clearance Rate Humans Machine Learning Computer Simulation
View on PubMed DOI

Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning.

Journal of pharmaceutical sciences Jan 23, 2021
Research into pharmacokinetics plays an important role in the development process of new drugs. Accurately predicting human pharmacokinetic parameters from preclinical data can increase the success rate of clinical trials. Since clearance (CL) which ...
Drug Elimination Routes Models, Biological Pharmacokinetics Species Specificity Metabolic Clearance Rate Humans Animals Drug Discovery Deep Learning Rats Pharmaceutical Preparations
View on PubMed DOI

Bayer's in silico ADMET platform: a journey of machine learning over the past two decades.

Drug discovery today Jul 9, 2020
Over the past two decades, an in silico absorption, distribution, metabolism, and excretion (ADMET) platform has been created at Bayer Pharma with the goal to generate models for a variety of pharmacokinetic and physicochemical endpoints in early dru...
Computer Simulation Pharmacokinetics Animals Intestinal Absorption Humans Models, Theoretical Machine Learning Pharmaceutical Preparations
View on PubMed DOI

Direct Comparison of Total Clearance Prediction: Computational Machine Learning Model versus Bottom-Up Approach Using In Vitro Assay.

Molecular pharmaceutics Jun 12, 2020
The in vitro-in vivo extrapolation (IVIVE) approach for predicting total plasma clearance (CL) has been widely used to rank order compounds early in discovery. More recently, a computational machine learning approach utilizing physicochemical descrip...
Models, Biological Madin Darby Canine Kidney Cells Microsomes, Liver Hepatocytes Permeability Pharmacokinetics Administration, Intravenous Plasma Liver Blood Proteins Pharmaceutical Preparations Male Humans Metabolic Clearance Rate Dogs Machine Learning Protein Binding Membranes, Artificial Animals Rats Rats, Sprague-Dawley
View on PubMed DOI

Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors.

Artificial intelligence in medicine Nov 27, 2019
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) plays an important role in diagnosis and grading of brain tumors. Although manual DCE biomarker extraction algorithms boost the diagnostic yield of DCE-MRI by providing quantitative infor...
Sensitivity and Specificity Brain Neoplasms Deep Learning Magnetic Resonance Imaging Algorithms Phantoms, Imaging Humans Contrast Media Regional Blood Flow Automation Pharmacokinetics Databases, Factual Prognosis Reproducibility of Results
View on PubMed DOI

Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology Nov 7, 2019
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...
Structure-Activity Relationship Molecular Structure Pharmaceutical Preparations Data Mining Computer-Aided Design Molecular Targeted Therapy Humans Drug Design Artificial Intelligence Pharmacokinetics Drug Discovery Databases, Factual Toxicology Big Data
View on PubMed DOI
Popular Topics
Recent Journals