AIMC Topic: Dose-Response Relationship, Drug

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Prediction of vancomycin dose on high-dimensional data using machine learning techniques.

Expert review of clinical pharmacology Apr 9, 2021
OBJECTIVES: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of ind...
Aged Male Middle Aged Cohort Studies Algorithms Dose-Response Relationship, Drug Humans Anti-Bacterial Agents Machine Learning Retrospective Studies Models, Biological Creatinine Female Vancomycin
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Mycophenolic Acid Exposure Prediction Using Machine Learning.

Clinical pharmacology and therapeutics Apr 6, 2021
Therapeutic drug monitoring of mycophenolic acid (MPA) based on area under the curve (AUC) is well-established and machine learning (ML) approaches could help to estimate AUC. The aim of this work is to estimate the AUC of MPA in organ transplant pat...
Adult Male Middle Aged Comorbidity Area Under Curve Time Factors Organ Transplantation Humans Bayes Theorem Age Factors Machine Learning Models, Biological Dose-Response Relationship, Drug Female Mycophenolic Acid Immunosuppressive Agents Aged
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Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity.

ChemMedChem Mar 16, 2021
Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making ...
Artificial Intelligence Drug Evaluation, Preclinical Antimalarials Parasitic Sensitivity Tests Protozoan Proteins Dose-Response Relationship, Drug Structure-Activity Relationship Plasmodium falciparum Molecular Structure Protein Kinase Inhibitors Mitogen-Activated Protein Kinase Kinases
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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...
Blood Coagulation International Normalized Ratio Pharmacology Systems Biology Dose-Response Relationship, Drug Models, Statistical Anticoagulants Humans Neural Networks, Computer
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Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker-driven precision dosing.

Clinical and translational science Feb 12, 2021
Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a c...
Biomarkers Precision Medicine Electronic Health Records Treatment Outcome Dose-Response Relationship, Drug Datasets as Topic Humans Machine Learning
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Early response to SPN-812 (viloxazine extended-release) can predict efficacy outcome in pediatric subjects with ADHD: a machine learning post-hoc analysis of four randomized clinical trials.

Psychiatry research Jan 5, 2021
Machine learning (ML) was used to determine whether early response can predict efficacy outcome in pediatric subjects with ADHD treated with SPN-812. We used data from four Phase 3 placebo-controlled trials of 100- to 600-mg/day SPN-812 (N=1397; 6-17...
Attention Deficit Disorder with Hyperactivity Viloxazine Clinical Trials as Topic Drug Administration Schedule Central Nervous System Stimulants Delayed-Action Preparations Adolescent Child Treatment Outcome Body Mass Index Humans Dose-Response Relationship, Drug Machine Learning Randomized Controlled Trials as Topic Female Double-Blind Method Male Body Weight
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Accelerating the identification of subtype selective inhibitors via Three-Dimensional Biologically Relevant Spectrum (BRS-3D): The monoamine oxidase subtypes as a case study.

Bioorganic chemistry Nov 24, 2020
Subtype-selective drugs are of great therapeutic importance as they are expected to be more effective and with less side-effects. However, discovery of subtype selective inhibitors was hampered by the high similarity of the binding sites within subfa...
Humans Support Vector Machine Dose-Response Relationship, Drug Structure-Activity Relationship Molecular Structure Monoamine Oxidase Monoamine Oxidase Inhibitors
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Weissella cibaria EIR/P2-derived exopolysaccharide: A novel alternative to conventional biomaterials targeting periodontal regeneration.

International journal of biological macromolecules Oct 22, 2020
Healing and regeneration of periodontium are considered as a complex physiological process. Therefore, treatments need to be addressed with highly effective components modulating the multiple pathways. In this study, exopolysaccharide (EPS) produced ...
Streptococcus mutans Chromatography, High Pressure Liquid Regeneration Biocompatible Materials Dextrans Humans Antioxidants Periodontium Anti-Bacterial Agents Polysaccharides, Bacterial Spectroscopy, Fourier Transform Infrared Weissella Biofilms Dose-Response Relationship, Drug Microbial Sensitivity Tests Cell Line
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Bolus pharmacokinetics: moving beyond mass-based dosing to guide drug administration.

Journal of pharmacokinetics and pharmacodynamics Aug 18, 2020
Despite the common approach of bolus drug dosing using a patient's mass, a more tailored approach would be to use empirically derived pharmacokinetic models. Previously, this could only be possible though the use of computer simulation using programs...
Infusions, Intravenous Models, Biological Body Weight Drug Dosage Calculations Drug Therapy, Computer-Assisted Artificial Intelligence Computer Simulation Point-of-Care Systems Dose-Response Relationship, Drug Humans
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Predicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling.

Archives of toxicology Jun 12, 2020
Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmaceutical companies as well as other industries and regulators. The goal of the current study was to develop an in vitro/in silico method for the rapid ...
Primary Cell Culture Actin Cytoskeleton Proto-Oncogene Mas Image Processing, Computer-Assisted High-Throughput Screening Assays Humans Microscopy, Fluorescence Hep G2 Cells Toxicity Tests Machine Learning Dose-Response Relationship, Drug Cellular Senescence Transcription Factor RelA Phenotype DNA Damage Chemical and Drug Induced Liver Injury Cell Death Risk Assessment Hepatocytes
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