AIMC Topic: Drug Monitoring
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Optimizing vancomycin dosing in pediatrics: a machine learning approach to predict trough concentrations in children under four years of age.
International journal of clinical pharmacy
Jun 11, 2024
BACKGROUND: Vancomycin trough concentration is closely associated with clinical efficacy and toxicity. Predicting vancomycin trough concentrations in pediatric patients is challenging due to significant inter-individual variability and rapid physiolo...
Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.
European archives of psychiatry and clinical neuroscience
May 21, 2024
In Europe, concentrations of ∆-tetrahydrocannabinol (THC) in cannabis resin (also known as hash) have risen markedly in the past decade, potentially increasing risks of mental health disorders. Current approaches to international drug monitoring cann...
Determining steady-state trough range in vancomycin drug dosing using machine learning.
Journal of critical care
Mar 18, 2024
BACKGROUND: Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care units (ICU). We aimed to predict the risk of inappropriate vancomycin trough levels and appropriate d...
Handheld Biosensor System Based on a Gradient Grating Period Guided-Mode Resonance Device.
Biosensors
Dec 30, 2023
Handheld biosensors have attracted substantial attention for numerous applications, including disease diagnosis, drug dosage monitoring, and environmental sensing. This study presents a novel handheld biosensor based on a gradient grating period guid...
Anti-infliximab antibodies and low infliximab levels correlate with drug discontinuation in pediatric inflammatory bowel disease.
Journal of pediatric gastroenterology and nutrition
Dec 27, 2023
BACKGROUND: Infliximab (IFX) use is limited by loss of response often due to the development of anti-IFX antibodies and low drug levels.
Machine Learning: A New Approach for Dose Individualization.
Clinical pharmacology and therapeutics
Sep 29, 2023
The application of machine learning (ML) has shown promising results in precision medicine due to its exceptional performance in dealing with complex multidimensional data. However, using ML for individualized dosing of medicines is still in its earl...
PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data.
Journal of biomedical informatics
Aug 17, 2022
Vancomycin is a commonly used antimicrobial in hospitals, and therapeutic drug monitoring (TDM) is required to optimize its efficacy and avoid toxicities. Bayesian models are currently recommended to predict the antibiotic levels. These models, howev...
Smart Portable Pen for Continuous Monitoring of Anaesthetics in Human Serum With Machine Learning.
IEEE transactions on biomedical circuits and systems
May 25, 2021
Continuous monitoring of anaesthetics infusion is demanded by anaesthesiologists to help in defining personalized dose, hence reducing risks and side effects. We propose the first piece of technology tailored explicitly to close the loop between anae...
A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters.
Scientific reports
Mar 10, 2021
The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing requirements. Our goal here was to use noninvasive clinical parameters to predict the dose-adjusted concentrations (C/D ratio) of LTG based on machine learnin...
Precision psychiatry in clinical practice.
International journal of psychiatry in clinical practice
Aug 27, 2020
The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing gui...
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