Publications by authors named "S Sassen"

Background: The level of inflammation alters drug pharmacokinetics (PK) in critically ill patients. This might compromise treatment efficacy. Understanding the specific effects of inflammation, measured by biomarkers, on drug absorption, distribution, metabolism, and excretion is might help in optimizing dosing strategies.

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Dexamethasone is crucial in pediatric acute lymphoblastic leukemia (ALL) treatment, however, studies regarding the pharmacokinetics of dexamethasone and its metabolites are scarce. Our study conducted a comprehensive pharmacokinetic-pharmacodynamic analysis of dexamethasone and metabolite, examining their association with dexamethasone-induced toxicity. Peak and trough concentrations were collected during the maintenance phase from pediatric ALL patients who received oral dexamethasone (6mg/m2/day).

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Background And Objective: When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization.

Methods: PK data and models describing both hospitalized patients (n = 134) receiving continuous vancomycin (26 models) and patients (n = 92) receiving imatinib in an outpatient setting (12 models) are included.

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Article Synopsis
  • - Achieving successful antimicrobial therapy requires personalized drug dosing due to differences in how patients metabolize drugs and their pathogens' susceptibility, which is reflected in minimum inhibitory concentration (MIC) values.
  • - Therapeutic drug monitoring (TDM) and population pharmacokinetic (popPK) models help tailor dosing regimens by analyzing drug behavior across various patients, while machine learning (ML) techniques can enhance dose individualization by identifying patterns in large datasets.
  • - The challenge is to balance model complexity with practical clinical application, ensuring regulatory compliance, accurate outcome measurement, and the incorporation of new technologies like real-time biosensors for better monitoring and adjustments in treatment.
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Background: Nintedanib is used to treat both idiopathic and progressive pulmonary fibrosis (IPF/PPF). Evidence of both an exposure-response relationship and an exposure-toxicity relationship has been found, suggesting the potential value of therapeutic drug monitoring (TDM). We aimed to define the therapeutic window of nintedanib in a real-world cohort.

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