ArticleIntensive care medicine2023
Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting.
Article in Intensive care medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Achievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis.Intensive care medicine · 2024Trial
- Evaluation of a model averaging algorithm for model-informed precision dosing in the context of parameter misspecifications.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- From Intelligent Operating Room to Smart ICU: Digital Continuity, AI-Supported Decision-Making and CRRT as a Model of Pharmacokinetic Personalization in Critical Care.Healthcare (Basel, Switzerland) · 2026Review
- Dosing Regimen Optimization of Aztreonam/Avibactam According to Renal Function Stratification: A Population Pharmacokinetic-Guided Simulation Study.Antibiotics (Basel, Switzerland) · 2026Article
- Application of escitalopram population pharmacokinetic repository: a step to precision dosing.Translational psychiatry · 2026Article
- Artificial Intelligence and Predictive Modelling for Precision Dosing of Immunosuppressants in Kidney Transplantation.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Guidance for External Evaluation and Selection of Population Pharmacokinetic Models for Precision Dosing.Clinical pharmacokinetics · 2026Review
- Article
- Population Pharmacokinetics and Dosing Regimen Optimization of Piperacillin in Critically Ill Patients.Drug design, development and therapy · 2026Article
- Toward Model-Informed Precision Dosing of Imipenem: Multicenter External Validation of Population Pharmacokinetic Models in Adult Critically Ill Patients.Drug design, development and therapy · 2026Article
- Newer antibiotics for drug-resistant Gram-negative infections in immunocompromised hosts: from pivotal trials to high-risk practice.Frontiers in cellular and infection microbiology · 2026Review
- Selecting the Most Robust Imipenem Pharmacokinetic Model Requires Paired Forecasts and Explicit Metric Weighting [Letter].Drug design, development and therapy · 2026Article
- Dose individualisation of antibiotics in critically ill patients with inflammation: A narrative review.British journal of clinical pharmacology · 2025Review
- Machine Learning-Based Model Selection and Averaging Outperform Single-Model Approaches for a Priori Vancomycin Precision Dosing.CPT: pharmacometrics & systems pharmacology · 2025Article
- Article
- [Empirical antibiotic therapy in life-threatening infections-current concepts and controversies].Die Anaesthesiologie · 2025Article
- First dose target attainment with extended infusion regimens of piperacillin and meropenem.Critical care (London, England) · 2025Article
- Recommended approaches for integration of population pharmacokinetic modelling with precision dosing in clinical practice.British journal of clinical pharmacology · 2025Review
- Review
- Therapeutic drug monitoring (TDM) of β-lactam/β-lactamase inhibitor (BL/BLI) drug combinations: insights from a pharmacometric simulation study.The Journal of antimicrobial chemotherapy · 2025Article
Corrections and comments
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Authors and funding
17 authors.
Funding
Abstract
purposeInadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models.
methodsA multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision.
resultsThe evaluation revealed a large inter-model variability (A: MPE - 135.6-78.3% and MAPE 35.7-135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|
conclusionThe predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.
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