About this Research Topic
Model-informed precision dosing (MIPD) of antibiotics is a burgeoning field that seeks to optimize antibacterial treatment by achieving target drug concentrations tailored to individual patients. The variability in pharmacokinetics among patients complicates the dosing process, necessitating therapeutic drug monitoring (TDM) to ensure effective treatment. Recent studies and meta-analyses have demonstrated that MIPD significantly enhances target attainment rates, reduces the time required to reach therapeutic levels, and minimizes adverse effects. Despite these advancements, a substantial proportion of patients—up to two-thirds—still fail to achieve the necessary drug concentrations for successful treatment. This gap underscores the need for further research into more effective MIPD strategies, including selecting and implementing population pharmacokinetic models, model averaging, and continuous learning approaches.
This research topic aims to highlight emerging approaches to improve model-informed precision dosing. Specifically, it seeks to explore computational methods for selecting and implementing pharmacokinetic models, as well as the prospective validation of these methods. Additionally, the research will investigate aspects beyond traditional models, such as the role of biosensing technologies in enhancing MIPD. By addressing these areas, the research aims to answer critical questions about the potential of current and novel methods to improve the precision and effectiveness of antibiotic dosing.
To gather further insights into the boundaries of model-informed precision dosing, we welcome articles addressing, but not limited to, the following themes:
- Computational methods for model selection and implementation
- Prospective validation of pharmacokinetic models
- Continuous learning and model updating techniques
- Biosensing technologies for real-time monitoring of antibiotic levels
- Integration of patient-specific data into dosing algorithms
- Comparative studies of different MIPD approaches
- Clinical outcomes associated with improved MIPD strategies
This research topic aims to highlight emerging approaches to improve model-informed precision dosing. Specifically, it seeks to explore computational methods for selecting and implementing pharmacokinetic models, as well as the prospective validation of these methods. Additionally, the research will investigate aspects beyond traditional models, such as the role of biosensing technologies in enhancing MIPD. By addressing these areas, the research aims to answer critical questions about the potential of current and novel methods to improve the precision and effectiveness of antibiotic dosing.
To gather further insights into the boundaries of model-informed precision dosing, we welcome articles addressing, but not limited to, the following themes:
- Computational methods for model selection and implementation
- Prospective validation of pharmacokinetic models
- Continuous learning and model updating techniques
- Biosensing technologies for real-time monitoring of antibiotic levels
- Integration of patient-specific data into dosing algorithms
- Comparative studies of different MIPD approaches
- Clinical outcomes associated with improved MIPD strategies
Keywords: Population pharmacokinetic model, Antibiotics, Model-informed precision dosing, Biosensing, Prospective validation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
