From pharmacometric foundations to emerging artificial intelligence applications: A bibliometric analysis of model-informed precision dosing for anti-infective therapy (2005–2025) - Report - MDSpire
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From pharmacometric foundations to emerging artificial intelligence applications: A bibliometric analysis of model-informed precision dosing for anti-infective therapy (2005–2025)
Clinical Report: A Bibliometric Study on Model-Informed Precision Dosing
Overview
This bibliometric study analyzes the evolution of model-informed precision dosing (MIPD) in anti-infective therapy from 2005 to 2025, highlighting the integration of artificial intelligence and machine learning in pharmacometric approaches.
Background
Infection-related morbidity and mortality are significant global health concerns, necessitating optimized dosing regimens for antibiotics to combat resistance. The variability in pharmacokinetics among patients, especially in intensive care settings, emphasizes the need for precision dosing strategies.
Data Highlights
No numerical data available in the source material.
Key Findings
MIPD utilizes Bayesian forecasting to improve dosing accuracy based on individual patient data.
AI and machine learning technologies are being integrated into MIPD, enhancing traditional pharmacometric methods.
The study employs bibliometric techniques to map the research landscape of MIPD from 2005 to 2025.
There is a noted shift in focus from theoretical modeling to external validation in MIPD research.
MIPD is positioned as a convergence of pharmacology and health informatics, facilitating real-time patient data integration.
Clinical Implications
Clinicians should be aware of the evolving landscape of dosing strategies that incorporate advanced modeling techniques.
Conclusion
This study provides an overview of advancements in MIPD.
