ReviewTherapeutic drug monitoring2025
The Rational Basis for Personalized Treatment Using Concentration-Guided Dosing.
Review in Therapeutic drug monitoring, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Impact of adsorptive CRRT membranes on vancomycin pharmacokinetics in critically ill patients.Renal failure · 2026Review
- Mechanistic Artificial Intelligence for Personalized Drug Therapy: Integrating Pharmacokinetics, Pharmacodynamics, Therapeutic Drug Monitoring, and Multiomic Systems Biology.Pharmaceutics · 2026Review
- Exploring the effects of renal and cardiac functions on the pharmacokinetics of vancomycin in patients undergoing cardiac surgery: a population pharmacokinetic analysis.International journal of clinical pharmacy · 2026Article
- European Network on Optimizing Treatment With Therapeutic Antibodies in Chronic Inflammatory Diseases: Overview, Progress and Perspectives.Clinical and translational science · 2026Review
- Individualising drug therapy in intensive care.Anaesthesia and intensive care · 2026Article
- Therapeutic drug monitoring education: The current state.British journal of clinical pharmacology · 2026Article
- Digital twins in precision pharmacotherapy: emerging applications, challenges, and future directions.Frontiers in digital health · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe purpose of the review is to explain and encourage the use of terminology that distinguishes between the steps of measurement and reporting of concentrations, interpretation of the measurements, and subsequent prediction of individualized doses. The principles of concentration-guided dosing (CGD) provide a rational basis for personalized dosing. Existing terminology such as therapeutic drug monitoring (TDM) or model-informed precision dosing (MIPD) may have multiple meanings or be imprecisely defined. A brief history of CGD reveals the evolution of more accurate terminology focused on using concentration observations to provide individual drug dose guidance to clinicians.
methodsRelevant literature was identified using keyword searches such as "TDM," "therapeutic range," "individualized dosing," "target concentration intervention," "precision dosing," "MIPD," and "personalized dosing." Studies were included if they addressed the theoretical basis, clinical implementation, and/or effectiveness of CGD approaches. The findings were synthesized to underscore the relevance of a CGD approach in the context of clinical pharmacology.
resultsCGD is commonly implemented using either the therapeutic window approach (TWA) or the target concentration approach (TCA). The dosing approach is often not specified for TDM and MIPD. Clinicians, clinical pharmacologists, and pharmacists have typically been trained to view TWA as the gold standard for personalized dosing.
conclusionsAlthough many clinicians are well-versed in dosing using TWA, understanding and awareness of the benefits of TCA are still lacking. TCA offers accurate, personalized treatment by guiding the clinical team to use an optimally effective and safe dose for each patient.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.