Evidence map›Paper›PMID 40990332›Full record

ReviewTherapeutic drug monitoring2026

Therapeutic Drug Monitoring and Point-of-Care Technologies: Opportunities and Current Challenges.

Sandro Carrara, Nicolas Widmer, Francesca Rodino, Lin Du, Myriam Briki, Laurent A Decosterd, Catia Marzolini, Thierry Buclin, Yann Thoma, Monia Guidi

Abstract readReview
In one paragraph

Review in Therapeutic drug monitoring, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sandro CarraraBio/CMOS Interfaces Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Neuchâtel, Switzerland.
Nicolas WidmerService of Clinical Pharmacology, Department of Medicine and Pathology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.ORCID 0000-0001-7392-2418
Francesca RodinoBio/CMOS Interfaces Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Neuchâtel, Switzerland.
Lin DuBio/CMOS Interfaces Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Neuchâtel, Switzerland.
Myriam BrikiBio/CMOS Interfaces Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), Neuchâtel, Switzerland.
Laurent A DecosterdService of Clinical Pharmacology, Department of Medicine and Pathology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Catia MarzoliniService of Clinical Pharmacology, Department of Medicine and Pathology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Thierry BuclinService of Clinical Pharmacology, Department of Medicine and Pathology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
Yann ThomaPharmacy of the Eastern Vaud Hospitals (PHEL), Rennaz, Switzerland.
Monia GuidiService of Clinical Pharmacology, Department of Medicine and Pathology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.

Funding

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 200021_207900/1
6 · The paper itself

Abstract

backgroundThis review re-evaluates therapeutic drug monitoring (TDM) by comparing the current analytical and subsequent clinical interpretation capabilities of hospital or community medical laboratories with the emerging potential of point-of-care (POC) devices, which could become increasingly utilized in hospital wards, day-hospital units, and outpatient clinic settings.

methodsA narrative review was conducted to identify publications that best illustrate the current trends in the development of POC TDM.

resultsThe latest scientific and technical literature indicates that POC devices for determining drug concentrations in clinical samples are approaching the market. Several technologies are now available to develop portable sensors capable of rapidly returning concentration measurements. Interfacing these methods with artificial intelligence-based pattern recognition may enhance the identification and quantification of drugs. However, once the drug concentration is accurately measured using a portable device, dosage adjustments require consideration of the drug's pharmacokinetics and the patient's characteristics. This is accounted for in the mathematical approaches underlying model-informed precision dosing, which consider inter- and intra-individual variability and provide recommendations for treatment adjustments. These complexities necessitate the use of digital technologies, including graphical interfaces, machine learning approaches, and secure connectivity, to enhance the application of TDM in clinical practice.

conclusionsPromising emerging technologies have considerable potential to expand TDM to cover a wide range of drugs, making precision medicine accessible to many patients.

Indexed as

Drug MonitoringPoint-of-Care SystemsArtificial IntelligenceHumansbedside technologymachine learningmodel-informed precision dosingpharmacokineticspoint-of-care systems

Identifiers

PMID40990332
PMCPMC12771989

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.