Evidence map›Paper›PMID 23196713›Full record

ReviewClinical pharmacokinetics2013

Benchmarking therapeutic drug monitoring software: a review of available computer tools.

Aline Fuchs, Chantal Csajka, Yann Thoma, Thierry Buclin, Nicolas Widmer

Abstract readReview
PubMed Publisher
In one paragraph

Review in Clinical pharmacokinetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 3 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

65 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. A Critique of Pharmacokinetic Calculators for Drug Dosing Individualization.European journal of drug metabolism and pharmacokinetics · 2020
    Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. [Free online software tools for precision dosing of vancomycin, and other drugs]Revista de la Facultad de Ciencias Medicas (Cordoba, Argentina) · 2025
    Review
  13. State of Art of Dose Individualization to Support tacrolimus drug monitoring: What's Next?Transplant international : official journal of the European Society for Organ Transplantation · 2025
    Review
  14. Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Review

5 more citing papers are in PubMed but not listed here.

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

5 authors.

Aline FuchsDivision of Clinical Pharmacology, Service of Biomedicine, Department of Laboratory, Hôpital de Beaumont, Centre Hospitalier Universitaire Vaudois and University of Lausanne, 1011, Lausanne, Switzerland.
Chantal Csajka
Yann Thoma
Thierry Buclin
Nicolas Widmer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Indexed as

SoftwareBayes TheoremCosts and Cost AnalysisDose-Response Relationship, DrugDrug MonitoringHumansInformation Storage and RetrievalModels, BiologicalUser-Computer Interface

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.