Evidence map›Paper›PMID 17906920›Full record

ReviewJournal of pharmacokinetics and pharmacodynamics2007

Mechanism-based pharmacokinetic-pharmacodynamic modeling of antimicrobial drug effects.

David Czock, Frieder Keller

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of pharmacokinetics and pharmacodynamics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–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

53 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Uncertainty undermines the validity of antimicrobial pharmacodynamics.Journal of pharmacokinetics and pharmacodynamics · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations.Computational and structural biotechnology journal · 2022
    Article
  13. Review
  14. Article
  15. Synthesis and Antimycobacterial Activity of 3-Phenyl-1Molecules (Basel, Switzerland) · 2021
    Article
  16. Article
  17. Article
  18. Semimechanistic Modeling of Eravacycline Pharmacodynamics UsingAntimicrobial agents and chemotherapy · 2020
    Article
  19. Time-kill curves of daptomycin and Monte Carlo simulation for the treatment of bacteraemia caused by Enterococcus faecium.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2020
    Article
  20. Article
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

2 authors.

David CzockDivision of Nephrology, Medical Department, University Hospital Ulm, Robert-Koch-Str. 8, 89081 Ulm Germany. david.czock@uniklinik-ulm.de
Frieder Keller

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mathematical modeling of drug effects maximizes the information gained from an experiment, provides further insight into the mechanisms of drug effects, and allows for simulations in order to design studies or even to derive clinical treatment strategies. We reviewed modeling of antimicrobial drug effects and show that most of the published mathematical models can be derived from one common mechanism-based PK-PD model premised on cell growth and cell killing processes. The general sigmoid Emax model applies to cell killing and the various parameters can be related to common pharmacodynamics, which enabled us to synthesize and compare the different parameter estimates for a total of 24 antimicrobial drugs from published literature. Furthermore, the common model allows the parameters of these models to be related to the MIC and to a common set of PK-PD indices. Theoretically, a high Hill coefficient and a low maximum kill rate indicate so-called time-dependent antimicrobial effects, whereas a low Hill coefficient and a high maximum kill rate indicate so-called concentration-dependent effects, as illustrated in the garenoxacin and meropenem examples. Finally, a new equation predicting the time to microorganism eradication after repeated drug doses was derived that is based on the area under the kill-rate curve.

Indexed as

Anti-Infective AgentsDrug Resistance, MicrobialHumansMicrobial Sensitivity TestsModels, BiologicalAnti-Infective Agents

Identifiers

What OpenQuestion holds

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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.