Evidence mapPaperPMID 35213979Full record

ReviewPharmaceutics2022

Application of Semi-Mechanistic Pharmacokinetic and Pharmacodynamic Model in Antimicrobial Resistance.

Kun Mi, Kaixiang Zhou, Lei Sun, Yixuan Hou, Wenjin Ma, Xiangyue Xu, Meixia Huo, Zhenli Liu, Lingli Huang

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. ComparativeAntimicrobial agents and chemotherapy · 2026
    Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
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  9. 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

9 authors.

Kun MiNational Reference Laboratory of Veterinary Drug Residues (HZAU), Wuhan 430000, China.ORCID 0000-0001-7058-1849
Kaixiang ZhouMAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China.ORCID 0000-0003-1411-9531
Lei SunNational Reference Laboratory of Veterinary Drug Residues (HZAU), Wuhan 430000, China.
Yixuan HouMAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China.
Wenjin MaMAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China.
Xiangyue XuMOA Laboratory for Risk Assessment of Quality and Safety of Livestock and Poultry Products, Huazhong Agricultural University, Wuhan 430000, China.
Meixia HuoMAO Key Laboratory for Detection of Veterinary Drug Residues, Huazhong Agricultural University, Wuhan 430000, China.
Zhenli LiuNational Reference Laboratory of Veterinary Drug Residues (HZAU), Wuhan 430000, China.
Lingli HuangNational Reference Laboratory of Veterinary Drug Residues (HZAU), Wuhan 430000, China.

Funding

fundamental research funds for the Central Universities 2662017PY081National key research and development program 2016YFD0501310National key research and development program 2018YFD500301
6 · The paper itself

Abstract

Antimicrobial resistance is a major public health issue. The pharmacokinetic/pharmacodynamic (PK/PD) model is an essential tool to optimize dosage regimens and alleviate the emergence of resistance. The semi-mechanistic PK/PD model is a mathematical quantitative tool to capture the relationship between dose, exposure, and response, in terms of the mechanism. Understanding the different resistant mechanisms of bacteria to various antibacterials and presenting this as mathematical equations, the semi-mechanistic PK/PD model can capture and simulate the progress of bacterial growth and the variation in susceptibility. In this review, we outline the bacterial growth model and antibacterial effect model, including different resistant mechanisms, such as persisting resistance, adaptive resistance, and pre-existing resistance, of antibacterials against bacteria. The application of the semi-mechanistic PK/PD model, such as the determination of PK/PD breakpoints, combination therapy, and dosage optimization, are also summarized. Additionally, it is important to integrate the PD effect, such as the inoculum effect and host response, in order to develop a comprehensive mechanism model. In conclusion, with the semi-mechanistic PK/PD model, the dosage regimen can be reasonably determined, which can suppress bacterial growth and resistance development.

Indexed as

antimicrobial resistancedosage regimenmathematical equationsemi-mechanistic PK/PD model

Identifiers

PMID35213979
PMCPMC8880204

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.