Evidence map›Paper›PMID 39435440›Full record

ArticleFrontiers in microbiology2024

Prediction of tissue exposures of polymyxin-B, amikacin and sulbactam using physiologically-based pharmacokinetic modeling.

Mengyuan Wu, Kun Feng, Xiao Wu, Chang Liu, Shixing Zhu, Frederico S Martins, Mingming Yu, Zhihua Lv, Meixing Yan, Sherwin K B Sy

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Optimization of pediatric dosing regimens for aztreonam and amoxicillin/clavulanate combination therapy against multidrug-resistant bacteria.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

10 authors.

Mengyuan Wu *School of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Kun Feng *Women and Children Hospital, Qingdao University, Qingdao, China.
Xiao WuQingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, China.
Chang LiuWomen and Children Hospital, Qingdao University, Qingdao, China.
Shixing ZhuSchool of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Frederico S MartinsDepartment of Clinical and Toxicological Analysis, Faculty of Pharmaceutical Sciences, Universidade de São Paulo, São Paulo, Brazil.
Mingming YuSchool of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Zhihua LvSchool of Medicine and Pharmacy, Ocean University of China, Qingdao, China.
Meixing YanWomen and Children Hospital, Qingdao University, Qingdao, China.
Sherwin K B SyDepartment of Statistics, Universidade Estadual de Maringá, Maringá, Paraná, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The combination antimicrobial therapy consisting of amikacin, polymyxin-B, and sulbactam demonstrated Objectives: The objectives were to predict drug disposition and extrapolate their efficacy in the blood, lung, heart, muscle and skin tissues using a physiologically-based pharmacokinetic (PBPK) modeling approach and to evaluate achievement of target pharmacodynamic (PD) indices against Methods: A PBPK model was initially developed for amikacin, polymyxin-B, and sulbactam in adult subjects, and then scaled to pediatrics, accounting for both renal and non-renal clearances. The simulated plasma and tissue drug exposures were compared to the observed data from humans and rats. Efficacy was inferred using joint probability of target attainment of target PD indices. Results: The simulated plasma drug exposures in adults and pediatrics were within the 0.5 to 2 boundary of the mean fold error for the ratio between simulated and observed means. Simulated drug exposures in blood, skin, lung, and heart were consistent with reported penetration ratio between tissue and plasma drug exposure. In a virtual pediatric population from 2 to <18 years of age using pediatric dosing regimens, the interpretive breakpoints were achieved in 85-90% of the population. Conclusion: The utility of PBPK to predict and simulate the amount of antibacterial drug exposure in tissue is a practical approach to overcome the difficulty of obtaining tissue drug concentrations in pediatric population. As combination therapy, amikacin/polymyxin-B/sulbactam drug concentrations in the tissues exhibited sufficient penetration to combat extremely drug resistant

Indexed as

antibiotic combinationmultidrug resistance (MDR)pharmacodynamic indexphysiologically-based pharmacokinetictissue exposure

Identifiers

PMID39435440
PMCPMC11491386

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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.