Prediction of Tissue Exposures of Meropenem, Colistin, and Sulbactam in Pediatrics Using Physiologically Based Pharmacokinetic Modeling

Zhu, Shijiang; Zhang, Jiayuan; Lv, Zhihua; Zhu, Peijuan; Oo, Charles; Yu, Mingming; Sy, Sherwin K. B.

doi:10.1007/s40262-022-01161-y

Cited by 12 publications

(12 citation statements)

References 79 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The P‐PBPK dose prediction articles included in the study, the name of the drug, the platform, and the study's funding are described in Table 1. Verified PBPK models of drugs are presented in support of pediatric dose prediction (Figure 4): 13 articles reported results from P‐PBPK models, which are presented in support of dose selection, 30–42 five articles were on the optimization of dosage in the design of future pediatric clinical studies, 3,29,43–45 and six articles reported findings from studies on determining dose regimens 46–51 . Fourteen publications were on some special pediatric populations and uncommon diseases with an assessment of renal impairment, 52–56 children with obesity, 57–60 and pediatric patients with severe coronavirus disease 2019 (COVID‐19) disease 61–65 .…”

Section: Resultsmentioning

confidence: 99%

“…One recent study has used the P‐PBPK model to support pediatric dosing regimens of meropenem/colistin/sulbactam in a co‐administration setting against infections in the blood, lung, skin, and heart tissues due to Acinetobacter baumannii . The P‐PBPK models of meropenem, colistin, and sulbactam were developed using PK‐Sim (version 10.0) 48 . Given the challenges in conducting pediatric studies, it is beneficial to use verified PBPK models to predict changes in drug exposure in various scenarios to guide dosing information when clinical trials are not possible, especially in pediatric subjects <2 years old.…”

Section: Resultsmentioning

confidence: 99%

“…Verified PBPK models of drugs are presented in support of pediatric dose prediction (Figure 4 ): 13 articles reported results from P‐PBPK models, which are presented in support of dose selection, 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 five articles were on the optimization of dosage in the design of future pediatric clinical studies, 3 , 29 , 43 , 44 , 45 and six articles reported findings from studies on determining dose regimens. 46 , 47 , 48 , 49 , 50 , 51 Fourteen publications were on some special pediatric populations and uncommon diseases with an assessment of renal impairment, 52 , 53 , 54 , 55 , 56 children with obesity, 57 , 58 , 59 , 60 and pediatric patients with severe coronavirus disease 2019 (COVID‐19) disease. 61 , 62 , 63 , 64 , 65 Consistent with this trend, several big research funding/grants for computational pharmaceutics worldwide were launched (Table 1 ).…”

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Zhang

Dun

Chen

et al. 2022

CPT Pharmacom & Syst Pharma

View full text Add to dashboard Cite

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling.We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Zhang

Dun

Chen

et al. 2022

CPT Pharmacom & Syst Pharma

View full text Add to dashboard Cite

show abstract

“…4 mg/l sulbactam further reduces MIC to ≤2/2/4 mg/l for meropenem/polymyxin-B/sulbactam, resulting in susceptible for meropenem and intermediate for polymyxin-B (CLSI, 2020). The reduction in MIC provides sufficient drug exposure for clinical regimens of meropenem, polymyxin-B and sulbactam to achieve ≥90% PTA for their respective pharmacodynamic indices (Martins et al, 2020;Zhu et al, 2022). The metabolomic profiling results revealed that the combination therapy (P + M + S) initially perturbed lipids, LPS and peptidoglycan metabolism therefore impacted the stability of cell membrane and cell wall.…”

Section: Discussionmentioning

confidence: 99%

Metabolomic profiling of polymyxin-B in combination with meropenem and sulbactam against multi-drug resistant Acinetobacter baumannii

et al. 2022

Self Cite

View full text Add to dashboard Cite

Empirical therapies using polymyxins combined with other antibiotics are recommended in the treatment of Acinetobacter baumannii infections. In the present study, the synergistic activities of polymyxin-B, meropenem, and sulbactam as combination therapy were investigated using metabolomic analysis. The metabolome of A. baumannii was investigated after treatment with polymyxin-B alone (2 mg/l), meropenem (2 mg/l) alone, combination of polymyxin-B/meropenem at their clinical breakpoints, and triple-antibiotic combination of polymyxin-B/meropenem and 4 mg/l sulbactam. The triple-antibiotic combination significantly changed the metabolite levels involved in cell outer membrane and cell wall biosynthesis, including fatty acid, glycerophospholipid, lipopolysaccharide, peptidoglycan, and nucleotide within 15 min of administration. In contrast, significant changes in metabolome were observed after 1 h in sample treated with either meropenem or polymyxin-B alone. After 1 h of administration, the double and triple combination therapies significantly disrupted nucleotide and amino acid biosynthesis pathways as well as the central carbon metabolism, including pentose phosphate and glycolysis/gluconeogenesis pathways, and tricarboxylic acid cycle. The addition of sulbactam to polymyxin-B and meropenem combination appeared to be an early disruptor of A. baumannii metabolome, which paves the way for further antibiotic penetration into bacteria cells. Combination antibiotics consisting of sulbactam/meropenem/polymyxin-B can effectively confer susceptibility to A. baumannii harboring OXA-23 and other drug resistant genes. Metabolomic profiling reveals underlying mechanisms of synergistic effects of polymyxin-B combined with meropenem and sulbactam against multi-drug resistant A. baumannii.

show abstract

“…The PTA of polymyxin-B dosing regimens in both plasma and ELF is an indicator of treatment efficacy against the pathogen based on drug exposures in the blood and the lung ( Zhu et al, 2022b ). Even with ≥80% PTA for polymyxin-B exposure in the ELF, f T >MPC in the ELF after polymyxin-B intravenous administration can be limited to around 20%.…”

Section: Discussionmentioning

confidence: 99%

The combination effect of meropenem/sulbactam/polymyxin-B on the pharmacodynamic parameters for mutant selection windows against carbapenem-resistant Acinetobacter baumannii

et al. 2022

View full text Add to dashboard Cite

The objective of this study was to evaluate whether combinations of sulbactam, meropenem, and polymyxin-B could reduce or close the gap of mutant selection window (MSW) of individual antibiotics against Acinetobacter baumannii harboring OXA-23. MICs of three antimicrobials used alone and in combination (meropenem/polymyxin-B or meropenem/polymyxin-B/sulbactam) were obtained in 11 clinical isolates and mutant prevention concentrations were determined in 4 of the 11 isolates. All isolates were resistant to meropenem or polymyxin-B. Combining meropenem and polymyxin-B with or without sulbactam resulted in synergistic bactericidal activities. Pharmacokinetic (PK) simulations of drug concentrations in the blood and epithelial lining fluid coupled with pharmacodynamic (PD) evaluations revealed that the fractions of time over the 24-h in terms of free drug concentration within the MSW (fTMSW) and above the MPC (fT>MPC) were optimized by combination therapy. The resultant clinical regimens of meropenem, polymyxin-B, and sulbactam evaluated in the PK-PD analysis were 2 g q8h, 2.5 mg/kg loading dose followed by 1.5 mg/kg q12h, and 3 g q8h, respectively, in patients with normal renal function. Subsequent corresponding equivalent exposure regimens would depend on the extent of renal failure. The overall results indicate that combination antibiotics consisting of sulbactam/meropenem/polymyxin-B can confer potential efficacy against A. baumannii harboring OXA-23, and reduce the opportunity for bacteria to develop further resistance. This study provides a framework for pharmacodynamic evaluation of drug-resistant mutant suppression in an antimicrobial co-administration setting. The results thereby lay the groundwork for additional studies and future clinical confirmation is warranted.

show abstract

Prediction of Tissue Exposures of Meropenem, Colistin, and Sulbactam in Pediatrics Using Physiologically Based Pharmacokinetic Modeling

Cited by 12 publications

References 79 publications

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Metabolomic profiling of polymyxin-B in combination with meropenem and sulbactam against multi-drug resistant Acinetobacter baumannii

The combination effect of meropenem/sulbactam/polymyxin-B on the pharmacodynamic parameters for mutant selection windows against carbapenem-resistant Acinetobacter baumannii

Contact Info

Product

Resources

About