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Predictive Performance of Pharmacokinetic Model-Based Virtual Trials of Vancomycin in Neonates: Mathematics Matches Clinical Observation

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Abstract

Background and Objective

Vancomycin is frequently used to treat Gram-positive bacterial infections in neonates. However, there is still no consensus on the optimal initial dosing regimen. This study aimed to assess the performance of pharmacokinetic model-based virtual trials to predict the dose–exposure relationship of vancomycin in neonates.

Methods

The PubMed database was searched for clinical trials of vancomycin in neonates that reported the percentage of target attainment. Monte Carlo simulations were performed using nonlinear mixed-effect modeling to predict the dose–exposure relationship, and the differences in outcomes between virtual trials and real-world data in clinical studies were calculated.

Results

A total of 11 studies with 14 dosing groups were identified from the literature to evaluate dose–exposure relationships. For the ten dosing groups where the surrogate marker for exposure was the trough concentration, the mean ± standard deviation (SD) for the target attainment between original studies and virtual trials was 3.0 ± 7.3%. Deviations between − 10 and 10% accounted for 80% of the included dosing groups. For the other four dosing groups where the surrogate marker for exposure was concentration during continuous infusion, all deviations were between − 10 and 10%, and the mean ± SD value was 2.9 ± 4.5%.

Conclusion

The pharmacokinetic model-based virtual trials of vancomycin exhibited good predictive performance for dose–exposure relationships in neonates. These results might be used to assist the optimization of dosing regimens in neonatal practice, avoiding the need for trial and error.

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Acknowledgements

The authors thank all the patients who participated in this study and all the participants and research staff in our hospital.

Author information

Authors and Affiliations

  1. Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, No.44, Wenhua West Road, Jinan, 250012, Shandong Province, China

    Bu-Fan Yao, Yue-E Wu, Bo-Hao Tang, Guo-Xiang Hao & Wei Zhao

  2. NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, Qilu Hospital of Shandong University, Shandong University, Jinan, China

    Wei Zhao

  3. Department of Pediatric Pharmacology and Pharmacogenetics, Hôpital Robert Debré, APHP, Paris, France

    Evelyne Jacqz-Aigrain

  4. Clinical Investigation Center CIC1426, INSERM, Paris, France

    Evelyne Jacqz-Aigrain

  5. Division of Clinical Pharmacology, Children’s National Medical Center, Washington, DC, USA

    John van den Anker

  6. Departments of Pediatrics, Pharmacology and Physiology, Genomics and Precision Medicine, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA

    John van den Anker

  7. Department of Paediatric Pharmacology and Pharmacometrics, University Children’s Hospital Basel, University of Basel, Basel, Switzerland

    John van den Anker

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  1. Bu-Fan Yao
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Corresponding author

Correspondence to Wei Zhao.

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Funding

This work was supported by the National Natural Science Foundation of China (grant number 82173897); Young Taishan Scholars Program of Shandong Province; and Distinguished Young and Middle-aged Scholar of Shandong University.

Conflict of Interest

Bu-Fan Yao, Yue-E Wu, Bo-Hao Tang, Guo-Xiang Hao, Evelyne Jacqz-Aigrain, John van den Anker and Wei Zhao have no conflicts of interest relevant to this article.

Availability of Data and Material

Research data will not be shared.

Code Availability

Research code will not be shared.

Consent to participate

All participants received written informed consent.

Consent for publication

Written informed consent for publication was obtained from all participants.

Author Contributions

Bu-Fan Yao contributed to the interpretation of the data for the work, the literature search, the PPK modeling analysis, drafting of the initial manuscript, and revising of the subsequent drafts. Yue-E Wu, Bo-Hao Tang, and Guo-Xiang Hao designed the study and reviewed the data. Evelyne Jacqz-Aigrain and John van den Anker interpreted the data for the work, provided advice, and critically reviewed and revised the manuscript. Wei Zhao contributed to the conception and design of the work, supervised the data, and critically reviewed and revised the manuscript. All authors performed the study, participated in the drafting of the manuscript, and approved the final version of the manuscript for submission.

Ethics Approval

All the data were obtained from our previous studies. These studies were approved by the institutional ethics committee.

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Yao, BF., Wu, YE., Tang, BH. et al. Predictive Performance of Pharmacokinetic Model-Based Virtual Trials of Vancomycin in Neonates: Mathematics Matches Clinical Observation. Clin Pharmacokinet 61, 1027–1038 (2022). https://doi.org/10.1007/s40262-022-01128-z

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