Can PBPK Modelling Solve the Postpartum Sepsis Pharmacokinetics Puzzle?

Background

Maternal sepsis and related infections (MSRIs) remain a global health challenge, causing nearly 10% of maternal mortalities. It disproportionately affects younger women in the postpartum phase and patients of low-socioeconomic status in Sub-Saharan Africa. In Uganda, the latest incidence is 43/10,000 live births (1,2). This high burden stems from health system constraints linked to the three-delays model. Timely antibiotic administration is crucial to prevent progression to sepsis, septic shock, and complications. However, physiological changes during and after pregnancy significantly alter antibiotic pharmacokinetics, and sepsis-induced organ dysfunction further complicates these changes. Coupled with ethical challenges, these factors create a complex clinical scenario requiring innovative approaches to understand pharmacokinetic exposure

Methods

We propose employing PBPK modeling to integrate postpartum physiological and sepsis-related parameters with drug characteristics to predict antibiotic exposure. This framework will utilize virtual populations representing postpartum sepsis, incorporating variability in physiological and sepsis-driven parameters. Predicting drug disposition will allow performance of probability of target attainment (PTA) analysis against relevant pathogens, optimizing dosing for PK/PD targets. Building on previous frameworks integrating pregnancy and postpartum physiology (3,4), our approach will focus on PBPK models using virtual populations to optimize antibiotic dosing in postpartum sepsis through PTA analysis.

Supporting Evidence and Rationale

PBPK modeling improves antimicrobial PK prediction, supporting its application here. PTA analysis translates PK predictions into clinically evaluable dosing recommendations and is especially valuable in resource-limited settings, where predictive modeling offers a cost-effective solution. Clinicians could leverage this technology and PTA outcomes to select safe, effective antibiotic doses by simulating drug exposure, enabling personalized strategies.

Proposed Impact & Future Work

This PBPK framework aims to optimize antibiotic therapy in postpartum sepsis, providing critical insights in high-burden settings. Future work will expand virtual populations to predict co-administered drug exposure and quantify infant drug exposure via breast milk.

Conclusion

Provides first evidence base for antibiotic dosing in postpartum sepsis. Captures dual dynamics: postpartum physiology + sepsis progression. Supports safe, effective, and rational antibiotic use. Ongoing work: observational PK study under the MILKCENTRE to generate empirical postpartum PK data for model refinement/validation

References

1. Tumusiime L, Namulondo E, Kwesiga B, Migisha R, Kadoberaᶾ D, Mwenyango I, et al. Trends and distribution of maternal sepsis, Uganda,. 2024;9(3).
2. Cao J, Xue D, Gao D, Zhang G. Maternal sepsis and other maternal infections: Global Burden from 1990 to 2021. BMC Pregnancy Childbirth. 2025 May 26;25(1):612.
3. Dallmann A, Himstedt A, Solodenko J, Ince I, Hempel G, Eissing T. Integration of physiological changes during the postpartum period into a PBPK framework and prediction of amoxicillin disposition before and shortly after delivery. J Pharmacokinet Pharmacodyn. 2020 Aug;47(4):341–59.
4. Abduljalil K, Ning J, Pansari A, Pan X, Jamei M. Prediction of Maternal and Fetoplacental Concentrations of Cefazolin, Cefuroxime, and Amoxicillin during Pregnancy Using Bottom-Up Physiologically Based Pharmacokinetic Models. Drug Metab Dispos. 2022 Apr;50(4):386–400.