Determining an Alternate Antimicrobial Regimen for the Empiric Treatment of Neonatal Sepsis in Low- and Middle-Income Countries in the Context of Rising Antimicrobial Resistance

Darlow, Christopher ORCID: 0000-0002-5400-3413 (2022) Determining an Alternate Antimicrobial Regimen for the Empiric Treatment of Neonatal Sepsis in Low- and Middle-Income Countries in the Context of Rising Antimicrobial Resistance. PhD thesis, University of Liverpool.

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Abstract

Background: Neonatal sepsis causes an estimated 430,000 – 680,000 infant deaths globally each year, with the burden predominantly borne by low- and middle-income countries (LMICs). The World Health Organisation (WHO) currently recommends of a combination of a narrow β-lactam and gentamicin for the empiric treatment of neonatal sepsis. However, emerging epidemiology suggests widespread resistance to these antibiotics in bacteria causing neonatal sepsis in LMIC settings. Alternative regimens that retain efficacy, are safe in neonates and are affordable in LMIC settings are sorely needed. Objectives: 1) Identification and selection of candidate antibiotic combinations for the empiric treatment of neonatal sepsis by metrics of spectrum of activity, pharmacodynamic interaction, and predicted efficacy of neonatal-like drug exposures to different bacteria. 2) Prediction of the neonatal drug exposures of the selected drugs using in silico techniques. Methods: Antibiotics were selected according to criteria for suitability of use in LMIC settings, with the predicted spectrum of activity of potential antibiotic combinations assessed with determination of minimum inhibitory concentration (MIC) for a representative panel of bacteria. High performing candidate combinations were further assessed in checkerboard assays and hollow-fiber infection model (HFIM) experiments to assess their pharmacodynamic interactions and pharmacodynamic performance. A neonatal population pharmacokinetic (popPK) model was constructed for the antibiotic flomoxef using Pmetrics, and neonatal physiology-based pharmacokinetic (PBPK) models of amikacin, fosfomycin and flomoxef were built and validated using Simcyp. Both were used to predict and explore neonatal drug exposures. Results: Eight candidate combinations from five off-patent antibiotics were identified. The three pairwise combinations of flomoxef, amikacin and fosfomycin had the superior predicted spectrum of activity. All three combinations demonstrated synergy in bactericidal effect and prevention of emergence of fosfomycin and/or amikacin resistance in checkerboard and HFIM experiments. When assessed in HFIM experiments with clinically relevant neonatal drug exposures, all provided additional pharmacodynamic effect compared to the constituent agents as monotherapy. A high performing neonatal popPK model was successfully built for flomoxef, with neonatal drug exposures and probability of target attainment (PTA) predicted for different regimens in different age groups. Successful PBPK models were built and validated for fosfomycin and amikacin, with prediction of the neonatal drug exposures with different regimens in different age groups. A valid flomoxef PBPK model was not built due to identified knowledge gaps in flomoxef pharmacology. Conclusion: This thesis has identified three alternative regimens for the potential empiric treatment of neonatal sepsis in LMIC settings: fosfomycin/amikacin, flomoxef/fosfomycin and flomoxef/amikacin. All are efficacious against clinically relevant resistance phenotypes, safe for use in neonates, and are off-patent (and therefore potentially affordable in LMICs). All are synergistic, with benefits of use of combination therapy demonstrated over monotherapy. As a result, all three combinations are being assessed further in an upcoming neonatal sepsis clinical trial. Supplementing this primary conclusion, the expected neonatal drug exposures of each agent were predicted with popPK and PBPK models, informing eventual regimen selection for each combination.

Item Type:	Thesis (PhD)
Divisions:	Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User:	Symplectic Admin
Date Deposited:	16 Dec 2022 10:18
Last Modified:	18 Jan 2023 21:00
DOI:	10.17638/03156381
Supervisors:	Hope, William Peck, Richard ORCID: 0000-0003-1018-9655
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3156381