Charlotte M Thomas1, T Harrison2, JN Jarvis3, KE Stott4, DS Lawrence5, M Mosepele6, G Meinjes7, CE Ndhlovu8, HC Mwandumba9, C Kanyama10, DB Meya11, CK Muzoora12, R Doyle13, JF Standing1, DO Lonsdale14, R Wake15
1University College London, GOS Institute of Child Health, 2Institute of Infection and Immunity, City St George's University London, 3Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Tropical Medicine, London, United Kingdom; Botswana Harvard Health Partnership, Gaborone, Botswana , 4Antimicrobial Pharmacodynamics and Therapeutics Group, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, United Kingdom; Malawi Liverpool Wellcome Clinical Research Programme, Blantyre, Malawi , 5Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Tropical Medicine, London, United Kingdom; Botswana Harvard Health Partnership, Gaborone, Botswana; Clinical Microbiology and Infectious Diseases, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa , 6Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana; Department of Internal Medicine, University of Botswana, Gaborone, Botswana, 7Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa); Institute of Infectious Disease and Molecular Medicine, and Department of Medicine, University of Cape Town, Cape Town, South Africa, 8Department of Medicine, University of Zimbabwe College of Health Sciences, Parirenyatwa Hospital, Harare, Zimbabwe, 9Malawi Liverpool Wellcome Clinical Research Programme, Blantyre, Malawi, 10University of North Carolina Project-Malawi, Lilongwe, Malawi, 11Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Central Region, Uganda, 12Department of Internal Medicine Faculty of Medicine Mbarara, University of Science and Technology Mbarara, Mbarara, Uganda, 13Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom, 14City St. George's, University of London, London, United Kingdom; St. George's University Hospitals NHS Foundation Trust, London, United Kingdom, 15Institute for Infection and Immunity, City St George's University of London, London, United Kingdom
Introduction & Objectives: Flucytosine (5-FC) is commonly used in combination therapy for the treatment of cryptococcal meningitis. Historically, its use has been limited due to accessibility issues. However, as flucytosine becomes increasingly available globally, there is new potential for its use in the treatment of other fungal infections. To optimise dosing and inform future trials, a greater understanding of flucytosine’s pharmacokinetics (PK) and pharmacodynamics (PD) is required. This study aimed to characterise the exposure of flucytosine in the plasma and cerebrospinal fluid (CSF) in patients with HIV-associated cryptococcal meningitis under combination antifungal treatment through the development of a population PK model. Methods: Analysis was conducted with data from the phase 3 AMBITION-CM trial (Jarvis et al. 2022), comprising 383 HIV-positive adults with cryptococcal meningitis from five African countries (Botswana, Malawi, South Africa, Uganda, Zimbabwe). A non-linear mixed effect modelling approach was undertaken using nlmixr2 (version 2.1.1.9) in R (version 4.3.1). Allometirc scalling was included as a prior. Creatinine, creatinine clearance, and neutrophil count were tested as model covariates. Serum concentrations below the limit of quantification were handled using the M3 method. Results: Pharmacokinetic data were best described by one plasma and one CSF compartment. Typical values for the absorption rate constant, clearance and volume of distribution were 0.727, 7.9 L/h, and 133 L. The intercompartmental clearance for CSF was 0.344 L/h, and the volume of distribution for CSF was 5.13 L. A proportional error model was employed for the estimation of plasma concentration, and a proportional-additive error model was employed for the estimation of CSF concentration. The model benefited from inter-individual variability on all parameters. No covariates were retained in the model. Model diagnostics demonstrated a good model fit. Conclusions: We reliably described the PK of 5-FC and its movement into the CSF. Future work will include utilising CFU counts to assess the impact of drug exposure on fungal clearance, to ultimately provide clinically relevant insights for current and future dosing strategies. To our knowledge, this is the largest PK dataset modelled for this drug.
Jarvis, J. N., D. S. Lawrence, D. B. Meya, E. Kagimu, J. Kasibante, E. Mpoza, et al. (Mar. 2022). “Single-dose liposomal amphotericin B treatment for cryptococcal meningitis”. en. In: N. Engl. J. Med. 386.12, pp. 1109–1120.
Reference: PAGE 33 (2025) Abstr 11700 [www.page-meeting.org/?abstract=11700]
Poster: Drug/Disease Modelling - Infection