Population Pharmacokinetics of Sulfadoxine and Pyrimethamine: A pooled analysis to Inform Optimal Dosing in African Children with Uncomplicated Malaria.
Miné de Kock (1,4), Joel Tarning (2,3,4), Lesley Workman (1,4), Elizabeth N Allen (1), Mamadou M Tekete (5), Abdoulaye A. Djimde (5), David J Bell (6), Steve A Ward (7), Karen I Barnes (1,4), Paolo Denti (1,4)
(1) Division of Clinical Pharmacology, Department of Medicine, University of Cape Town, Cape Town, South Africa. (2) Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. (3) Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK. (4) World Wide Antimalarial Resistance Network (WWARN), Oxford, United Kingdom. (5) Malaria Research and Training Center, Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Sciences, Technique and Technology of Bamako, Bamako, Mali (6) Infectious Diseases Unit, Queen Elizabeth University Hospital, Glasgow, UK. (7) Molecular and Biochemical Parasitology Group, Liverpool School of Tropical Medicine, Liverpool, UK.
Objectives: To analyse pooled data from four previously published trials on the pharmacokinetics of sulfadoxine and pyrimethamine in children and adult patients, using nonlinear mixed-effects modelling and to evaluate the current dosing regimen and propose an optimised dosing regimen in children under the age of five.
Methods:
Pharmacokinetic (PK) data was pooled from 4 different studies (1,2,3,4) from the African countries of Mozambique, South Africa, Mali, and Malawi. The data from studies in Mali and Malawi were only from children while the data from studies in Mozambique and South Africa included both children and adults. Seven to ten samples were collect for each patient, with samples collected at pre-dose and day 1, 3 ,7 ,14, 21, and 28 in all patients. Nonlinear mixed-effects modelling was implemented in the software Monolix Suite 2016R1 (Lixoft, France) to analyse the PK data, and parameters were estimated using the Stochastic Approximation Expectation Maximization (SAEM) algorithm. The effect of weight - using allometric scaling (5), age - using maturation (5), weight for age z-score, study site, sex, baseline haemoglobin, mg/kg dose, concomitant medications, baseline parasitemia, and sample blood matrix were tested as predefined covariates. The -2 x log-likelihood value (-2LL), goodness of fit plots, visual predictive checks (n=1000), residual error plots, and Wald’s test guided the model development.
Results: Differences in PK properties between adults and children were described with body size, age and weight-for-age z-scores. Underweight-for-age children were found to have 13.3% and 26.7% lower bioavailability of sulfadoxine and pyrimethamine respectively, for each unit of z-score below -2. Under WHO dosing recommendations, with simulation based predictions, patients who weigh 8-9 (-12%), 19-24 (-12%), 46-49 (-7%) and 74-79(-4%) kg have median sulfadoxine Cday7 lower than the chosen efficacy target: 75% of the median Cday7 of a typical patient (50kg), and the same for pyrimethamine in the weight-bands 8-9 (-22%), 14-24 (-18%) and 42-49 (-6%) kg.
Conclusion: Suboptimal sulfadoxine/pyrimethamine exposures in some weight bands given the current WHO recommended dose regimens were confirmed in this pooled PK analysis. We found that children who were underweight for age had decreased bioavailability with a greater effect on pyrimethamine. PK modelling and simulation was used to derive an optimised antimalarial dosing regimen.
References:
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