2013 - Glasgow - Scotland

PAGE 2013: Drug/Disease modelling
Martin Bergstrand

Modeling of the concentration-effect relationship for piperaquine in preventive treatment of malaria

Martin Bergstrand (1), FranÁois Nosten (2,3,4), Khin Maung Lwin (4), Mats O. Karlsson (1), Nicholas White (2,3), Joel Tarning (2,3)

(1) Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. (2) Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand. (3) Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. (4) Shoklo Malaria Research Unit (SMRU), Mae Sod, Thailand.

Objectives: A randomized, placebo controlled trial conducted on the Northwest border of Thailand compared monthly to bi-monthly treatment with a standard 3-day treatment regimen of dihydroartemisinin-piperaquine [1]. A total of 1000 healthy adult male subjects were followed up weekly for 9 months of treatment. This project aimed to characterize the concentration-effect relationship for the malaria preventive effect of piperaquine and utilize it for simulations of dosing in vulnerable populations and in areas with piperaquine resistance.

Methods: Seasonal variations in baseline risk of malaria infection were investigated by applying one or two surge functions to a constant baseline hazard for placebo treated subjects. A mixture model was used to differentiate between a high- and low-risk subpopulation [2]. Monthly observations of piperaquine plasma concentrations were modeled using a frequentist prior [3] based on a published PK model [4]. A joint PKPD model was subsequently applied to explore the effect of piperaquine plasma concentration on malaria infection hazard. The model was sequentially extended to account for the effect of dihydroartemisinin and the delay between the malaria diagnosis and the crucial point of prevention failure.

Results: One significant seasonal peak in malaria transmission was identified from May throughout June during when the hazard was increased with 217% (RSE 27%). The concentration-effect relationship was best characterized with a sigmoidal Emax relationship where concentrations of 7 ng/mL (RSE 13%) and 20 ng/ml were found to reduce the hazard of acquiring a malaria infection by 50% (i.e. IC50) and 95% (IC95), respectively.

Simulations of monthly dosing, based on the final model and literature information about PK, suggested that the one year incidence of malaria infections could be reduced by 70% with a recently suggested dosing regimen compared to the manufacture recommendations for children with a body weight of 8-12 kg [5]. Pregnant women were predicted to have a 12.5% higher incidence compared to non-pregnant.

Conclusions: For the first time a concentration-effect relationship for the malaria preventive effect of piperaquine was established. The established model has been useful in translating observed results from a healthy male population to that expected in other populations.

[1] K. M. Lwin et al., Randomized, double-blind, placebo-controlled trial of monthly versus bimonthly dihydroartemisinin-piperaquine chemoprevention in adults at high risk of malaria. Antimicrobial Agents and Chemotherapy 56, 1571 (2012).
[2] Farewell, V.T., The use of mixture models for the analysis of survival data with long-term survivors. Biometrics, 1982. 38(4): p. 1041-1046.
[3] Gisleskog, P.O., M.O. Karlsson, and S.L. Beal, Use of prior information to stabilize a population data analysis. J Pharmacokinet Pharmacodyn, 2002. 29(5-6): p. 473-505.
[4] Tarning, J., et al., Population pharmacokinetics of dihydroartemisinin and piperaquine in pregnant and nonpregnant women with uncomplicated malaria. Antimicrobial Agents and Chemotherapy, 2012. 56(4): p. 1997-2007.
[5] Tarning, J., et al., Population pharmacokinetics and pharmacodynamics of piperaquine in children with uncomplicated falciparum malaria. Clinical Pharmacology and Therapeutics, 2012. 91(3): p. 497-505.


Reference: PAGE 22 (2013) Abstr 2933 [www.page-meeting.org/?abstract=2933]
Oral: Drug/Disease modelling
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