Jean Lavigne (1), Mary Lor (1), and Silvia Pace (2)
(1) Celerion, Montreal, Canada, (2) Sigma-Tau, Rome, Italy
Objectives: Develop a population pharmacokinetic and pharmacodynamic (PK/PD) model for the treatment and smear count of Plasmodium falciparum by pooling data from 5 studies (PK part), 2 patients studies (PD part), and applying them to predict the smear count in pediatric patients (6-12 months) infected with P. falciparum malaria after administration of a new dispersible formulation.
Methods: PK parameters for both drugs were developed[1,2] and the Bayesian estimates were fixed. The patients with Bayesian estimated PK parameters from both medications were included in the analysis for a total of 50 smear count profiles, 563 samples (163 were greater than zero). The MLEM algorithm in ADAPT5[3] was used to estimate the population PD parameters. The natural logarithm of the smear count plus two was used for PD modeling. The initial conditions were fixed to the measure smear level before administration of the medication. The covariates age, body weight (WGT), body surface area, sex, race (RACE), fasted/fed, and crushed/not crushed were explored. The Bayesian Information Criteria (BIC) was used for model discrimination and covariate inclusion/exclusion.
Results: A one-compartment model with a grow and kill rate based on both medications best fitted the smear count data. An antagonistic effect was assumed between the two medications[4], i.e., less than additive, the worst case scenario was achieved by taking the kill rate to be the maximum effect for the two medications. DHA and PQ effects were modeled with an Emax and a sigmoidal Emax model, respectively. An onset of effect parameter and the inclusion of RACE on DHAmax both improved the BIC. It was suspected that RACE was more a marker of different parasite populations since one study was conducted in Asia with Asian adult patients and the second study was conducted in Africa with Black pediatric patients. The model estimated a 48-hour parasite growth rate in blood to be 18.3, which was within the range reported in the literature[5]. For the simulations, WGT was simulated according to the WHO training[6]. One thousand Black infants were simulated receiving 80/10, 160/20, or 320/40 mg PQ/DHA depending of their WGT once a day for 3 consecutive days. The simulated results suggested a geometric mean parasite clearance time of 22.5 hours (range between 10 to 65 hours).
Conclusions: The model described well the parasite smear level count and the geometric mean parasite clearance time of 22.5 hours.
References:
[1] Lavigne J., Lor M., Pace S. Modeling and Simulation of Piperaquine (PQ) after Administration of Eurartesim® (PQ Tetraphosphate/Dihydroartemisinin). Poster presented at ACoP2015 (http://celerion.com/wordpress/wp-content/uploads/2015/10/Celerion_2015-ACOP_Modeling-and-Simulation-of-Piperaquine-PQ-after-Administration-of-Eurartesim.pdf).
[2] Lavigne J., Lor M., Pace S. Modeling and Simulation of Dihydroartemisinin (DHA) after Administration of Eurartesim® (Piperaquine Tetraphosphate/DHA). Poster presented at PAGE2014 (http://www.page-meeting.org/pdf_assets/5485-14_05%20PAGE%20pst%20D5.pdf).
[3] D’Argenio, D.Z., A. Schumitzky and X. Wang. ADAPT 5 User’s Guide: Pharmacokinetic/Pharmacodynamic Systems Analysis Software. Biomedical Simulations Resource, Los Angeles, 2009.
[4] Anirudh Gautam, Tausif Ahmed, Vijay Batra and Jyoti Paliwal Pharmacokinetics and Pharmacodynamics of Endoperoxide Antimalarials, Current Drug Metabolism, 2009, 10, 289-306
[5] Philip Bejon, Laura Andrews, Rikke F Andersen, Suzanna Dunachie, Daniel Webster, Michael Walther, Sarah C. Gilbert, Tim Peto, and Adrian V. S. Hill. Calculation of Liver-to-Blood Inocula, Parasite Growth Rates, and Preerythrocytic Vaccine Efficacy, from Serial Quantitative Polymerase Chain Reaction Studies of Volunteers Challenged with Malaria Sporozoites. The Journal of Infectious Diseases, 2005; 191:619-26. (https://jid.oxfordjournals.org/content/191/4/619.full)
[6] Training Course on Child Growth Assessment – WHO – Module C: Interpreting Growth Indicators. (http://www.who.int/childgrowth/training/module_c_interpreting_indicators.pdf)
Reference: PAGE 25 (2016) Abstr 5930 [www.page-meeting.org/?abstract=5930]
Poster: Drug/Disease modeling - Paediatrics