Neopterin dynamics in pediatric patients after miltefosine treatment of visceral leishmaniasis
Semra Palic (1), Fabiana Alves (2), Alwin D.R. Huitema(1,3), Jos H. Beijnen(1), Thomas P.C. Dorlo(1)
1. Department of Pharmacy and Pharmacology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands 2. Drugs for Neglected Diseases initiative, Geneva, Switzerland 3. Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, The Netherlands
Introduction/Objectives
Visceral leishmaniasis (VL) is the most severe form of the neglected tropical disease leishmaniasis affecting internal organs such as spleen, liver and the bone marrow. If left untreated, VL is lethal within months. In East Africa, the pediatric population appears particularly vulnerable for this infection (1). Leishmania parasites are known to invade macrophages of the host, persuading the rise in anti-inflammatory cytokines to foster disease progression. Activated macrophages produce neopterin, a pteridine that has served as a marker of immune activation in various pathologies for decades (2). Recently, neopterin was also shown to be increased in patients suffering from VL, where it could potentially function as predictor of relapse (3). The main objective of the present study was to develop an integrated pharmacokinetic-pharmacodynamic (PK-PD) model to characterize the neopterin response to miltefosine treatment of pediatric VL.
Methods
Pediatric East African VL patients from two trials investigating miltefosine monotherapy were included in the current analysis. Twenty one patients (age 7-11) were treated with the conventional linear weight based miltefosine regimen (median 2.4 mg/kg/day) (4), while thirty patients (age 4-12) were treated with an allometric weight based dosing regimen (median 3.2 mg/kg/day) (5). Individual PK parameters from a previously developed population PK model of miltefosine (6) were used to link with neopterin PD. In total 562 neopterin plasma concentrations (analyzed using an ELISA assay, Demeditec Diagnostics GmbH) were available. All samples were measured in duplicates, and average values were used for this population analysis. Data were analyzed using the first-order conditional estimation with interaction (FOCE+I) estimation method in NONMEM (version 7.3.0, Globomax, USA) using Pirana as interface (version 2.9.6).
Results
Neopterin pharmacodynamics were characterized using a turnover model. Given that neopterin is an endogenous marker, also present in plasma of healthy individuals, two modes of neopterin production were included in our model. Normal neopterin production, and VL-specific production were estimated in combination with neopterin elimination. VL specific production was modelled to be influence by miltefosine exposure (cumulative AUC) by a second-order inactivation rate constant. The turnover time, which corresponds to the mean residence time of neopterin, was estimated at 29 days (relative standard error (RSE) 14%). The typical neopterin increase at baseline due to the disease was 77.4 nmol/L, but was variable among patients (between subject variability (BSV) 35%, RSE 19%), while the healthy neopterin steady-state to which neopterin returned after treatment in this patient population was estimated at 19.4 nmol/L (RSE 13%). However, literature reports a healthy standard reference for neopterin in various other patient populations at 10 nmol/L (7), but none of the patients in this cohort recovered to endogenous values. Moreover, during follow-up neopterin plasma levels increased again in a subset of patients. To identify these individuals, a mixture model was used, which indicated a subpopulation (30%, RSE 17%) for whom a zero-order regrowth rate during follow-up could be estimated at 0.0157 disease unit/day (RSE 12%).
Conclusion
We developed an integrated PK-PD model using a latent disease variable and an underlying endogenous turnover model to elucidate the relationship of miltefosine pharmacokinetics with neopterin dynamics and VL-driven change in neopterin production. Future analyses will focus on identifying predictors for the neopterin increases during follow-up. Finally, this model will further be used to explore neopterin as a potential biomarker of disease relapse in patients who suffered from VL.
References
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