Fluid‐Retention Side‐Effects of the Chemotherapy‐Supportive Treatment Interleukin‐11: Mathematical Modelling of Putative Underlying Mechanisms

Abstract

Interleukin-11 (IL-11) is a pleiotropic thrombopoietic cytokine and immune modulator, clinically approved for alleviation of chemotherapy-induced thrombocytopenia in non-myeloid malignancies. IL-11 therapy exerts fluid accumulation-associated adverse effects, complicating its administration and limiting its use. Implementation of standard biomathematical techniques to assess these effects is not possible, due to incomplete knowledge of the underlying mechanisms. This study investigates IL-11-induced blood volume expansion (BVE) by a new mathematical modelling methodology. Alternative models for BVE following IL-11 therapy were constructed, calibrated with clinical information and simulated in a number of treatment scenarios. The models demonstrated high compliance and were equally capable of reliably predicting BVE in a wide range of treatments, provided sufficient data. Model simulations indicate that frequent and low dose IL-11 regimens are favored for ensuring minimal fluid retention, upon the current IL-11 therapy.

Mathematical Modeling as a New Approach for Improving the Efficacy/Toxicity Profile of Drugs: The Thrombocytopenia Case Study

“…The study therefore consisted of two essential steps: experimentally-based calibration and parallel assessment of model simulationderived BVE behavior. These procedures are described hereafter [36].…”

“…However, the definitive mechanism underlying IL-11-mediated water accumulation is yet to be discovered, and the incomplete data [23,35], restrict the possibility to produce a concrete and reliable model for this problem. Instead, a novel biomathematical approach was developed so that not one, but several mathematical models, each representing an alternative mechanism for BVE following IL-11 therapy, were devised and evaluated [36]. The underlying assumption here was that by concurrently simulating multiple models, which formally describe alternative mechanisms, but all producing the same fluidretentive behavior, it is possible to faithfully depict this effect despite the obscurity of the actual mechanism and related data.…”

“…Model simulations under the experimental schedule (treatment 'exp') and other regimens of various durations, doses, and inter-dosing intervals (treatments 1-11), following calibration with clinical measurements, are compared using the difference index (data adapted from [36]). …”

“…Blood volume (liters) measured during one week of IL-11 therapy (7 daily doses of 25 µg/kg), was taken from a previous study in healthy humans. Three models, calibrated with data from either the therapeutic days (upper panel), or both the therapeutic and posttherapeutic windows (lower panel) were simulated under the above experimental treatment schedule (data adapted from [36]). …”

Preface

“…The analysis is developed at the macroscopic scale after a detailed analysis of the existing literature on models proposed at different scales as discussed in the monograph edited by Preziosi [22]. An interesting example of the interaction between mathematics and medicine is the paper by Kheiffetz et al [17], devoted to super-macroscopic modelling of fluid retention side effects on chemotherapy supportive treatment. The mathematical modelling is carefully correlated to data availability and so offers a precise link with the medical sciences.…”