Abstract
BackgroundThrombocytopenia is a major side-effect of cytotoxic cancer therapies. The aim of precision medicine is to develop therapy modifications accounting for the individual’s risk.Methodology/Principle findingsTo solve this task, we develop an individualized bio-mechanistic model of the dynamics of bone marrow thrombopoiesis, circulating platelets and therapy effects thereon. Comprehensive biological knowledge regarding cell differentiation, amplification, apoptosis rates, transition times and corresponding regulations are translated into ordinary differential equations. A model of osteoblast/osteoclast interactions was incorporated to mechanistically describe bone marrow support of quiescent cell stages. Thrombopoietin (TPO) as a major regulator is explicitly modelled including pharmacokinetics and–dynamics of TPO injections. Effects of cytotoxic drugs are modelled by transient depletions of proliferating cells.To calibrate the model, we used population data from the literature and close-meshed individual data of N = 135 high-grade non-Hodgkin’s lymphoma patients treated with CHOP-like chemotherapies. To limit the number of free parameters, several parsimony assumptions were derived from biological data and tested via Likelihood methods. Heterogeneity of patients was explained by a few model parameters. The over-fitting issue of individual parameter estimation was successfully dealt with a virtual participation of each patient in population-based experiments.The model qualitatively and quantitatively explains a number of biological observations such as the role of osteoblasts in explaining long-term toxic effects, megakaryocyte-mediated feedback on stem cells, bi-phasic stimulation of thrombopoiesis by TPO, dynamics of megakaryocyte ploidies and non-exponential platelet degradation. Almost all individual time series could be described with high precision. We demonstrated how the model can be used to provide predictions regarding individual therapy adaptations.ConclusionsWe propose a mechanistic thrombopoiesis model of unprecedented comprehensiveness in both, biological mechanisms considered and experimental data sets explained. Our innovative method of parameter estimation allows robust determinations of individual parameter settings facilitating the development of individual treatment adaptations during chemotherapy.
Highlights
Reduced platelet counts, called thrombocytopenia, is a major dose-limiting side effect of many dose-intense cancer chemotherapies [1,2]
We propose a mechanistic thrombopoiesis model of unprecedented comprehensiveness in both, biological mechanisms considered and experimental data sets explained
We present our model assumptions and equations for the production and degradation of endogenous TPO, pharmacokinetics of pegylated TPO applications and corresponding effects on bone marrow thrombopoiesis: 1. In the previous model [4], only circulating platelets and MKC are supposed to consume TPO
Summary
Reduced platelet counts, called thrombocytopenia, is a major dose-limiting side effect of many dose-intense cancer chemotherapies [1,2]. Understanding thrombopoiesis during cytotoxic chemotherapy is crucial for its amelioration by chemotherapy dose adjustments, therapy postponement, platelet transfusion or growth factor applications such as thrombopoietin (TPO). This is a non-trivial task since thrombocytopenia risk depends on several therapybased and individual factors such as dosing and timing of the cytotoxic drugs, application of platelet concentrates, age, sex and individual chemosensitivity [1,3]. A major challenge of precision medicine is to take all of these factors into account for optimal risk management. Due to the large number of factors influencing therapy outcome and side-effects, we hypothesize that comprehensive models are required to support the concept of precision medicine.
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