Model-based individual managing of thrombocytopenia during multi-cyclic chemotherapy
Yuri Kheifetz; Prof. Dr. Markus Scholz; Prof. Dr. Markus Loeffler
IMISE (Institut für Medizinische Informatik, Statistik und Epidemiologie), Leipzig University
Objectives: Thrombocytopenia is a major side-effect of cytotoxic cancer therapies. The development of individual therapy adaptations is a non-trivial task since thrombocytopenic risk depends on many therapy-associated and individual factors. To solve this task, we developed an individualized bio-mathematical model of human thrombopoiesis under chemotherapy and implemented it in a software-tool usable for therapy management.
Methods: We performed bio-mechanistic modelling of the dynamics of bone marrow thrombopoiesis and platelets by ordinary differential equations. Amplifications, death rates and transition times of the system are regulated by three types of biologically motivated feedback loops. The most important one is mediated by thrombopoietin for which injections can be considered by an attached pharmacokinetic and –dynamic model. Effects of cytotoxic drugs are modelled by a transient depletion of proliferating cells and a long-term depletion of osteoblasts reducing the supporting capacity of the bone marrow.
To parametrize the model, we used population data from the literature and close-meshed individual data of 138 non-Hodgkin’s lymphoma patients treated with CHOP-like chemotherapies (on average 43 measurements per patient). The over-fitting issue of individual parameter estimates was successfully dealt with a virtual participation of each patient in 3 population-based experiments measuring 12 biological features.
Results: Our model qualitatively and quantitatively explains major mechanisms of thrombopoiesis such as: the role of osteoblasts in explaining long-term toxic effects, multiple regulatory functions of TPO, dynamics of megakaryocyte ploidies and non-exponential platelet degradation.
Almost all of the considered 138 individual time series data are fitted with high precision assuming only 11 parameters to be heterogeneous among patients.
We transferred the model into a user-friendly software tool which allows individual prediction of platelet-dynamics for CHOP-like chemotherapies of non-Hodgkin’s lymphoma and the effect of therapy adaptations.
Conclusions: We successfully established a comprehensive mechanistic model of human thrombopoiesis under chemotherapy. It allows individual predictions of degrees of thrombopenia for the first time with superior accuracy compared to statistical or semi-mechanistic competitors. Moreover, it can be used to make clinically relevant predictions regarding individual therapy adaptations.
