Project: Mathematical modeling of TKI effects and immune response to predict patient-specific treatment dynamics in CML
| Acronym | prediCt (Reference Number: JTC2_8) |
| Duration | 01/07/2018 - 31/12/2021 |
| Project Topic | Chronic myeloid leukemia (CML) is a malignant, lethal disease of the hematopoietic system, caused by a chromosomal (9;22)-translocation.The current standard treatment by tyrosine kinase inhibitors (TKI) offers an efficient, targeted therapeutic option. However, while continuousTKI treatment allows to control the disease in the majority of patients, it is still unclear whether a complete cure can be achieved. Althoughthere are multiple ongoing trials investigating the suitability of TKI cessation, lifelong treatment, with its obvious disadvantages such asdrug-induced side effects and high costs, is still the default.Hence, a major aim in CML research is to achieve an ultimate cure or at least to identify patients for which TKI cessation is a safe option andto predict an optimal time point for stopping. Due to patient heterogeneity and a lack of biomarkers, a reliable prediction of individualizedrelapse risk and of optimal TKI stopping time is not possible at the moment. Also, it has been shown that patient-heterogeneity isdetermined by different mechanisms, including the growth rate of malignant cells, the efficiency of TKI treatment, and the individualimmune response. There is increasing evidence that the latter one represents a major determinant for the relapse risk after TKI cessation.Here, we will extend a previously developed and validated mathematical model of TKI-treated CML. Based on different, high quality datasets from clinical studies, we will adapt the model for the situation of TKI-cessation, which requires to consider stem cell dynamics as well asimmune effects. Specifically, we will advance an already developed “demonstrator” version of the model with the objective to provide asoftware environment that allows to integrate clinical data and simulation results. It is our particular aim to support clinical decision-makingwith respect to relapse risk assessment and TKI cession planning at the level of individual patients. |
| Network | ERACoSysMed |
| Call | 2nd Joint Transnational Call for European Research Projects on Systems Medicine |
Project partner
| Number | Name | Role | Country |
|---|---|---|---|
| 1 | Technische Universität Dresden | Coordinator | Germany |
| 2 | Universitätsklinikum Jena | Partner | Germany |
| 3 | Norwegian University of Science and Technology (NTNU), | Partner | Norway |
| 4 | CRLCC Institut Bergonié and Laboratoire Oncogenèse Mammaire et Leucémique INSERM U1218 ACTION | Partner | France |
| 5 | University of Helsinki (UH) and Helsinki University Central Hospital (HUCH), Hematology Research Unit Helsinki (HRUH) | Observer | Finland |
| 6 | University Clinic Giessen and Marburg | Observer | Germany |
| 7 | Inserm Clinical Investigation Centre 1402 | Partner | France |