Optimization of tisagenlecleucel treatments of lymphoma: An integrated human data-based approach using mathematical models
Cancer immunotherapies use components of the patient immune system to selectively target and attack tumor cells. Immunotherapies are an effective treatment option for hematological malignancies. The most successful type of immunotherapy today is Chimeric antigen receptor (CAR) T cell. This treatment consists of helping T cells to fight cancer by changing them in the lab so they can find and destroy cancer cells. CAR T cell therapies have shown relevant results in patients with B cell malignancies such as leukemia, lymphoma, and multiple myeloma. However, relapsed, or refractory B-cell malignancies after two or more lines of therapy have a poor prognosis. The problem addressed is the correct identification of non-responders to CAR T cell therapy at the time of decision to treat. To solve this problem, this project aims to use mathematical models to describe disease dynamics in patients. These models will be used to optimize, personalize, and improve CAR T cells treatment of B cell malignancies.
Funding entity
NOVARTIS (2023-2025)
University of Castilla-La Mancha, Spanish Group of Hematopoietic Transplants and Cellular Therapies
Principal investigator
3 years