Less is more: reducing the number of administered chimeric antigen receptor T cells in a mouse model using a mathematically guided approach.

Chimeric antigen receptor T cell (CAR-T) therapy is a novel approved treatment for hematological malignancies, still under development for solid tumors. Here, we use a rate equation-based mathematical model to discover regimens and schedules that maintain efficacy while potentially reducing toxicity by decreasing the amount of CAR-T infused. Tested on an in vivo murine model of spontaneous breast cancer, we show that our mathematical model accurately recapitulates in vivo tumor growth results achieved in the previous experiments.

Improving Bacillus Calmette-Guérin (BCG) immunotherapy for bladder cancer by adding interleukin 2 (IL-2): a mathematical model.

One of the treatments offered to non-invasive bladder cancer patients is BCG instillations, using a well-established, time-honoured protocol. Some of the patients, however, do not respond to this protocol. To examine possible changes in the protocol, we provide a platform for in silico testing of alternative protocols for BCG instillations and combinations with IL-2, to be used by urologists in planning new treatment strategies for subpopulations of bladder cancer patients who may benefit from a personalized protocol.

Improving T-cell immunotherapy for melanoma through a mathematically motivated strategy: efficacy in numbers?

T-cell mediated immunotherapy for malignant diseases has become an effective treatment option, especially in malignant melanoma. Recent advances have enabled the transfer of high T-cell numbers with high functionality. However, with more T cells becoming technically available for transfer, questions about dose, treatment schedule, and safety become most relevant.

Predicting outcomes of prostate cancer immunotherapy by personalized mathematical models.

Background: Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.

Methodology/principal Findings: We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine.

Improving alloreactive CTL immunotherapy for malignant gliomas using a simulation model of their interactive dynamics.

Glioblastoma (GBM), a highly aggressive (WHO grade IV) primary brain tumor, is refractory to traditional treatments, such as surgery, radiation or chemotherapy. This study aims at aiding in the design of more efficacious GBM therapies. We constructed a mathematical model for glioma and the immune system interactions, that may ensue upon direct intra-tumoral administration of ex vivo activated alloreactive cytotoxic-T-lymphocytes (aCTL).