Mathematical modeling of gene and cell therapy for HIV cure
Antiretroviral therapy (ART) suppresses levels of plasma Human Immunodeficiency Virus (HIV) below detection limits in standard assays. However, due to a latent reservoir of long-lived, HIV-infected cells, ART does not cure HIV and must be taken daily. Only five known cases of HIV cure have resulted in individuals receiving allogeneic hematopoietic stem cell transplantation (HSCT) for their hematological malignancies. Ongoing gene and cell therapy strategies appear promising to attain an HIV remission like the ones achieved during allogeneic HSCT by either protecting susceptible cells from HIV or boosting the immune system with infusions of T cells or antibody-like peptides targeting HIV-infected cells. We have developed ordinary differential equation models that parsimoniously recapitulate viral load and T-cell measurements from SHIV-infected, non-human primates (NHP) receiving several gene/cell therapies. We have simulated each data-validated model to find optimal conditions in which those strategies provide ART-free HIV remission. Although gene and cell therapy strategies for HIV cure are in the early stages, mathematical modeling might contribute to accelerating the success of these approaches.