Combinatorial strategies are considered as the future of immunotherapy in oncology. A rising number of clinical trials have thus tried to combine immune checkpoint inhibitors with cytotoxics, targeted therapies or radiation therapy, as an attempt to turn once "cold" tumors into "hot" ones. Quite notably, most of these combinations have been tested on an empirical basis so far, i.e, simply by adding immunotherapy to already existing regimen. Of note, immunomodulating features are probably drug-, dose- and schedule-dependent, thus calling for developing model-driven studies with strong pharmacometrics support. For instance, thePK/PD relationships with immune checkpoint inhibitors, and the complex interplay between treatments, have all been neglected for too long and could partly explain the high attrition rate of such combinatorial studies. By developing appropriate models, designing optimal combinations in terms of dosing, scheduling and sequencing would help reducing this attrition rates.
Upon completion, participant will be able to understand the current challenges when setting up combinatorial strategies with immune checkpoint inhibitors.
Upon completion, participant will be able to understand why dosing, scheduling and sequencing of the combined treatments could matter eventually.
Upon completion, participant will be able to understand trhe current challeznges in picturing the exact PK/PD relationships with immunotherapy.
Upon completion, participant will be able to discuss whether or not modeling support could help to refine the way combinatorial strategies are set up in oncology.