LAUSR

Abstract Scheduling therapies is a central paradigm in personalized medicine. Modeling and control theoretical approaches are opening an avenue for linking interactions between drugs and diseases in the host. In this paper, considering an inverse optimal approach, we formulate a framework based on a bounded input impulsive control to schedule therapies. Results for stability with a bounded input are introduced. We show the application of the algorithms with illustrative examples as well as the biomedical application of the long-term impact of therapies for a functional HIV cure. Results highlight that the proposed framework has the potential for tailoring therapies in different diseases such as diabetes, cancer, and infectious diseases.