  While many novel therapies have been approved in recent years for treating
patients with multiple myeloma, there is still no established curative regimen,
especially for patients with high risk disease. In this work, we use a
mathematical modeling approach to determine combination therapy regimens that
maximize healthy lifespan for patients with multiple myeloma. We start with a
model of ordinary differential equations for the underlying disease and immune
dynamics, which was presented and analyzed previously. We add the effects of
three therapies to the model: pomalidomide, dexamethasone, and elotuzumab. We
consider multiple approaches to optimizing combinations of these therapies. We
find that optimal control combined with approximation outperforms other
methods, in that they can quickly produce a combination regimen that is
clinically-feasible and near-optimal. Implications of this work can be used to
optimize doses and advance the scheduling of drugs.
