Currently, there is great interest in incorporating biological information into intensity-modulated radiotherapy (IMRT) treatment planning with the aim of selectively boosting high-risk tumor subvolumes - a concept that has also been called 'dose painting'. However, conventional IMRT optimization utilizes dose-volume based objective functions, which have inherent limitations such as pursuing homogeneous dose distributions and assuming linear-dose-response curves. In this book we present a dose painting IMRT optimization-framework in which nonlinear biological objective functions are utilized. Prostate cancer has been used as a model system to explore its feasibility. The impact of functional imaging accuracy such as sensitivity and specificity on dose painting IMRT is subsequently presented. A comparison study between dose painting IMRT strategies and uniform-boosting IMRT strategies yielding the same EUD to the overall PTV is also presented. A novel dose painting IMRT strategy using biological parameters is proposed and promises increased expected local control for locoregionally advanced tumors with equivalent or better normal tissue sparing.