LAUSR

Harnessing the full therapeutic potential of the explosively growing universe of immuno-oncology (IO) drug targets and diverse therapeutic modalities in a highly competitive clinical research landscape demands commitment to principled decisions through biologically sound quantitative translation. Model-informed multidimensional optimization of dose, schedule, combination, and patient population remains an untapped opportunity. Herein, we offer perspectives on approaches to model-informed decision making in early clinical development with a Bayesian mindset that exploits the totality of evidence.