Incorporating prior knowledge into Q-learning for drug delivery individualization

Individualization of drug delivery in treatment of chronic ailments is a challenge to the physician. Variability of response across patient population requires tailoring the dosing strategies to individual´s needs. We have previously demonstrated the potential of reinforcement learning methods to support the physician in the management of anemia. In this paper, we propose the incorporation of prior knowledge into the learning mechanism to further improve the outcomes of the treatment.