Hydroxyurea treatment of sickle cell disease: towards a personalized model-based approach

Abstract

Hydroxyurea is a commonly used drug for the treatment of sickle cell disease. Several studies have demonstrated the efficacy of hydroxyurea in ameliorating disease pathophysiology. However, a lack of consensus on optimal dosing and the need for ongoing toxicity monitoring for myelosuppression limits its utilization. Pharmacokinetic (PK) and pharmacodynamic (PD) studies describe drug-body interactions, and hydroxyurea PK-PD studies have reported wide inter-patient variability. This variability can be explained by a mathematical model taking into consideration different sources of variation such as genetics, epigenetics, phenotypes, and demographics. A PK-PD model provides us with a tool to capture these variant responses of patients to a given drug. The development of an integrated population PK-PD model that can predict individual patient responses and identify optimal dosing would maximize efficacy, limit toxicity, and increase utilization. In this review, we discuss various treatment challenges associated with hydroxyurea. We summarize existing population PK-PD models of hydroxyurea, the gap in the existing models, and the gap in the mechanistic understanding. Lastly, we address how mathematical modeling can be applied to improve our understanding of hydroxyurea’s mechanism of action and to tackle the challenge of interpatient variability, dose optimization, and non-adherence.