Exploratory translational modeling approach in drug development to predict human brain pharmacokinetics and pharmacologically relevant clinical doses.

The central nervous system (CNS) pharmacokinetics (PK) of drugs that have pharmacological targets in the brain are not often understood during drug development, and this gap in knowledge is a limitation in providing a quantitative framework for translating nonclinical pharmacologic data to the clinical patient population. A focus of translational sciences is to improve the efficiency of clinical trial design via a more judicious selection of clinical doses on the basis of nonclinical data. We hypothesize that this can be achieved for CNS-acting drugs based on knowledge of CNS PK and brain target engagement obtained in nonclinical studies. Translating CNS PK models from rat to human can allow for the prediction of human brain PK and the human dose-brain exposure relationship, which can provide insight on the clinical dose(s) having potential brain activity and target engagement. In this study, we explored the potential utility of this translational approach using rat brain microdialysis and PK modeling techniques to predict human brain extracellular fluid PK of atomoxetine and duloxetine. The results show that this translational approach merits consideration as a means to support the clinical development of CNS-mediated drug candidates by enhancing the ability to predict pharmacologically relevant doses in humans in the absence of or in association with other biomarker approaches.