Systems pharmacokinetic models to the prediction of local CNS drug concentrations in human

Yamamoto, Y. (2017)

Doctoral Thesis

Clinical development of drugs for central nervous system (CNS) disorders has been particularly challenging and still suffers from high attrition rates. This high attrition is mainly due to lack of efficacy during clinical development. To improve the prediction of CNS drug effects, knowledge of the drug concentration at the CNS target-site is indispensable. Unfortunately, measuring drug concentrations in the human CNS has major practical and ethical constraints. Therefore, alternative approaches to predict the drug pharmacokinetics (PK) at the target-site(s) in the human CNS should be searched for.

In this research, a comprehensive CNS physiologically based PK (PBPK) model for prediction of drug concentration-time profiles in multiple CNS compartments was developed for both rats and humans. The CNS PBPK model only requires knowledge of physicochemical properties of the drugs, with the influence of the net active transporters on the drug exchange across the BBB and the BCSFB that can be obtained from in silico predictions, literature information and in vitro studies (if needed). Because of this, the developed CNS PBPK model is a powerful tool to predict drug PK in the CNS in the early stage of the drug development.

• CNS
• BBB
• BCSFB
• PK
• PBPK model
• Translational research

• All authors: Yamamoto, Y.
• Supervisor: Danhof, M.
• Co-supervisor: Lange, E.C.M. de
• Committee: Irth, H.; Bouwstra, J.A.; Rostami, A.; Masereeuw, R.; Burggraaf, J.; Meijer, O.C.; Hankemeier, T.
• Qualification: Doctor (dr.)
• Awarding Institution: Pharmacology, Science, Leiden University
• Date: 2017-11-21
• ISBN (print): 9789462996847