Predicting the impact of healthy aging on the brain pharmacokinetic profiles using a translational modeling approach
Mohammed A. A. Saleh (1), Jeroen Elassaiss-Schaap (1,2), Elizabeth C. M. de Lange (1)
(1) Division of Systems Biomedicine and Pharmacology, Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands, (2) PD-value, Houten, The Netherlands
Objectives: Unbound drug concentrations at brain extracellular (ECF) and intracellular (ICF) target sites are the drivers of CNS drug (side) effects. Predicting these target site pharmacokinetic (PK) profiles is thus crucial for CNS drug development. Measuring unbound PK profiles in the human’s brain is restricted by the ethical limitations of human brain sampling and the technical challenges associated with imaging techniques, while cerebrospinal fluid (CSF) surrogates for unbound brain PK profiles appear context-dependent [1]. We have previously published LeiCNS-PK3.0, a physiologically-based PK (PBPK) model of the central nervous system (CNS) that can predict rat and human brain ECF and CSF PK profiles within the two-fold error limit, exclusively on the basis of drug physicochemical and CNS physiological properties [2]. The mechanistic and physiological structure of LeiCNS-PK3.0 allows translating the PK profiles between species and between populations. Here, we aim to predict the impact of healthy aging on the brain ECF and ICF PK profiles, by accounting for CNS physiological changes that are associated with aging.
Methods: We performed an extensive literature search on aging-related physiological changes of BBB surface area, passive permeability, and active transporters; brain and CSF volume; pH within the different CNS compartments; non-specific binding; and brain ECF bulk-, CSF-, and cerebral blood flow. Both parameter values and their change rates over age (where available) were extracted and used as model input. Model simulations were performed for acetaminophen, morphine, and indomethacin, which have distinct physicochemical properties in terms of lipophilicity and ionization at physiological pH. The PK profiles at the brain ECF and ICF of young adults and of elderly from 60 to 100 years old were compared. A sensitivity analysis was performed for parameters that were not available from literature, and the impact of such changes on brain ECF and ICF PK profiles was investigated. Model building and simulation were performed in R (version 4.0.3) and the R-package RxODE (version 0.9.2-0).
Results: We have demonstrated based on LeiCNS-PK3.0 simulations that brain PK profiles might change over the course of healthy aging, depending on the extent of change in CNS physiology and on the drug physicochemical properties. Cmax and AUC of acetaminophen at the brain ECF and the brain ICF of 100 years old decreased slightly (<10%) compared to that of a young adult. Cmax and AUC of morphine increased at the brain ECF by about 20%, while those at the brain ICF decreased by >40%. Cmax and AUC of indomethacin decreased in both the brain ECF and ICF by 30% and 25%, respectively. Tmax did not change at brain ECF or ICF for any of the drugs.
Conclusions: Using translational PBPK modeling, we have demonstrated that PK profiles at brain target sites might be altered during healthy aging, in a drug dependent manner. This approach can be extended for other drugs to improve drug dosing in the aging population.
References:
[1] Saleh and de Lange. Pharmaceutics. 2021. Doi:10.3390/pharmaceutics13010095.
[2] Saleh et al. J. Pharmacokinet. Pharmacodyn. 2021. Under review.