Utilization of Tracer Kinetic Data in Endogenous Pathway Modeling: Example from Alzheimerís Disease
Huub Jan Kleijn, Tom Bradstreet, Mary Savage, Mark Forman, Matthew Kennedy, Arie Struyk, Rik de Greef, Julie A. Stone
Merck Research Laboratories, Whitehouse Station, NJ, US
Objectives: Tracer kinetic studies can be a valuable tool to gain understanding on the dynamics of protein pathways. However, results interpretation is difficult and requires a model-based evaluation to take full advantage of the data. In this example, timecourse data on CSF tracer and ELISA-based total CSF Aβ were obtained under unaltered, mild and potent production inhibition with a BACE inhibitor in healthy human to inform understanding of the amyloid pathway, which is central to plaque formation in Alzheimer's Disease. Our goal was to establish a mechanistic pathway model that describes the total Aβ, fraction labeled Aβ, and newly generated Aβ with a single drug action (inhibition of BACE) to enhance understanding of the utility and interpretation of tracer kinetic data.
Methods: Subjects (n=5/arm) received single doses of placebo, low or high dose BACE inhibitor with 13C-labeled leucine infused from 5 to 15 hours post-dose. Serial plasma and CSF samples were obtained for assessment of drug concentration, total Aβ, and fraction of leucine and Aβ labeled.
Data were fit to a compartmental model reflecting brain pools for precursor protein, BACE cleavage product C99, gamma secretase cleavage product Aβ and distribution to the lumbar CSF sampling site. Duplicate pathways were needed, informed by the timecourse of fraction 13C-labeled leucine, to separately describe the labeled and unlabeled fractions. BACE inhibition was modeled as an Emax function on the production rate of C99.
Results: The model was able to simultaneously describe the time courses of total Aβ, fraction labeled Aβ, and newly generated Aβ with a single drug action. Rate constants related to steps in the amyloid pathway could be separated from delays related to distributional processes. Simulations indicated that timing of 13C-leucine infusion relative to dosing of the BACE inhibitor is key in obtaining informative data on the underlying system.
Conclusions: Tracer kinetic approaches together with mechanistic modeling enhance the understanding of endogenous pathway dynamics. A model-based analysis allowed to distinguish between steps in the amyloid pathway and distributional processes. This framework enables a more physiologically based approach to account for effects of Aβ oligomers and/or plaque pool in Alzheimer's disease. Finally, model-based simulations inform on improvements of the experimental design that will maximize derived knowledge on the underlying system pharmacology of the amyloid pathway.