A Semi-Physiological Model of Amyloid-β Biosynthesis and Clearance in Human Cerebrospinal Fluid: A Tool for Alzheimer's Disease Research and Drug Development

Authors

  • Karin G. Haug PhD,

    1. Department of Pharmaceutics, University of Florida, Gainesville, FL, USA
    2. Department of Translational Medicine, Pharmacometrics, Boehringer Ingelheim Pharma GmbH & Co KG, Biberachan der Riss, Germany
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  • Alexander Staab PhD,

    1. Department of Translational Medicine, Pharmacometrics, Boehringer Ingelheim Pharma GmbH & Co KG, Biberachan der Riss, Germany
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  • Chantaratsamon Dansirikul PhD,

    1. Department of Translational Medicine, Pharmacometrics, Boehringer Ingelheim Pharma GmbH & Co KG, Biberachan der Riss, Germany
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  • Thorsten Lehr PhD

    Corresponding author
    1. Clinical Pharmacy, Saarland University, Saarbruecken, Germany
    • Department of Translational Medicine, Pharmacometrics, Boehringer Ingelheim Pharma GmbH & Co KG, Biberachan der Riss, Germany
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Corresponding Author:

Thorsten Lehr, PhD, Junior-Professor of Clinical Pharmacy, Saarland University, Campus C2 2, Saarbruecken 66123, Germany

Email: thorsten.lehr@mx.uni-saarland.de

Abstract

Stable isotope labeling kinetics (SILK) was successfully applied to quantify endogenous amyloid-β (Aβ) metabolism in human cerebrospinal fluid (CSF). A semi-physiological model describing Aβ biosynthesis and degradation in human CSF and the impact of the γ-secretase inhibitor semagacestat should be developed and validated based on digitized data from three published SILK studies. Aβ biosynthesis was adequately characterized by six transit compartments. At each transition step, a first-order degradation process was implemented. A two-compartment model best described semagacestat CSF concentration-time profiles. Semagacestat concentrations were linked to the Aβ production by an inhibitory Emax model. For model validation, three individual Aβ profiles from literature were successfully predicted. Model application demonstrated a 35% decreased Aβ elimination rate constant in Alzheimer's disease (AD) patients. Study design optimization revealed that SILK studies could be conducted with significant less sampling points compared to the standard protocol without losing information about the Aβ metabolism, if analyzed by the presented model. In conclusion, the analysis outlined the advantages and opportunities of integrating all available data and knowledge into a semi-physiological model. The model can serve as valuable tool for researchers and clinicians interested in the pathology of AD as well as in the development of new therapeutics for AD.

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