Quantitative Systems Pharmacology Model for Alzheimer Disease Indicates Targeting Sphingolipid Dysregulation as Potential Treatment Option

Abstract

Alzheimer disease (AD) is a devastating neurodegenerative disorder with high unmet medical need. Drug development is hampered by limited understanding of the disease and its driving factors. Quantitative Systems Pharmacology (QSP) modeling provides a comprehensive quantitative framework to evaluate the relevance of biological mechanisms in the context of disease and to predict the efficacy of novel treatments. Here, we report a QSP model for AD with a particular focus on investigating the relevance of dysregulation of cholesterol and sphingolipids. We show that our model captures the modulation of several biomarkers in subjects with AD, as well as the response to pharmacological interventions. We evaluate the impact of targeting the sphingosine‐1‐phosphate 5 receptor (S1PR5) as a potential novel treatment option for AD, and model predictions increase our confidence in this novel disease pathway. Future applications for the QSP model are in validation of further targets and identification of potential treatment response biomarkers.

Quantitative Systems Pharmacology and Empirical Models: Friends or Foes?

“…(Image reprinted from ref. , CPT: Pharmacometrics & Systems Pharmacology https://doi.org/10.1002/psp4.12351, image is licensed under CC BY‐NC‐ND 4.0. ©2018 The authors.)…”

Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

“…QSP modeling can also be leveraged for biomarker identification, and its mechanistic detail can provide valuable insights to new potential targets. An example in Alzheimer's disease is the QSP model ( Figure ) published by Clausznitzer et al . that includes lipid dysregulation in the brain with a focus on sphingosine‐1‐phosphate receptor 5 (S1PR5).…”

“…Figure reprinted from Clausznitzer et al . , licensed under CC BY ‐ NC ‐ ND 4.0 © 2018 The Authors. Aβ, amyloid‐beta; APP, amyloid precursor protein; AD, Alzheimer's disease; BL, baseline level; Cer, ceramide; CSF, cerebrospinal fluid; E max , maximal effect; Ka, absorption rate constant; Ke, elimination rate constant; PK, pharmacokinetic; V, volume of central compartment; VBrain, volume of brain compartment; V2, volume of peripheral compartment.…”

“…A decade later, this model was used by the US Food and Drug Administration (FDA) to address a safety concern of hypercalciuria for a drug, parathyroid hormone (NATPARA), in an entirely different indication (hypoparathyroidism). Similarly, the Alzheimer's disease QSP model presented earlier was used to identify new targets in the lipid regulation pathway that were not previously studied in the clinic …”

“…Biomarker identification and selection QSP modeling can also be leveraged for biomarker identification, and its mechanistic detail can provide valuable insights to new potential targets. An example in Alzheimer's disease is the QSP model ( Figure 2) published by Clausznitzer et al 21 that includes lipid dysregulation in the brain with a focus on sphingosine-1-phosphate receptor 5 (S1PR5). The model reproduces expected baseline levels of lipids and amyloid-beta (Aβ) for healthy and Alzheimer's Disease subjects, and appropriately captured reported plasma and cerebral spinal fluid treatment responses to several therapies.…”