Mechanistic Modeling of Soluble Aβ Dynamics and Target Engagement in the Brain by Anti-Aβ mAbs in Alzheimer's Disease.

Background: Anti-amyloid-beta (A beta) monoclonal antibodies (mAbs) are currently in development for treating Alzheimer's disease. Objectives: To address the complexity of A beta target engagement profiles, improve the understanding of crenezumab Pharmacokinetics (PK) and A beta Pharmacodynamics (PD) in the brain, and facilitate comparison of anti-A beta therapies with different binding characteristics. Methods: A mechanistic mathematical model was developed describing the distribution, elimination, and binding kinetics of anti-A beta mAbs and A beta (monomeric and oligomeric forms of A beta(1-40) and A beta(1-42)) in the brain, Cerebrospinal Fluid (CSF), and plasma. Physiologically meaningful values were assigned to the model parameters based on the previous data, with remaining parameters fitted to clinical measurements of A beta concentrations in CSF and plasma, and PK/PD data of patients undergoing anti-A beta therapy. A beta target engagement profiles were simulated using a Monte Carlo approach to explore the impact of biological uncertainty in the model parameters. Results: Model-based estimates of in vivo affinity of the antibody to monomeric A beta were qualitatively consistent with the previous data. Simulations of A beta target engagement profiles captured observed mean and variance of clinical PK/PD data. Conclusion: This model is useful for comparing target engagement profiles of different anti-A beta therapies and demonstrates that 60 mg/kg crenezumab yields a significant increase in A beta engagement compared with lower doses of solanezumab, supporting the selection of 60 mg/kg crenezumab for phase 3 studies. The model also provides evidence that the delivery of sufficient quantities of mAb to brain interstitial fluid is a limiting step with respect to the magnitude of soluble A beta oligomer neutralization.