(M1130-11-61) Systematic In Silico Analysis of Clinically Tested Drugs for Reducing Amyloid-Beta Plaque Accumulation in Alzheimer's disease

Purpose: Despite strong evidence linking amyloid beta (Aβ) to Alzheimer's disease, most clinical trials have shown no clinical efficacy for reasons that remain unclear. To understand why, we developed a quantitative systems pharmacology (QSP) model for seven therapeutics including 4 anti-Aβ monoclonal antibodies (mAbs) (aducanumab, crenezumab, solanezumab, bapineuzumab), 2 ꞵ-secretase enzyme (BACE) inhibitor (elenbecestat, verubecestat), and 1 ɣ-secretase inhibitor (semagacestat).

Methods: Ordinary differential equations were used to model the production, transport, and aggregation of Aβ; pharmacology of the drugs; and their impact on plaque.

Results: The Aβ biology module matched available data for Aβ dynamics in CSF from stable isotope labeling kinetics (SILK) experiments. The drug pharmacology modules together with the Aβ biology module captured the available PK and PD data for seven drugs including the observed amyloid plaque reduction (or lack of reduction). The model was used to explore doses and regimens that have not been tested clinically including a comparison of equal doses and regimens for all four anti-Aβ mAbs. The model predicted bapineuzumab and aducanumab to induce the fastest plaque reduction when given at the same dose and regimen among the four mAbs. Additional model analysis revealed that binding to plaque and the induction of active clearance of plaque, potentially through antibody dependent cellular phagocytosis (ADCP), could be the most effective approach to reduce amyloid plaque. For drugs aiming at preventing plaque formation (e.g., BACE inhibitors and mAbs binding to Aβ monomer and oligomer, such as solanezumab), the reduction rate of existing plaque is limited by the endogenous turnover rate of plaque. The predicted slow speed of this process (half-life of ≈2.75 years), could explain the relatively small magnitude of plaque reduction observed with BACE inhibitors after 2 years of treatment.

Conclusion: A QSP model can integrate clinical results from multiple molecules to provide novel insights. Our model explains the results of clinical trials and provides guidance for future therapeutic development.

Acknowledgements: Authors have no conflict of interest