The Neuroplatform: Towards a comprehensive mechanistic model of Alzheimer's disease for supporting drug discovery and development

The success of amyloid antibodies has generated a lot of excitement in the Alzheimer (AD) community. Twenty years after the approval of the symptomatic treatments, patients and health care providers are looking forward to a new generation of disease modifying treatment. However, there is still a long way to go. To support these efforts, we developed a comprehensive mechanistic Quantitative Systems Pharmacology of the different major pathologies in AD; (amyloid, tau and neuroinflammation) combined with a computational neuroscience model that predict efficacy on a clinically relevant scale. The amyloid aggregation model, coupled with a Physiology-Based Pharmacokinetic (PBPK) model for drug exposure in the human brain demonstrated that lecanemab or Lequembi was sufficiently different from the previous failed antibodies both in efficacy and side-effects. The model models the cross-talk between amyloid and tau and is currently being used for supporting clinical decision in real world situations with readouts both in biomarker change and functional clinical scales. The progression of misfolded tau proteins is modeled using both a traditional ODE approach as well as a spatial Mont-Carlo approach that takes into account realistic geometry of the brain synapse and provides a reasonable biological explanation for the failure of many anti-tau antibodies. To account for neuroinflammation targets such as TREM2, the amyloid model is coupled with an extensive microglia model allowing to simulate intracellular pathways and phenotype switching. Finally, this all comes together in a computational neuroscience model, where biophysically realistic action potentials in relevant neuronal networks are simulated and drive cognitive outcomes. Amyloid, tau pathology and microglia derived cytokines affect different voltage-gated and ligand gated channels, the effect of which is calibrated using clinical data of successful and negative trials with amyloid antibodies. This allows for generating virtual twin profiles with specific comedications and common genotype variants, ultimately reducing variability in clinical trial readouts. Hugo Geerts is Head Neuroscience Applied Biosimulation at Certara. His studies included a physics degree, a Biophysics PhD, a Bachelor Degree in Medicine, a Master in Pharmaceutical Sciences, and a Pharma Executive MBA. He worked for 17 years with Dr. Paul Janssen, the greatest drug hunter in history at the Janssen Research Foundation heading the Alzheimer Discovery research. He identified galantamine (Razadyne-Reminyl) for inlicensing and supported its successful clinical development. His team was one of the first in industry to initiate R&D projects focused on tau pathology for Alzheimer’s Disease and to publish on transgene mouse models with tau pathology. In 2002, he co-founded In Silico Biosciences (ISB) to provide mechanistic disease modeling services in CNS R&D, combining his degrees in physics and medicine with the discipline of computational neurosciences into a comprehensive Quantitative Systems Pharmacology approach for Alzheimer’s, Parkinson’s disease and schizophrenia. He has published over 120 papers and is an inventor on multiple patents related to modeling. The acquisition of ISB by Certara combined state-of-the-art PBPK modeling with mechanistic simulation. For more information see: https://www.certara.com/blog/building-a-robust-clinical-pharmacology-model-informed-drug-development-strategy-for-new-alzheimers-disease-drugs/ *Contents* 00:00 - Introduction 05:48 - The Neuroplatform: Towards a comprehensive mechanistic model of Alzheimer's disease for supporting drug discovery and development 01:00:47 - Questions and Discussion Moderator: Tom Helikar, PhD, University of Nebraska, Lincoln If you found this video useful, please check out our other videos on computational modeling, infection and immunology: https://youtube.com/playlist?list=PLiEtieOeWbMKh9VcQoinSwODcSZKMTGat Please consider joining our IMAG/MSM WG on Multiscale Modeling and Viral Pandemics: https://www.imagwiki.nibib.nih.gov/content/msm-viral-pandemics-meetings Please also consider joining the Global Alliance for Immune Prediction and Intervention: http://glimprint.org/