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Modelling of Anti-amyloid-Beta Therapy for Alzheimer’s Disease

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Bioinformatics and Biomedical Engineering (IWBBIO 2023)

Abstract

A healthy brain clears different types of debris with the help of specialized glial cells. These cells contiguously tile the entire central nervous system (CNS), exert many essential complex functions in the healthy CNS, and maintain a healthy balance in the brain. However, over age, these cells fail to control the healthy balance of the proteins and cause different neurodegenerative diseases, one of which is Alzheimer’s disease (AD). In AD, insoluble amyloid-beta plaques accumulate in the extracellular space along with neurofibrillary tangles (NFTs) inside the brain cells. In this paper, we have developed a model and studied the accumulation of amyloid-beta plaques and NFTs along with an anti-amyloid-beta therapy applied in the treatment of the disease. Based on these studies, we have demonstrated the dynamics of the modelling therapy such that the drug helps clear a subsequent amount of amyloid-beta plaques in each dose. Numerical simulations have been used to show different long-term outcomes of the model. To further analyze the disease progression in the brain and its treatment, we have integrated brain connectome data in the network model as part of our developed modelling framework.

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Acknowledgements

The authors thank the NSERC and the CRC Program for their support. RM also acknowledges the support of the BERC 2022-2025 program and the Spanish Ministry of Science, Innovation and Universities through the Agencia Estatal de Investigacion (AEI) BCAM Severo Ochoa excellence accreditation SEV-2017-0718. This research was partly enabled by support provided by SHARCNET (www.sharcnet.ca) and Digital Research Alliance of Canada (www.alliancecan.ca).

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Correspondence to Roderick Melnik .

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Pal, S., Melnik, R. (2023). Modelling of Anti-amyloid-Beta Therapy for Alzheimer’s Disease. In: Rojas, I., Valenzuela, O., Rojas Ruiz, F., Herrera, L.J., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2023. Lecture Notes in Computer Science(), vol 13919. Springer, Cham. https://doi.org/10.1007/978-3-031-34953-9_34

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  • DOI: https://doi.org/10.1007/978-3-031-34953-9_34

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  • Online ISBN: 978-3-031-34953-9

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