BACKGROUND: Apoptosis is a highly regulated and irreversible process of cell death, while autophagy maintains cellular homeostasis by degrading and recycling cytoplasmic components, such as aggregated and damaged proteins (Elmore, 2007; Glick et al., 2010). Dysregulation of both processes is observed in neurodegenerative diseases (NDs) (Ghavami et al., 2014). For example, in Alzheimer’s disease (AD), accumulation of amyloid-β peptides is attributed to dysregulated autophagy (Han et al., 2020). Dysregulated autophagy can further induce apoptosis and neurodegeneration (Chung et al., 2018). Although studies have focused on signaling pathways involved in apoptosis and autophagy extensively in other cell types, an effective framework to clarify their interplay in the nervous system is lacking. Here we develop a simplified network model of the key pathways involved in apoptosis and autophagy to study their interplay and dysregulation in NDs. Specifically, we model triggers such as cell stress and Ca2+ dysregulation implicated in aging and NDs and simulate their effects on cell fate. Although much of the empirical support to model development came from studies in other cell types, our integrative framework of the ubiquitous and non-cell autonomous pathways can offer deeper insights into the pathophysiology in NDs. METHODS: Ordinary differential equations (ODEs) were used to model the network of molecular compartments, and the rates of change in their abundances and interactions. The interconnections between these compartments, for example, the inhibitory role of caspases on autophagy-inducing Beclin-1(BECN1), are validated in empirical work and adopted in previous modeling studies (Bogdał et al., 2013; Fan and Zong, 2013; Mariño et al., 2014; Tavassoly et al., 2015; Wirawan et al., 2010; Yin et al., 2017). MATLAB was used to code and simulate the model; ode45 was the numerical integration method of choice. RESULTS: We developed an integrative framework for the signaling pathways of apoptosis and autophagy. Our model adapted and merged three previously reported dynamic network models (Bogdal et al., 2013; Tavassoly et al., 2015; Yin et al., 2017) which also included pathways relevant to NDs. A hypothetical cell stress input and cytosolic Ca2+ concentration in our network model represent extrinsic and intrinsic triggers respectively. Using such a computational approach, we are investigating the multiplexing role of Beclin 1 protein (part of Bcl-2 protein family), mTOR (mammalian target of rapamycin) kinase and JNK (Jun N-terminal kinase) in the synergy between autophagy and apoptosis. Simulation experiments are underway to predict the mechanisms of cell vulnerability versus resilience implicated in NDs involving these pathways. CONCLUSION: Our network provides a framework based on which experiments can be designed to validate model predictions and better understand the dynamic processes involved in NDs. Although NDs are complex and chronic, understanding the effects of common triggers such as cell stress and disrupted Ca2+ homeostasis on cell fate determination is critical to slow ND progression. Therefore, our study delineating the dynamic crosstalk between apoptosis and autophagy offers crucial insights into ND pathophysiology and suggests specific protein targets within these key common pathways. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.