Eder is primarily interested in the mechanisms underpinning neuroendocrine regulation of the Hypothalamic-Pituitary-Adrenal (HPA) axis. His goal is to develop a mathematical understanding of hormone dynamics that includes rhythmic secretion, responses to perturbations, and long-term physio-pathological changes. To do this, he works alongside a range of interdisciplinary collaborators to propose models that offer testable predictions. He has developed mathematical models of the adrenal steroidogenic gene regulatory network that successfully predicts dynamic responses to ACTH perturbations of different magnitude. By including the crosstalk interactions with the immune pathway, his models also explain the sustained glucocorticoid activation observed during the inflammatory stress response.
Currently, Eder is extending this theoretical framework to integrate rhythmicity and stress, while also considering how these processes interact with the metabolic and reproductive endocrine axes. His plan is to continue developing these multiscale mathematical models to understand the dynamic changes elicited by disease, with a focus on understanding the disruption of these mechanisms during stress-related disorders.
Eder is also interested in healthcare technologies for diagnosing and monitoring the progression of illness. To do this, he is developing a quantitative analysis of continuously-sampled 24h ambulatory micro-dialysis hormone profiles to identify novel dynamic
biomarkers that signal disease more efficiently than current single time point diagnosis. Eder combines this with the analysis of wearable device data (e.g., physical activity, heart rate, temperature, glucose, and sleep tracking) collected simultaneously with continuous hormone and metabolite microdialysates to characterise the dynamic human chronobiome.