Hybrid
On-site Venue:
Conference Room, B1F, Faculty of Medicine Bldg. B (No.6 in map), Kyoto University
https://www.kyoto-u.ac.jp/en/access/medicine-campus-map
Abstract:
Personalised medicine holds great promise for improving treatment outcomes in complex, chronic diseases like eczema and asthma. But realizing this potential requires a deep understanding of the complex biological mechanisms involved. In this kick-off seminar, I will present our recent work integrating mathematical modelling with machine learning and AI to design patient-specific treatment strategies for allergic diseases.
Our group has developed a mathematical model of eczema pathogenesis that captures the dynamic interplay between skin barrier integrity, immune responses, and environmental stressors, a triangle of interactions interlinked through intricate positive and negative feedback loops. This model not only explains the onset and progression of eczema but also reveals potential routes for prevention and intervention. Expanding further, we have incorporated the role of the skin microbiome, a key player in eczema pathophysiology, into our computational framework. These in silico models complement experimental approaches and offer a systems-level insights into host-microbe dynamics, helping to identify new therapeutic targets.
I will also highlight current limitations and open challenges in applying computational approaches to allergic diseases, and explore future directions in advancing clinically actionable, personalised medicine for allergic diseases.
