Berlin 2024 – wissenschaftliches Programm
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BP: Fachverband Biologische Physik
BP 6: Bacterial Biophysics I
BP 6.4: Vortrag
Montag, 18. März 2024, 16:00–16:15, H 1028
Exploiting Spatial Dynamics to Optimize Evolution-Based Therapy Strategies in Dense Cellular Populations — Nico Appold1,2, Serhii Aif1,2, and •Kayser Jona1,2 — 1Max Planck Institute for the Science of Light, Erlangen, Germany — 2Max Planck Zentrum für Physik und Medizin, Erlangen, Germany
The ubiquitous emergence of resistant mutants in pathogenic cellular populations is one of the primary challenges for modern antibiotic or anti-cancer therapies. Despite advances in evolution-based adaptive therapies and mathematical or computational models, a gap remains in translating these findings to clinical application. Empirical investigations are particularly challenging for densely packed cellular communities, such as microbial biofilms or solid tumors, as a result of their inherently complex spatio-temporal dynamics. Addressing this, we introduce a yeast-based model system tailored for the systematic study of resistant mutant emergence and therapy failure dynamics in dense populations. This model combines the precise tracking of de novo mutant clones with an accurate control over temporally varying fitness landscapes. Applying concepts from active granular matter physics and collective growth dynamics, our research uncovers a previously unidentified mode of competitive release. We then integrate our results with a tailored reinforcement learning approach to optimize the balance between immediate efficacy and long-term control of population size. Our findings underscores the importance of integrating physical principles of population dynamics into the design of evolution-based treatment strategies.