Events Calendar

AME Seminar

Speaker: Michaëlle N. Mayalu, Stanford University

Talk Title: Control Theoretic Applications for Biomedical Therapeutics

Abstract: The body uses feedback control strategies at intermolecular, intercellular and interorgan levels to maintain health and fight disease. Using mathematical models to understand and predict these control strategies gives insight into a wide array of biomedical applications ranging from engineered cell-based therapies to diet-based modulation of brain function.

For engineered cell-based therapies, cooperative feedback control of cell population density is an integral part in many genetic designs. In this multicellular coordination problem, control action takes place on two levels: i) individual cells can activate or repress relevant genes, ii) cells can access the ensemble state of the entire population as obtained through diffusible signaling molecules. These genetically altered cells can provide new and improved functionalities and act as smart therapies to make decisions based on intercellular communication and the environment. However, previous population controller genetic designs are not robust to mutational invasions.

For diet-based modulation of brain function, diet can initiate multiple interorgan feedback control systems that effect brain signaling and contribute to cognitive performance. Specifically, diet-mediated gut microbial signals influence nervous, immune, and bloodstream pathways which connect to memory function within the brain. It is desired to use diet to modulate gut microbiota as a novel therapy for maintaining cognitive performance. However, relationships between diet, changes in gut microbiota, activation of interorgan pathways, and alterations in brain signaling are not well understood.

In this talk I present mathematical frameworks from an integrated control theoretic, computational biology and healthcare perspective that: i) characterize genetic designs for robust feedback control of cell population and ii) elucidate the connections between diet and cognitive performance. These modeling frameworks share the underlying structure where communication between agents contribute to the prediction of a collective response. In healthcare contexts, this allows for better understanding and manipulation of the connection between therapeutic targets and dominant patterns within the biological process. Using these models, we further analyze internal mechanisms, performance properties, and derive general design principles and functional relationships in the context of the aforementioned biomedical therapies.

Biography: Michaelle N. Mayalu is an Assistant Professor of Mechanical Engineering. She received her Ph.D., M.S., and B.S., degrees in Mechanical Engineering at the Massachusetts Institute of Technology. She was a postdoctoral scholar at the California Institute of Technology in the Computing and Mathematical Sciences Department. She was a 2017 California Alliance Postdoctoral Fellowship Program recipient and a 2019 Burroughs Wellcome Fund Postdoctoral Enrichment Program award recipient.

Dr. Michaëlle N. Mayalu's area of expertise is in mathematical modeling and control theory of synthetic biological and biomedical systems. She is interested in the development of control theoretic tools for understanding, controlling, and predicting biological function at the molecular, cellular, and organismal levels to optimize therapeutic intervention.

She is the director of the Mayalu Lab whose research objective is to investigate how to optimize biomedical therapeutic designs using theoretical and computational approaches coupled with experiments. Initial project concepts include: i) theoretical and experimental design of bacterial "microrobots" for preemptive and targeted therapeutic intervention, ii) system-level multi-scale modeling of gut associated skin disorders for virtual evaluation and optimization of therapy, iii) theoretical and experimental design of "microrobotic" swarms of engineered bacteria with sophisticated centralized and decentralized control schemes to explore possible mechanisms of pattern formation. The experimental projects in the Mayalu Lab utilize established techniques borrowed from the field of synthetic biology to develop synthetic genetic circuits in E. coli to make bacterial "microrobots". Ultimately the Mayalu Lab aims to develop accurate and efficient modeling frameworks that incorporate computation, dynamical systems, and control theory that will become more widespread and impactful in the design of electro-mechanical and biological therapeutic machines.

Website: https://mayalulab22.sites.stanford.edu/

Host: AME Department

More Info: https://ame.usc.edu/seminars/

Webcast: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09

Location: Seaver Science Library (SSL) - 202

WebCast Link: https://usc.zoom.us/j/98775609685?pwd=a2lSd01oY0o2KzA4VWphbGxjWk5Qdz09

Audiences: Everyone Is Invited

Contact: Tessa Yao

Event Link: https://ame.usc.edu/seminars/