Engineering feedback control loops into CAR-T therapeutics
Project ID: 2531bd1618
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Research Theme: Healthcare Technologies
Research Area(s):
Engineering biology
Mathematical biology
Control engineering
UCL Lead department: Biochemical Engineering
Lead Supervisor: Darren Nesbeth
Project Summary:
Why this research is important
CAR-T immunotherapy has revolutionized cancer treatment, achieving remarkable remissions in previously untreatable blood cancers. However, serious limitations remain: severe cytokine release syndrome affects many patients, and manufacturing variability compromises product quality. This project develops “self-regulating” CAR-T cells capable of sensing their population density and automatically adjusting activity levels. By preventing dangerous overactivation while maintaining therapeutic efficacy, this innovation could substantially improve CAR-T safety profiles and manufacturing reliability.
Who you will be working with
You will join a dynamic multidisciplinary team at UCL’s Department of Biochemical Engineering and Department of Mathematics. The project brings together Dr Darren Nesbeth’s expertise in engineering biology and cell therapy bioprocessing with Professor Alexey Zaikin’s background in mathematical modeling and systems biology. This collaboration provides comprehensive support spanning experimental design, theoretical analysis, and translational applications.
What you will be doing
You will design, construct, and characterize artificial genetic circuits enabling mammalian cells to sense and respond to population density. Initial experiments establish proof-of-concept using fluorescent reporters that activate at specific cell densities. You will then engineer immortalized T cells with circuits that regulate cytotoxic function in response to crowding. Your training encompasses molecular cloning, DNA assembly, mammalian cell culture, lentiviral transduction, flow cytometry, genetic circuit design, and data analysis. You will also learn to integrate experimental results with mathematical modeling.
Who we are looking for
We seek enthusiastic candidates with strong foundations in life sciences, bioengineering, biotechnology, or related disciplines. While experience in molecular biology or mammalian cell culture is advantageous, it is not essential—we value curiosity, creativity, problem-solving ability, and enthusiasm for interdisciplinary collaboration. Strong communication skills and eagerness to work across traditional disciplinary boundaries are particularly important.