Multi-Modal Molecular Analyses for Living Drugs¶
Cellular immunotherapy harnesses the power of living cells — such as genetically engineered T cells — to actively seek out, recognize, and eliminate diseased cells, making it a groundbreaking cancer treatment. One of the most advanced forms of this therapy is CAR T cell therapy, where T cells are modified to express a Chimeric Antigen Receptor (CAR) — a synthetic receptor that enhances their ability to identify and attack cancer cells. However, high costs, serious side effects, and the risk of relapse remain major challenges — highlighting the need for therapies that are precisely tailored to each patient’s unique health profile.
A unique aspect of adoptive cellular immunotherapies, such as CAR T cell therapies, is that they are "living drugs", meaning that they are themselves biological systems that continue to evolve and respond in the patient's body. Given the complexity of these therapies, tailored computational biology is essential to study such heterogeneous systems. Therefore, we apply advanced multi-modal single-cell technologies and develop computational pipelines, in order to study adoptive cellular immunotherapies. While all currently approved adoptive cellular immunotherapies are based on CAR T cells, each specific therapy has distinct characteristics. To support their study and development, we aim to provide a comprehensive resource detailing the genetic designs of CAR constructs and the vector systems used for the transfection of these CAR T cell products.
Explore the Sections¶
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Technologies
Explore the technologies we use to study living drugs — including single-cell multi-omics and integration site analysis.
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Pipelines
Access our computational best practices and analytical pipelines designed to study adoptive cellular immunotherapies.
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Resources
Find detailed explanation of the differences between CAR T therapies and a resource on CAR constructs and the vector systems.
CERTAINTY¶
In order to address current challenges in CAR T cell therapies we are part of the EU project CERTAINTY, which aims at developing a virtual twin for the treatment of cancer patients with CAR T cell therapies. This will be achieved by building on biological models and real-world data, which will be designed to mimic and predict the behavior of real patients. The virtual twin aims to support doctors and patients by offering insights that may guide decisions during treatment, contributing to a more informed approach to cancer care. Learn more about the Virtual Twin Project within the CERTAINTY consortium at: https://www.certainty-virtualtwin.eu/
Contacts and Collaborations¶
For any inquiries, suggestions, or opportunities for collaboration, please feel free to reach out to our group Who we are or write us an email: christina.kuhn@izi.fraunhofer.de
Acknowledgment¶
This work was supported by the CERTAINTY project funded by the European Union (Grant Agreement 101136379). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.