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Titel:

Engineering de novo binder CAR-T cell therapies with generative AI

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Mergen, Markus; Abele, Daniela; Koleci, Naile; Schmahl Fernandez, Alba; Sugden, Maya; Holzleitner, Noah; Carr, Andreas; Rieger, Leonie; Leone, Valentina; Reichert, Maximilian; Laugwitz, Karl-Ludwig; Bassermann, Florian; Busch, Dirk H.; Grünewald, Julian; Schmidts, Andrea
Abstract:
Chimeric antigen receptor T cell (CAR-T) therapies have revolutionized cancer treatment, with six CAR-T products currently in clinical use1–4. Despite their success, high resistance rates due to antigen escape remain a major challenge5,6. In silico design of de novo binders (DNBs) has the potential to accelerate the development of new binding domains for CAR-T, possibly enabling personalized therapies for cancer resistance7,8. Here, we show that DNBs can be used for CAR-T, targeting clinically r...     »
Zeitschriftentitel:
bioRxiv
Jahr:
2024
Volltext / DOI:
doi:10.1101/2024.11.25.625151
WWW:
https://www.biorxiv.org/content/early/2024/11/25/2024.11.25.625151
Verlag / Institution:
Cold Spring Harbor Laboratory
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