1. Ten challenges and opportunities in computational immuno-oncology
- Author
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Hong Zhang, Riyue Bao, Song Liu, Mark Long, Sacha Gnjatic, Yi Xing, Elana J Fertig, Alan Hutson, Martin Morgan, Eytan Ruppin, Anant Madabhushi, Natalie Vokes, Daoud Meerzaman, Edgar Gonzalez-Kozlova, Vanessa D Jonsson, Eliezer M Van Allen, Spencer R Rosario, Jennifer Altreuter, Himangi Marathe, Jill S Barnholtz-Sloan, Lyndsay Harris, Qingrong Chen, James Dignam, Andrew J Gentles, Erika Kim, and David Van Valen
- Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation.
- Published
- 2024
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