TY - JOUR
KW - Biomarker
KW - Education
KW - Immune related adverse event - irAE
KW - Immunotherapy
KW - statistics
AU - Riyue Bao
AU - Alan Hutson
AU - Anant Madabhushi
AU - Vanessa D. Jonsson
AU - Spencer R. Rosario
AU - Jill S. Barnholtz-Sloan
AU - Elana J. Fertig
AU - Himangi Marathe
AU - Lyndsay Harris
AU - Jennifer Altreuter
AU - Qingrong Chen
AU - James Dignam
AU - Andrew J. Gentles
AU - Edgar Gonzalez-Kozlova
AU - Sacha Gnjatic
AU - Erika Kim
AU - Mark Long
AU - Martin Morgan
AU - Eytan Ruppin
AU - David Van Valen
AU - Hong Zhang
AU - Natalie Vokes
AU - Daoud Meerzaman
AU - Song Liu
AU - Eliezer M. Van Allen
AU - Yi Xing
AB - 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.
BT - Journal for ImmunoTherapy of Cancer
DA - 2024/10/01
DO - 10.1136/jitc-2024-009721
IS - 10
LA - en
N2 - 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.
PY - 2024
EP - e009721
T2 - Journal for ImmunoTherapy of Cancer
TI - Ten challenges and opportunities in computational immuno-oncology
UR - https://jitc.bmj.com/content/12/10/e009721
VL - 12
Y2 - 2025-03-07
SN - 2051-1426
ER -