Author:
Coroller Thibaud,Sahiner Berkman,Amatya Anup,Gossmann Alexej,Karagiannis Konstantinos,Samala Ravi K.,Santana-Quintero Luis,Solovieff Nadia,Wang Craig,Amiri-Kordestani Laleh,Cao Qian,Cha Kenny H.,Orbach Rosane Charlab,Cross Frank H.,Hu Tingting,Huang Ruihao,Kraft Jeffrey,Krusche Peter,Li Yutong,Li Zheng,Mazo Ilya,Moloney Conor,Paul Rahul,Plawinski Jason,Schnakenberg Susan,Serra Paolo,Smith Sean,Song Chi,Su Fei,Subramaniam Sajanth,Tiwari Mohit,Vechery Colin,Xiong Xin,Zarate Juan Pablo,Ziegler Jonathan,Zhu Hao,Chakravartty Arunava,Liu Qi,Ohlssen David,Petrick Nicholas,Schneider Julie A.,Walderhaug Mark,Zuber Emmanuel
Abstract
AbstractIn 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4-year scientific collaboration to find novel radiogenomics-based prognostic and predictive factors for HR+/HER2-metastatic breast cancer under a Research Collaboration Agreement. This manuscript aims to detail the guiding principles and methodology for this study. We include a discussion of internal and external clinical, genomics, imaging datasets, data processing workflows, and machine learning model development strategies. We also prospectively define our success criteria to ensure robust scientific outputs.DisclosureThis publication reflects the views of the authors and should not be construed to represent FDA’s views or policies.
Publisher
Cold Spring Harbor Laboratory
Cited by
1 articles.
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