Methodology for Good Machine Learning with Multi‐Omics Data

Author:

Coroller Thibaud1ORCID,Sahiner Berkman2ORCID,Amatya Anup3,Gossmann Alexej2ORCID,Karagiannis Konstantinos4,Moloney Conor5,Samala Ravi K.2ORCID,Santana‐Quintero Luis4ORCID,Solovieff Nadia1,Wang Craig5ORCID,Amiri‐Kordestani Laleh3,Cao Qian2,Cha Kenny H.2ORCID,Charlab Rosane3,Cross Frank H.3,Hu Tingting2,Huang Ruihao3ORCID,Kraft Jeffrey3,Krusche Peter5,Li Yutong1,Li Zheng1,Mazo Ilya4ORCID,Paul Rahul4ORCID,Schnakenberg Susan1,Serra Paolo1,Smith Sean4ORCID,Song Chi3ORCID,Su Fei1ORCID,Tiwari Mohit3,Vechery Colin1,Xiong Xin2,Zarate Juan Pablo1,Zhu Hao3,Chakravartty Arunava1,Liu Qi3ORCID,Ohlssen David1,Petrick Nicholas2ORCID,Schneider Julie A.6ORCID,Walderhaug Mark4ORCID,Zuber Emmanuel5ORCID

Affiliation:

1. Novartis Pharmaceutical Company East Hanover New Jersey USA

2. Center for Devices and Radiological Health, U.S. Food and Drug Administration Silver Spring Maryland USA

3. Center for Drug Evaluation and Research, U.S. Food and Drug Administration Silver Spring Maryland USA

4. Center for Biologics Evaluation and Research, U.S. Food and Drug Administration Silver Spring Maryland USA

5. Novartis Pharma AG Rotkreuz Switzerland

6. Oncology Center of Excellence, U.S. Food and Drug Administration Silver Spring Maryland USA

Abstract

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4‐year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio‐genomics‐based prognostic and predictive factors for HR+/HER− metastatic breast cancer under a Research Collaboration Agreement. This collaboration has been providing valuable insights to help successfully implement future scientific projects, particularly using artificial intelligence and machine learning. This tutorial aims to provide tangible guidelines for a multi‐omics project that includes multidisciplinary expert teams, spanning across different institutions. We cover key ideas, such as “maintaining effective communication” and “following good data science practices,” followed by the four steps of exploratory projects, namely (1) plan, (2) design, (3) develop, and (4) disseminate. We break each step into smaller concepts with strategies for implementation and provide illustrations from our collaboration to further give the readers actionable guidance.

Publisher

Wiley

Subject

Pharmacology (medical),Pharmacology

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