Real-World Evidence Gathering in Oncology: The Need for a Biomedical Big Data Insight-Providing Federated Network

Frontiers in Medicine

article

Tine Geldof¹  Isabelle Huys²  Walter Van Dyck¹ 

[1] Healthcare Management Centre, Vlerick Business School;Department of Pharmaceutical and Pharmacological Sciences, Research Centre for Pharmaceutical Care and Pharmaco-economics

关键词: real-world data;    real-world evidence;    oncology;    data exploring;    federated network;    common data model;   

DOI  :  10.3389/fmed.2019.00043

学科分类：社会科学、人文和艺术（综合）

来源: Frontiers

【 摘 要 】

Moving toward new adaptive pathways for the development and access to innovative medicines implies that real-world data (RWD) collected throughout the medicinal product life cycle is becoming increasingly important. Big data analytics on RWD can obtain new and powerful insights into medicines' effectiveness. However, the healthcare ecosystem still faces many sector-specific challenges that hamper the use of big data analytics delivering real world evidence (RWE). We distinguish between exploratory (ExTE) and hypotheses-evaluating (HETE) studies testing treatment effectiveness in the real world. From our experience and in the context of the four V's of data management, we show that to get meaningful results data Variety and Veracity are needed regardless of the type of study conducted. More so, for ExTE studies high data Volume is needed while for HETE studies high Velocity becomes essential. Next, we highlight what are needed within the biomedical big data ecosystem, being: (a) international data reusability; (b) real-time RWD processing information systems; and (c) longitudinal RWD. Finally, in an effort to manage the four V's whilst respecting patient privacy laws we argue for the development of an underlying federated RWD infrastructure on a common data model, capable of bringing the centrally-conducted big data analysis to the de-centrally kept biomedical data.

【 授权许可】

CC BY