Real world big data for clinical research and drug development

Area of Science:

• Biopharmaceutical Research
• Public Health Informatics
• Data Science in Medicine

Background:

• Real-world data (RWD) offers a valuable resource for advancing drug development and understanding disease.
• Current utilization of RWD in biopharmaceuticals is nascent, with broader application in public health.

Purpose of the Study:

• To assess the current and potential large-scale utilization of RWD in drug development.
• To identify specific applications of RWD in areas such as biomarker discovery, disease understanding, and pharmacovigilance.

Main Methods:

• Systematic screening of peer-reviewed literature to identify studies utilizing RWD.
• Analysis of cited examples for applications in various stages of drug development and public health.

Main Results:

• RWD is being used for biomarker discovery/validation, disease association studies, patient stratification, and pharmacovigilance.
• The majority of current RWD applications are in public health, focusing on early, rare, or novel disease incidents.
• Few studies focused on novel targets or indications within the biopharmaceutical sector.

Conclusions:

• RWD provides insights for novel, faster, and less invasive approaches to disease understanding and biomarker discovery.
• The biopharmaceutical sector needs to increase investment in Electronic Health Records and foster precompetitive collaboration to scale RWD utilization.
• Enhanced use of RWD is crucial for the advancement of precision medicine research.