Social media mining in drug development-Fundamentals and use cases

Jonathan Koss; Astrid Rheinlaender; Hubert Truebel; Sabine Bohnet-Joschko

doi:10.1016/j.drudis.2021.08.012

Social media mining in drug development-Fundamentals and use cases

Drug Discov Today. 2021 Dec;26(12):2871-2880. doi: 10.1016/j.drudis.2021.08.012. Epub 2021 Sep 1.

Authors

Jonathan Koss¹, Astrid Rheinlaender², Hubert Truebel³, Sabine Bohnet-Joschko⁴

Affiliations

¹ Witten/Herdecke University, Witten, Germany. Electronic address: [email protected].
² R&D Digital Technologies, Bayer AG, Leverkusen, Germany.
³ Witten/Herdecke University, Witten, Germany; AiCuris AG, Wuppertal, Germany.
⁴ Witten/Herdecke University, Witten, Germany.

PMID: 34481080
DOI: 10.1016/j.drudis.2021.08.012

Abstract

The incorporation of patients' perspectives into drug discovery and development has become critically important from the viewpoint of accounting for modern-day business dynamics. There is a trend among patients to narrate their disease experiences on social media. The insights gained by analyzing the data pertaining to such social-media posts could be leveraged to support patient-centered drug development. Manual analysis of these data is nearly impossible, but artificial intelligence enables automated and cost-effective processing, also referred as social media mining (SMM). This paper discusses the fundamental SMM methods along with several relevant drug-development use cases.

Keywords: Innovation; Machine learning; Patient-centered drug development, digital phenotype; Research and development; Social media mining.

Publication types

Review

MeSH terms

Artificial Intelligence
Data Mining / methods*
Drug Development / methods*
Drug Discovery / methods
Humans
Patient-Centered Care
Social Media*