Abstract
INTRODUCTION: While pharmaceutical companies aim to leverage real-world data (RWD) to bridge the gap between clinical drug development and real-world patient outcomes, extant research has mainly focused on the use of social media in a post-approval safety-surveillance setting. Recent regulatory and technological developments indicate that social media may serve as a rich source to expand the evidence base to pre-approval and drug development activities. However, use cases related to drug development have been largely omitted, thereby missing some of the benefits of RWD. In addition, an applied end-to-end understanding of RWD rooted in both industry and regulations is lacking. OBJECTIVE: We aimed to investigate how social media can be used as a source of RWD to support regulatory decision making and drug development in the pharmaceutical industry. We aimed to specifically explore the data pipeline and examine how social-media derived RWD can align with regulatory guidance from the US Food and Drug Administration and industry needs. METHODS: A machine learning pipeline was developed to extract patient insights related to anticoagulants from X (Twitter) data. These findings were then analysed from an industry perspective, and complemented by interviews with professionals from a pharmaceutical company. RESULTS: The analysis reveals several use cases where RWD derived from social media can be beneficial, particularly in generating hypotheses around patient and therapeutic area needs. We also note certain limitations of social media data, particularly around inferring causality. CONCLUSIONS: Social media display considerable potential as a source of RWD for guiding efforts in pharmaceutical drug development and pre-approval settings. Although further regulatory guidance on the use of social media for RWD is needed to encourage its use, regulatory and technological developments are suggested to warrant at least exploratory uses for drug development.