期刊
DRUG DISCOVERY TODAY
卷 27, 期 5, 页码 1523-1530出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.drudis.2022.01.015
关键词
Social media listening; Natural language processing; Patient-centric drug discovery; Real-world data; Social media analysis; Artificial intelligence
This article reviews the latest developments in quantitative social media listening methods applied to drug discovery from the perspective of the pharmaceutical industry, discussing the need for patient-centric therapies and the importance of drawing from developments in artificial intelligence and real-world data analysis.
Social media listening has been increasingly acknowledged as a tool with applications in many stages of the drug development process. These applications were created to meet the need for patient-centric therapies that are fit-for-purpose and meaningful to patients. Such applications, however, require the leverage of new quantitative approaches and analytical methods that draw from developments in artificial intelligence and real-world data (RWD) analysis. Here, we review the state-of-the-art in quantitative social media listening (QSML) methods applied to drug discovery from the perspective of the pharmaceutical industry.
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