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- W4387572091 abstract "Patients' increasing digital participation provides an opportunity to pursue patient-centric research and drug development by understanding their needs. Social media has proven to be one of the most useful data sources when it comes to understanding a company's potential audience to drive more targeted impact. Navigating through an ocean of information is a tedious task where techniques such as artificial intelligence and text analytics have proven effective in identifying relevant posts for healthcare business questions. Here, we present an enterprise-ready, scalable solution demonstrating the feasibility and utility of social media-based patient experience data for use in research and development through capturing and assessing patient experiences and expectations on disease, treatment options, and unmet needs while creating a playbook for roll-out to other indications and therapeutic areas." @default.
- W4387572091 created "2023-10-13" @default.
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- W4387572091 date "2023-10-12" @default.
- W4387572091 modified "2023-10-13" @default.
- W4387572091 title "Artificial intelligence-driven approach for patient-focused drug development" @default.
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- W4387572091 doi "https://doi.org/10.3389/frai.2023.1237124" @default.
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