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Fierce AI Week: Patient insights from Social Media Listening


Patient-focused drug development requires a strong integration of the patient’s voice at every step of the drug development process. Developing clinical endpoints that are meaningful to patients and that are qualified to measure a relevant change in quality of life is challenging. The patient’s perspective is traditionally investigated with scientific literature reviews, exchange with clinical experts and patient organizations, as well as interviews with patients. However, all of these methods suffer from shortcomings such as underrepresenting the direct view of the patients or representing the view of a limited number of them.  

We addressed these shortcomings by using Social Media Listening (SML) as an abundant information source to complement insights from traditional methods. Patients share their perspective not just with their clinicians, but also on social media. They talk about their symptoms and the impacts these symptoms have on their daily lives. SML strengthens the patient-centricity of the drug development process. The level of burden to the patients is significantly lower than in concept-elicitation interviews and it can reach more patients.

Social media data are highly diverse and the analysis of these data comes with significant challenges. One example is the understanding of the patient’s language and its mapping to scientific language. Given the growing amount of data available in social media, robust computational approaches have to be developed to produce meaningful insights. 

During this event, we will highlight how we integrate the patient’s voice via social media listening studies into the early part of the drug development process. We will give insights into the tasks and tools required for social media listening and how artificial intelligence and natural language processing can help to translate the patients’ voice into actionable insights.


Mathias Leddin, PhD
Mathias Leddin, PhD
Senior Data Scientist, Roche pRED

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