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Case Study: How Roche is Using NLP to Gain Patient Insights from Social Media

Situation: Patients’ social media posts are a rich source of information on the patients’ views on symptoms, treatments, outcomes and use of competitive products. They can provide valuable insights from a broad population of patients, healthcare professionals and key opinion leaders. Traditional market research techniques such as patient focus groups, interviews and questionnaires are time-consuming, expensive and limited in coverage. Roche investigated using IQVIA’s NLP-based text mining to analyze patients’ social media posts about an experimental Parkinson’s disease drug to see if they could uncover new insights about symptoms and effects on the patients’ quality of life.

Solution: Underpinning the Roche study was a conceptual Parkinson’s disease model that is a collection of symptoms and their bothersome impact on patients. Roche analyzed 24,000 documents from social media discussion threads with open queries developed using IQVIA’s Linguamatics I2E NLP platform. They focused on early Parkinson’s, i.e. before or around the time of diagnosis. Some symptoms like “voice change” were easy to detect, but others such as “tingling” were harder, as patients had many creative ways to express what they felt. The study confirmed expected symptoms, but also revealed symptoms that were previously overlooked in the scientific literature.

Success: This analysis of Parkinson’s disease patients’ social media posts showed that IQVIA’s NLP- based text mining can extract quantitative information on symptoms and their impacts on patients. As well as confirming expected symptoms, the study uncovered socially embarrassing symptoms, such as urinary urgency, that are hardly ever mentioned in clinical reports or the scientific literature. The availability of quantitative information allows the use of co-occurrence and principal components analyses to refine the symptom/impact links in the conceptual disease model. This in turn can ensure that clinical trial endpoints and drug treatments are truly addressing the most important patient needs.

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