Using Artificial Intelligence to Predict Disease Progression
Targeting therapy transition with precise HCP and patient engagement
White Paper
May 18, 2020

A shifting paradigm: The importance of understanding a patient’s journey to a new medication

In recent years, pharma innovation has increasingly focused on developing products that meet the needs of more specific patient populations. This evolution has also changed how pharma companies interact with their customers. Fundamentally, pharma marketers want to engage customers by understanding a patient’s status, disease progression, and treatment journey.

Too frequently, outreach is ill-timed, messages aren’t relevant to the target audience, and patients don’t receive potentially beneficial information and treatments. This is the direct result of increasingly complex and intricate pathways to disease progression for niche patient populations, often measured through line of therapy transitions (LOTT) or additions.

However, these commercial challenges can be solved. Advances in artificial intelligence (AI), patient-level “big data,” and cutting-edge analytics are now helping companies deliver these relevant, timely messages to patients and their healthcare providers (HCPs). Specifically, this messages can be delievered to the HCPs most likely to observe disease progression and to be the change of therapy decision makers. AI is capable of revealing leverageable patterns and interactions that would otherwise go unnoticed, empowering pharma brands with a better, more efficient approach in an ever-escalating competitive environment.

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