• First-of-its-kind targeting predicts which patients will become non-adherent in the next 30 days

• New offering leverages Swoop’s best-in-class machine learning and artificial intelligence

Swoop, the leading provider of custom direct-to-consumer (DTC) and healthcare provider (HCP) audiences for the pharmaceutical and life sciences industry, today announced the launch of Predictive AI Adherence Targeting. Having pioneered the use of machine learning (ML) and artificial intelligence (AI) in conjunction with real world data (RWD) to build privacy-safe, brand exclusive segments of ideal patient and provider populations, this first-of-its-kind targeting methodology allows healthcare advertisers to predict and precisely engage the patients who are most likely to become non-adherent within the next 30 days, as well as their associated HCPs.

“Until now, real world data targeting has focused on what has historically occurred in the healthcare ecosystem, such as a diagnosis or a prescription, rather than predict what is likely to happen in the future,” said Scott Rines, President of Swoop. “Through advanced ML and AI, this breakthrough targeting allows brands to proactively intercept patients and their HCPs at one of the most critical moments in the treatment journey: just prior to a patient becoming non-adherent.”

Marketing Technology News: With the Right Approach, AI Could Close the Gap in Digital Accessibility

As many as 50% of patients with long-term chronic conditions fail to appropriately take their medications, making non-adherence a $500-billion-per-year challenge for the healthcare industry. By applying privacy-safe ML/AI to a RWD universe of more than 300 million de-identified patient journeys with a 10-year lookback and 65 billion anonymized social determinants of health (SDOH) signals, Swoop predicts the likelihood of every patient on a therapy becoming non-adherent in the next 30 days. Brands can leverage this intelligence for timely and impactful activation targeting those most likely to become non-adherent. Examples of the precision healthcare marketers can leverage with Swoop’s Predictive AI Adherence Targeting include:

• 94% of all patients who became non-adherent in the next 30 days were accurately predicted for a type 2 diabetes drug.
• 92% of all patients who became non-adherent in the next 30 days were accurately predicted for a multiple sclerosis treatment.
• 91% of all patients who became non-adherent in the next 30 days were accurately predicted for a depression therapy.

“The end result is that patients are more likely to stay on life-improving treatments, benefiting their health and the healthcare system, while pharmaceutical and life sciences manufacturers realize improved commercial outcomes,” added Rines. “This represents just the beginning of what predictive modeling can bring to healthcare marketing, allowing brands to better understand their audience, accurately target them and optimize engagement before a real world event has even occurred.”

Swoop Predictive AI Adherence Targeting can be applied to any condition – common or rare, sensitive or non-sensitive. Swoop is HIPAA-certified, a member of the Network Advertising Initiative (NAI) and all its technology is built on a patented privacy-by-design data infrastructure.

Marketing Technology News: MarTech Interview with Shachar Orren, CMO and Co-Founder of EX.CO