Turning decades of real-world data into more effective and sustainable access solutions for patients today and tomorrow
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Turning unique insights into better programs, stronger access, and better patient outcomes.
Whitepaper
Historically, patient assistance programs have relied on experience, local market knowledge, and retrospective evaluation to guide program design. As larger, longitudinal datasets become available, there is an opportunity to complement that expertise with data-driven predictive insights. This paper presents the first large-scale analysis of administrative data from a multi-country, multi-product oncology Patient Assistance Program (PAP) portfolio for the purpose of identifying potential predictive outcome factors.
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