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Real World Data Clinical Design Operations

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Our goal is to unleash the value of real-world data (RWD) in the era of artificial intelligence (AI) through rigorous analysis and strategic collaborations.

Real-World Data in Clinical Design and Operations

At Janssen R&D, we’re harnessing the power of diverse and rich real-world data spanning from omics, EHR, claims, imaging, labs, wearables, consumer data and more and advanced techniques such as AI/machine learning (ML) to derive insights on novel disease targets, patient journeys, real-word endpoints, external control arms, AI-augmented patient findings and matching to enhance our clinical trials, and more.

One example of our use of RWD is in developing external control arms. In 2019, we received expedited approval for an innovative medicine for the treatment of a specific cancer with limited options for patients. The U.S. Food and Drug Administration (FDA) approval relied on our use of real-world data as an external comparator arm which demonstrated clear, enhanced efficacy versus the evolving standard of care. Building upon this success, we are scaling the use of external control arms across the therapeutic areas to develop bespoke real-world data sets to serve as external control arms to enhance our evidence package for both regulatory and access purposes.

With this information at our fingertips, we provide scientists, doctors and patients with the ability to make decisions that are based on novel insights derived from a deep understanding of data. Through strategic collaborations and rigorous analysis, we are leveraging the most comprehensive data sets to ensure we understand and can help patients of all backgrounds.

RWD is being leveraged every day for a variety of other use cases aimed at developing novel insights and conducting more efficient clinical trials. Our scientists are leveraging this data to assist as they develop and validate novel clinical endpoints, discover new disease biomarkers, identify optimal sites for clinical trials, and accelerate recruitment of patients into our studies.

Data Sciences