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Patient Data For Research

Patient Data For Research

"JCI is helping Janssen remain at the forefront of today’s exciting trends in harnessing big data to unearth the small differences among patients that point to new potential therapies and identify those most likely to benefit from them."

Martine Lewi, MBA, Ph.D.

Scientific Director, JCI

Mining

 

Aggregating Actionable Real-World Data (RWD)

The enormous amount of data generated by and about each one of us is growing faster than our ability to interrogate it skillfully or assess its responses. Nowhere is this more urgent than in healthcare, where troves of data hold as-yet unexamined clues to future solutions.  

The challenge is not simply of computational power and speed. The ability to assess the origins and quality of data, and the analytics to extract useful signals, are essential for the future of healthcare.  

Toward these ends, Real-World Evidence (RWE) studies apply powerful processing capabilities to mine existing health data to parse the effects of interventions on different patient populations in their real-life settings. In the changing health care ecosystem, there is a need for data which can support value-based outcomes. RWD is also important in support of early clinical development and market access.     

The potential of RWE studies is limited by challenges of acquiring RWD from different electronic health records (EHR) systems and high variability in data quality. No single organization can solve such challenges on its own. Janssen is actively participating in consortia projects like Electronic Health Records to Electronic Data Capture (EHR2EDC), a European Institute of Innovation and Technology (EIT) – funded project exploring ways to automate high-quality data capture from EHRs. Besides development of innovative solutions, there is a focus on regulatory compliance, data privacy, and change management, within both the sponsor and study investigator environments. This initiative aims at improving – in the mid-term – the operational efficiency of clinical trials by reducing the burdens of manual data entry, as well as shortening the time of data collection. These solutions are also contributing, for example, to the development of virtual registries for observational studies.  

JCI has pilot studies in progress in several disease areas, in Europe, the US, and other regions, establishing strong partnerships in cross industry collaborations where sponsors and sites are establishing best practices to optimize clinical trials through automated capture and translation of complex health data. 

 

Precision Medicine Initiative

Despite the promise of successes, the challenges of precision medicine remain daunting, with many outstanding genotype and phenotype mysteries. Still, the need persists to better predict disease risk and progression, understand disease mechanisms, and apply the most appropriate diagnostic and therapeutic strategies to maximize outcomes for patients.

JCI is collaborating in this effort both internally within Janssen and externally through public-private partnerships, such as Europe’s Innovative Medicines Initiative (IMI). Success depends, in part, on the ability to generate and access genomic and other biomarker data (omics) and integrate them with clinical, environmental, and social factors (non-omics), in search of, for example, risk factors which can help predict disease progression and responsiveness to treatments among individuals and groups.  

In parallel with the growth of these augmented real-world databases, we are also contributing to the development of machine-learning and artificial intelligence tools to generate novel medical and clinical insights.