Leveraging Real-World Data with AI to Enhance Comparative Effectiveness Research

Leveraging Real-World Data with AI to Enhance Comparative Effectiveness Research


How AI-enabled RWD analysis can take your Comparative Effectiveness Research to the next level

How are AI-enabled tools transforming the use of real-world data (RWD) in Comparative Effectiveness Research (CER)? Advanced analysis of diverse data sources such as electronic health records, patient registries, wearable data, and genomics reports is providing a more nuanced understanding of the patient experience. As payer and regulator demand grows, what are the key CER elements that will feed into approval, pricing and reimbursement decision-making?

Companies

Roche, Sanofi, Genentech, Bayer, Sensyne Health, Microsoft, Aetion, Flatiron Health, Tempus, Aceso RWE, AllRe, Atropos Health, Arcturis Data, Comsentimento, Cornerstone AI, CuriMeta, Deep 6 AI, Evidium, Gimli, Health Compiler, Imagine If Health, Navidence, OmicsChart, EvidentIQ, Labfront, Seer, syndena, Telemonica, Wemedoo, 3Aware


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Research methodology and objectives
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Issues and insights
The current impact of RWD and AI on CER
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Challenges of utilising RWD and AI analytics in CER
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Regulatory perspective on utilising RWD and AI analytics in CER
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Future opportunities for RWD and AI analytics in CER
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Further Reading

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