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    Learn real-world evidence.

    RWD Basics

    Essentials for getting started with RWE.

    Start with the basics

    Uses in oncology

    • Trial design
    • Biomarker prioritization
    • Post marketing requirements and commitments
    • Label expansion
    Start with uses in oncology

    RWD basics

    Real-world data is different.

    The path to understanding real-world evidence starts at the point of care. Unlike data sourced from clinical trials, real-world data (RWD) are typically recorded in support of a patient’s treatment plan rather than according to a particular research protocol. This means that key insights may lie scattered across annotated radiology reports or physicians’ notes.

    Without careful effort to process and verify these data, RWD may be subject to gaps and biases, rendering the data unfit for use. To succeed with RWD, researchers must first understand the quality challenges, impacts, and what measures must be taken to assure its fitness for use in the context of their research or regulatory questions.

    These articles cover the fundamentals of where RWD comes from, how it is curated, processed and ultimately adopted for use by life science companies, regulators and other decision-making bodies throughout the oncology drug development lifecycle.

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      glossaryAsset 4 Glossary

      Key definitions

      Realizing the promise of real-world data requires alignment and consensus across many fronts, including the vocabulary of this emerging field.

      6 min read
    • Machine learning thumbnail Machine learning thumbnail

      videoAsset 7 Video

      What is machine learning's role in generating real-world data?

      Flatiron team members discuss the evolving role of machine learning and natural language processing (NLP) in real-world evidence along with appropriate applications for these technologies. Learn more about machine learning and AI.

      45 min watch
    • Endpoints Thumbnail Endpoints Thumbnail

      videoAsset 7 Video

      How are real-world endpoints derived?

      Discover how real-world endpoints are enabling new approaches and how Flatiron is partnering with regulatory and industry stakeholders to develop and evaluate them. Learn about how real-world endpoints are derived in oncology

      7 min watch
    • FDA Thumbnail FDA Thumbnail

      videoAsset 7 Video

      What's the latest FDA thinking on RWE?

      Chana Weinstock, MD, of the FDA discusses the use of real-world evidence in oncology drug approvals, the role of external control arms and how COVID-19 is impacting regulatory decision making. Watch her talk now.

      11 min watch
    • Early Adopters Thumbnail Early Adopters Thumbnail

      videoAsset 7 Video

      How early adopters are applying RWE

      Across organizations, researchers are looking to assess how RWE can support their drug development pipelines. Hear perspectives from early adopters across clinical development, regulatory and market access roles.

      57 min watch
    • HTA Thumbnail HTA Thumbnail

      videoAsset 7 Video

      An introduction to RWE for HTA and market access

      RWE is becoming a critical component of Health Technology Appraisals (HTAs) worldwide, particularly in oncology. However, questions remain about how it can be used effectively to support market access.

      57 min watch

    RWE in Oncology

    Using real-world evidence today.

    Browse related research, case studies and other resources that highlight examples of how RWE is being used today.

    Trial design

    Clinical trials can provide the most definitive and robust evidence for efficacy and safety. In 2021, the average oncology phase 3 study costs nearly 250 million dollars and takes more than 3 years to read out. Today, RWD is helping to improve trial designs decisions and accelerate drug development timelines. Read this collection to learn how researchers are using RWD to predict control arm performance, establish protocols according to the latest standards of care and more.

    • expert insightAsset 6 Article For Research Partners
      Real-world data and the case of the missing deaths

      Overall survival is a key endpoint in clinical trials. But when using RWD, how is missing data addressed?

      21 min read

    • publication summaryAsset 5 Publication Summary For Research Partners
      Emulating control arms for cancer clinical trials using RWD

      This exploratory study assessed whether EHR-derived patient cohorts can emulate the control arms of published clinical trials that supported FDA approvals of anticancer therapies across multiple tumor types.

      7 min read

    • publication summaryAsset 5 Publication Summary For Research Partners
      Comparative effectiveness with RWD?

      RWD can enhance health technology appraisals by providing population-level evaluations of cancer therapies. This enables researchers to select comparator populations and inform clinical trial design.

      8 min read

    • publication summaryAsset 5 Publication Summary For Research Partners
      How rapid adoption of IO impacted outcomes in the real world

      Real-world data is curated to track novel therapies in real-time, when registries may lag for years. This makes it possible to anticipate and design trials based on actual current outcomes.

      9 min read

    • videoAsset 7 Video For Research Partners
      Use of a clinico-genomic database (CGDB) for R&D

      Combining real-world data to genomic datasets enables discovery of new prognostic biomarkers, and provides clinical evidence within unique populations needed for trial design.

      10 min watch

    • podcastAsset 10 Podcast For Research Partners
      Racial and ethnic disparities: What can we learn from RWE?

      In this episode, we examine racial and ethnic disparities through the lens of oncology, real-world data and health policy.

      25 min listen

    • lockAsset 6 Methodology For Research Partners
      Statistical Biases in Real-World Data

      This article provides Flatiron research partners with a general overview of some of the common forms of statistical bias that can arise when working with RWD.

      10 min read

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