Optimising the use of real world data to drive effective outcomes
Late phase research is undergoing rapid transformation due to the impact of healthcare digitalisation and the greater availability of and access to Real World Data (RWD).
How can the abundance of Real World Data (RWD) from Electronic Health Records (EHRs) enhance your late phase research studies while decreasing study costs?
Real world evidence (RWE) continues to drive healthcare and research discussions and decisions. ICON delivers Real World Intelligence®, bringing together innovative thinking and technology solutions to identify, generate, and communicate the clinical, safety and cost-effectiveness evidence that regulators, payers and providers demand.
Download our white paper, Real World Evidence Generation: The Value of Cross-Sectional Studies and Medical Chart Reviews to learn how this hybrid approach to study design can be advantageous for generating real world evidence. Get insights on the issues you need to consider to ensure that your study is planned to produce robust scientific data that can be extrapolated beyond the study population.Download whitepaper
Kathleen Mandziuk, VP of Real-World Solutions, offers her insights on the use of real world data to improve clinical trials outcomes.
Kathleen Mandziuk, VP Real World Solutions, offers insights into the importance of real-world data in clinical trials and how it can be used to inform trial recruitment.
Emily Mitchell and Kathleen Mandziuk discuss how study data has progressed in recent years and how trial teams can keep up effectively with proper data management.
As more biotech companies use RWE to support approvals, broader real-world outcomes for their products will emerge.
Study designs and real-world data sources are evolving to meet drug development needs.
The increasing availability of big data is creating a shift in the clinical research landscape, allowing researchers to make intelligent, strategic decisions based on real world evidence that is derived from the aggregation and analysis of real world data.
Cross-sectional surveys (CSS) and medical chart reviews (MCRs) are both common study designs, and each has its strengths and limitations.
Duplicate data environments, redundant data subscriptions, and siloed data access are not providing a good enough return on investment for Real World Evidence (RWE) generation.
As with every aspect of clinical research, the cost of post-market surveillance and other post approval studies is rising fast – and in some cases, exceeds projected revenues.
Based on clinical data alone, manufacturers can only speculate on a device’s cost-savings in the real world.
A new rate-limiting step has emerged in drug and device development.
The industry, intelligent data, meaning data that can be leveraged to make more informed decisions, and early planning for payer evidence generation, are integral to the solution.
Insights and lessons learned about operationalising the use of real world data.
Expert insights on the 21st Century Cures Act's relation to the expanding use of real-world evidence (RWE).
Real-world data studies play a key role in orphan and rare disease research.
A discussion on how sponsors can take advantage of technology innovations to collect, standardise and analyse real world data for more informed, strategic regulatory and reimbursement decisions.
Real world evidence (RWE) is expected to have a significant impact on how healthcare technologies and biopharmaceuticals will be developed and consumed.
A data-driven feasibility assessment can help ensure that your clinical research plan is designed to enroll the right patients, rely on the right investigators, and take place in the right countries for success.
Real world data is rapidly becoming the latest frontier for life sciences companies for supporting regulatory filings and conducting drug safety surveillance.
Veronica Guiterrez Martinez and Michael Tokar at ICON discuss the challenges of setting up MAPs and the various considerations that must be tackled for a successful programme.
Database mapping provides a tool to systematically identify and evaluate RWD sources.
As more sources of anonymized Real World Data (RWD) become available, the ability to ingest, standardize and then link the collected disparate data sets is critical to creating insightful, analytical output.
Duplicate data environments, redundant data subscriptions, and siloed data access are not providing a good enough return on investment for Real World Evidence (RWE) generation
Increasing drug development cost, the shift from volume to value-based pricing, and competition from generics and biosimilars, are forcing pharma and life science organizations are looking towards Real World Evidence (RWE) to prove the value – cost, safety, and effectiveness - of their products.
Creating a comprehensive RWE strategy demands a focus on organizing and synthesizing the many real world data (RWD) asset options that are available to life sciences companies.
Payment models and federal reforms are increasingly focused on the real world impact of treatments and devices. More regulatory guidance is being released in both the US and EU around the use of RWE to support and enhance submissions and product uptake.
Real-World Evidence (RWE) is derived from Real World Data (RWD), and early use of Real World Evidence can cut post-marketing study costs and Medical Device time-to-market.
Devices are especially good candidates for early RWE use since evidence collected in the context of actual patient care from previously approved versions or similar devices often can be used to supplement findings from clinical trials of the latest version in development.Download the case studies
Real world data such as sleep quality and quantity have clinical relevance in Alzheimer's disease, providing objective measures of sleep and activity patterns that are not subject to patient recall bias. Review the use of wearables in Alzheimer’s disease to provide objective measures of sleep and activity patterns that are not subject to patient recall bias.Read more
Late phase research is undergoing rapid transformation due to the impact of healthcare digitalisation and the greater availability of and access to Real World Data (RWD).Download whitepaper
How can the abundance of Real World Data (RWD) from Electronic Health Records (EHRs) enhance your late phase research studies while decreasing study costs?Download whitepaper