Clinical Trials Analysis and Real-world Evidence – Where is the Frontier?
In an application of the overall PhUSE theme this year, "Digital Innovation in Healthcare", this topic will provide the opportunity to share experiences on the new concepts, trends and solutions related to interoperability and technology used to support both Randomized Clinical Trials (RCT) and Real-world Data (RWD).
Randomized Clinical Trials (RCT) remain the trusted standard for assessing pharmaceutical drug and medical device safety and efficacy. RCTs use a carefully planned experimental framework to compare a proposed treatment against a control and to investigate and analyse the effect of each treatment to determine if the defined outcomes have been achieved. RCTs are structured and controlled, such as patient inclusion criteria and the documented focus or purpose of the trial, to achieve the objectives of the trial.
Digital Innovation in Healthcare, focusing on Real-world Data, collects and analyses more and more sources of data (social media, smart phones, activity trackers, electronic health records, etc.). The importance of this RWD to support advances in healthcare is becoming more evident. When important health information about patients is available to fill the knowledge gap between clinical trials and actual clinical practices, researchers have a better understanding how treatments work when applied in practice. The hope is that properly analysed RWD can provide key insights that will help drive down medical costs, as well as improve both product safety and effectiveness. Compared to the RCTs, RWD multiple data sources allow for learning beyond the focus of the study.
RWD studies are useful complements to RCTs, as they reflect the day-to-day utility of drugs, devices and other products, providing a more comprehensive view of patient response to medications, a better understanding of disease patterns, additional safety data, as well as data for economic analyses.
RWE in Pharma: Does the Emperor have Clothes? – Florent Richy, Business & Decision Life Sciences
A Flexible Approach to Multi-Source Data Imputation – How it Works and Expected Results – James Hunter, OCS Life Sciences
Why an "RWE Integrated Platform" is a Key Enabler to Realize our Ambition – Rémi Chossinand, Sanofi
Machine Learning and IOT for Medical Prevention. A View From the Tranches – Pierre Gutierrez, Dataiku
Providing the Real World Value of New Medicines – Mark Lambrecht, SAS
RWE Applications: Using Healthcare Data to Understand Population Treatment Effects of Pharmaceutical Therapies – Taylor Pressler, d-Wise
Aim for the Stars – The Use of Metadata to Manage your Clincial Data – Niels Booth, S-cubed
PhUSE Updates – Katja Glass, Bayer
Download the event brochure here.