For several years, health authorities have been advocating the use of Patient-Reported Outcomes (PROs) to strengthen the value demonstration of new treatments on efficacy and cost-effectiveness. PROs reflect patients’ subjective symptoms and the impact of a disease and/or treatment on their quality-of-life and are one of four types of Clinical Outcome Assessments (COAs). Other types of COAs include observer, clinician and performance outcomes which can each be used independently or as composite measures to capture different perspectives on how patients are feeling or functioning.
Yet identifying COAs that are fit-for-purpose remains challenging. Selecting COAs for clinical trials depends on multiple parameters, including health authorities’ requirements, trial design, population of interest, targeted disease concepts and the COAs’ psychometric performance. In this webinar, we will explain how to identify the most suitable COAs for your needs to enable your endpoint strategies and ultimately de-risk trial operations as well as secure regulatory approval.
The speakers will present strategies to facilitate the selection of fit-for-purpose COAs, by defining the right questions for appropriate landscape analysis and by searching appropriate data on COAs. Mapi Research Trust has integrated information on COAs in three databases for a streamlined selection process. PROINSIGHT describes guidelines, released by health technology assessment authorities and regulatory agencies, on criteria that endpoint measurement tools should meet. PROLABELS shows COA labelling claims granted by FDA and EMA, reflecting competitors’ claims landscape and PRO success stories in the drug approval process. Finally, PROQOLID reports descriptive information on all types of COAs.
Navigating from guidelines and label claims, to COA properties, users can easily source COAs with validation data that are recommended by health agencies, and/or substantiated by their use in approved labelling claims. Using COAs that are validated for specific contexts of use helps to de-risk trial deployment, optimizes relevant data collection, and the overall endpoint strategy success thus increasing the likelihood of regulatory approval.
Key learning points
- How to search for and select COAs that are validated for specific contexts of use to improve patient outcomes and experience
- How to embed regulatory recommendations and approved labelling claims into fit-for-purpose COA selection decision-making to de-risk regulatory acceptance
- How to develop patient-centered clinical strategies by assessing COA data to minimize participant burden and measure what matters to patients
Who should attend
This webinar will appeal to academia, healthcare professionals, clinical researchers and pharmaceutical companies interested in the efficient use of COAs, building end point strategies, regulatory recommendations, and labeling claims.
Speakers
Nadine Kraft
Nadine has a decade of experience with Clinical Outcome Assessments and digital measures, including their development and validation in the context of psychological testing, and clinical research. She graduated with a M.Sc. in Psychology with a specialization in cognitive neuroscience and psychological diagnostic and completed her studies working in an international medical technology company, cognitive research and a start-up developing outcome assessments. Since more than 5 years she is part of Mapi Research Trust, initially curating evidence-based information for ePROVIDE, facilitating the choice of fit-for-purpose COAs. In her role as a Team Lead of ePROVIDE Databases, she supports the efficient and scientific sound extraction of COA descriptions, COA labelling claims and regulatory recommendations.
Tilly Stott
Tilly works as a Research Associate at Mapi Research Trust where she has been involved in curating clinical outcome assessment-related data for over four years. Alongside her work, Tilly is completing a Master of Public Health at the University of Edinburgh and is finalising her dissertation on patient-reported outcome measure development and intersectionality.