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Development, optimisation and implementation of artificial intelligence methods for real world data analyses in regulatory decision-making and health technology assessment along the product lifecycle

Project description

DEENESFRITPL

AI-based real-world data tools for medicinal product assessment

Real-world data (RWD) is essential in supporting regulatory processes such as safety monitoring. However, evidentiary value for ulterior use cases, as in the pre-authorisation and evaluation phase of medicinal products, is limited by data variability and challenges in analysing data from different settings and sources. As such, it is essential to develop new and optimised methods for RWD analyses. The EU-funded Real4Reg project will develop AI-based data-driven methods and tools for medicinal product assessment. The project relies on highly relevant use cases from regulatory practice and across the product life cycle. Real4Reg will implement the results in existing and emerging guidelines for health regulatory authorities and health technology assessment bodies across Europe.

Objective

Real-world evidence derived from real-world data (RWD) has a promising role to inform regulatory decision-making. Based on highly relevant use cases from regulatory practice and across the product lifecycle Real4Reg develops AI-based data-driven methods and tools for the assessment of medicinal products. Findings will inform training activities on good practice examples and will be implemented in existing and emerging guidelines for both health regulatory authorities and health technology assessment (HTA) bodies across Europe. There is urgent need to enable the use and establish the value of the application of RWD across the spectrum of regulatory use cases. The use of RWD is established in regulatory processes such as safety monitoring, but evidentiary value for further use cases, especially in the pre-authorisation and evaluation phase of medicinal products, is rudimentary. The use of RWD in post-authorisation steps is constrained by data variability and by challenges in analysing data from different settings and sources. Thus, the development of new and optimised methods for RWD analyses is essential. Real4Reg addresses the challenges and opportunities of RWD analyses across different health care systems by involving multiple stakeholders to work together in a collaborative approach, also outreaching to already established European initiatives. Our consortium assembles partners with outstanding excellence in the field of RWD analyses, including experts from regulatory agencies/ HTA (BfArM, DKMA, Infarmed), academia (Fraunhofer, UEF, CSC, AU, DZNE) and patient organisations (EUpALS, EIWH). In an advisory board stakeholders provide input and guidance to the project, including patients, industry, payers, HTA bodies and healthcare professionals. The structure and approach of our project facilitates the successful implementation of the effective use of RWD in regulatory decision-making and HTA, and ultimately supports the application of better medicines for patients.

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Call for proposal

HORIZON-HLTH-2022-TOOL-11

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

BUNDESINSTITUT FUR ARZNEIMITTEL UND MEDIZINPRODUKTE
Net EU contribution
€ 1 495 828,75
Address
KURT GEORG KIESINGER ALLEE 3
53175 Bonn
Germany

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Region
Nordrhein-Westfalen Köln Bonn, Kreisfreie Stadt
Activity type
Research Organisations
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Total cost
€ 1 495 828,75

Participants (9)

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Last update: 25 November 2022

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Permalink: https://cordis.europa.eu/project/id/101095353

European Union, 2024