Project description
Innovating drug development for paediatric and orphan diseases
Limited patient populations and ethical constraints delay access to life-saving treatments for paediatric and orphan diseases. Traditional methods struggle to provide reliable assessments of drug efficacy and safety. In this context, the EU-funded ERAMET project integrates modelling and simulation methods to establish credibility within regulatory procedures. Its transparent ecosystem connects questions, data, and methods, facilitating adoption of advanced techniques like AI and hybrid approaches. Three pillars underpin ERAMET: a versatile repository, high-quality standards for data and methods, and an AI-driven platform for automated analysis and credibility assessment. Five use-cases, spanning rare diseases like ataxia and neuromuscular disorders, demonstrate ERAMET’s potential, aiming for regulatory approval of validated tools. Training initiatives will ensure stakeholders embrace this transformative paradigm.
Objective
ERAMET will provide an integrated approach for developers and regulators’ decision-making for paediatric and orphan drugs, centred on the drug development questions. This will constitute a transparent ecosystem for drug development and assessment, that will facilitate the adoption of modelling and simulation (M&S) methods and related data types (including real word data such as registries and electronic healthcare data).
The overall objective of ERAMET is to provide and implement a framework for establishing the credibility of M&S methods and related results as sources of evidence within regulatory procedures.
The ecosystem proposed by ERAMET will be based on three pillars:
(1) A repository connecting questions, data and methods.
(2) The development and validation of high-quality standards for data and analytical methods (including M&S and hybrid approaches). These will cover computational M&S, digital twins, AI, hybrid approaches, standard statistics and pharmacometrics, as analytical methods and alternative data types and sources such as RWD, eHealth data, registries, historical regulatory submissions, scientific and (non)clinical trials).
(3) An AI-based platform that will automate and optimise the data collection, formatting and modelling and simulation analysis and implement the credibility assessment.
As part of ERAMET, the ecosystem will be applied to five use-cases including paediatric extrapolation and characterisation of drug benefit/risk in 4 groups of rare diseases, namely ataxia, transfusion dependent haemoglobinopathies, bronchopulmonary dysplasia, and degenerative neuromuscular.
Each of the use-case is planned to lead to submission and regulatory approval of at least one validated M&S tool via the EMA qualification procedure.
Training will be proposed to familiarise regulatory assessors, drug developers and clinical researchers with this new approach.
Fields of science
Keywords
Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
5000 Namur
Belgium