Periodic Reporting for period 1 - ERAMET (Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines )
Reporting period: 2024-01-01 to 2025-06-30
ERAMET stands for “Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and pediatric medicines”. The project is managed by a multidisciplinary consortium made up of 17 partners located in Belgium, Norway, UK, Italy, Spain, France and the Netherlands. The ERAMET project is a collaborative initiative aimed at enhancing model-informed drug development (MIDD) for pediatric and rare diseases
ERAMET’s overall objective is to provide and implement a robust framework for the development and validation of mature modelling and simulation methods, specifically tailored to address regulatory needs in the development and assessment of orphan and pediatric medicines. It will establish a transparent ecosystem for drug development and assessment, facilitating the adoption of modelling and simulation (M&S) methods along with various data types, including real world data such as registries and electronic healthcare data.
The ecosystem is based on three pillars:
(1) A repository that serves as a hub connecting questions, data and methods.
(2) The establishment and validation of rigorous standards for data and analytical methods. These standards will cover modelling and simulation, digital twins, AI, hybrid approaches, standard statistics, and pharmacometrics, ensuring robust analysis and encompassing alternative data types and sources such as real-world data, eHealth data, registries, historical regulatory submissions, and scientific and non-clinical trials.
(3) An AI-based platform designed to automate and optimise data collection, formatting, modeling, simulation analysis, and credibility assessment processes.
The ecosystem will be applied to five distinct use cases, including pediatric extrapolation and the characterisation of drug benefit/risk across four groups of rare diseases: ataxia, transfusion-dependent hemoglobinopathies, bronchopulmonary dysplasia, and degenerative neuromuscular disorders. Each use case will be strategically designed to result in the submission and regulatory approval of at least one validated M&S tool through the EMA qualification procedure. Additionally, training sessions will be offered to familiarise regulatory assessors, drug developers, and clinical researchers with this innovative approach.
ERAMET’s overall objective is to provide and implement a robust framework for the development and validation of mature modelling and simulation methods, specifically tailored to address regulatory needs in the development and assessment of orphan and pediatric medicines. It will establish a transparent ecosystem for drug development and assessment, facilitating the adoption of modelling and simulation (M&S) methods along with various data types, including real world data such as registries and electronic healthcare data.
The ecosystem is based on three pillars:
(1) A repository that serves as a hub connecting questions, data and methods.
(2) The establishment and validation of rigorous standards for data and analytical methods. These standards will cover modelling and simulation, digital twins, AI, hybrid approaches, standard statistics, and pharmacometrics, ensuring robust analysis and encompassing alternative data types and sources such as real-world data, eHealth data, registries, historical regulatory submissions, and scientific and non-clinical trials.
(3) An AI-based platform designed to automate and optimise data collection, formatting, modeling, simulation analysis, and credibility assessment processes.
The ecosystem will be applied to five distinct use cases, including pediatric extrapolation and the characterisation of drug benefit/risk across four groups of rare diseases: ataxia, transfusion-dependent hemoglobinopathies, bronchopulmonary dysplasia, and degenerative neuromuscular disorders. Each use case will be strategically designed to result in the submission and regulatory approval of at least one validated M&S tool through the EMA qualification procedure. Additionally, training sessions will be offered to familiarise regulatory assessors, drug developers, and clinical researchers with this innovative approach.
Since its inception in January 2024, the ERAMET project has made substantial progress in building a model-informed, question-centric ecosystem to support regulatory decision-making in paediatric and rare disease drug development.
Key achievements include:
• Development of an integrated repository (WP2) that maps regulatory questions, relevant data, and analytical methods.
• Establishment of a technical platform (WP3) based on a secure research infrastucture to operationalise the question-centric approach. A novel uncertainty quantification metric has been developed.
• Development of mature model simulating ataxia-telangiectasia immune defects (WP4).
• Development of a harmonising framework for PK and/or PKPD scaling for pain medications in the paediatric population (WP5).
• Development of a drug-disease model describing the effect of chelating agents on ferritin (WP6).
Key achievements include:
• Development of an integrated repository (WP2) that maps regulatory questions, relevant data, and analytical methods.
• Establishment of a technical platform (WP3) based on a secure research infrastucture to operationalise the question-centric approach. A novel uncertainty quantification metric has been developed.
• Development of mature model simulating ataxia-telangiectasia immune defects (WP4).
• Development of a harmonising framework for PK and/or PKPD scaling for pain medications in the paediatric population (WP5).
• Development of a drug-disease model describing the effect of chelating agents on ferritin (WP6).
ERAMET is delivering advancements beyond the current state of the art in the regulatory science and drug development landscape for paediatric and rare diseases.
The project have produced:
• A repository (WP2) based on the question-centric approach that connects regulatory questions, data sources, and analytical methods, improving traceability and transparency in regulatory submissions. This enable better alignment between modelling approaches and regulatory expectations, while facilitating the integration of modelling where it has traditionally been underutilised.
• A platform (WP3) based on a secure, cloud-based research infrastructure to enable collaborative data analysis across partners, improving the speed and integrity of data handling and model sharing. Innovative model credibility assessment tools have been developed, including a novel uncertainty quantification metric.
• Computational disease modelling innovations:
• An in-silico modelling of Ataxia-Telangiectasia using the Universal Immune System Simulator (WP4).
• A harmonising framework for PK and/or PKPD scaling for pain medications in the paediatric population (WP5).
• A drug-disease model describing the effect of chelating agents on ferritin (WP6)
The project have produced:
• A repository (WP2) based on the question-centric approach that connects regulatory questions, data sources, and analytical methods, improving traceability and transparency in regulatory submissions. This enable better alignment between modelling approaches and regulatory expectations, while facilitating the integration of modelling where it has traditionally been underutilised.
• A platform (WP3) based on a secure, cloud-based research infrastructure to enable collaborative data analysis across partners, improving the speed and integrity of data handling and model sharing. Innovative model credibility assessment tools have been developed, including a novel uncertainty quantification metric.
• Computational disease modelling innovations:
• An in-silico modelling of Ataxia-Telangiectasia using the Universal Immune System Simulator (WP4).
• A harmonising framework for PK and/or PKPD scaling for pain medications in the paediatric population (WP5).
• A drug-disease model describing the effect of chelating agents on ferritin (WP6)