ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines

ERAMET - 快速采用建模和模拟方法的生态系统，以满足孤儿药和儿科药物开发中的监管需求

• 批准号: 10107647
• 金额: $ 60.61万
• 依托单位: UNIVERSITY COLLEGE LONDON
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10107647
• 关键词: ERAMET; Ecosystem; rapid; adoption; modelling

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, eHealthdata, 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 in4 groups of rare diseases, namely ataxia, transfusion dependent haemoglobinopathies, bronchopulmonary dysplasia, and degenerative the EMA qualification procedure. Training will be proposed to familiarise regulatory assessors, drug developers and clinical researchers with this new approach.

埃赫曼将为儿科和孤儿药的开发者和监管者提供一个综合的决策方法，以药物开发问题为中心。这将构成一个透明的药物开发和评估生态系统，促进采用建模和模拟（M&S）方法和相关数据类型（包括注册和电子医疗保健数据等真实的文字数据）。埃赫曼的总体目标是提供并实施一个框架，以建立M&S方法和相关结果作为监管程序中证据来源的可信度。埃赫曼提出的生态系统将基于三个支柱：（1）连接问题、数据和方法的知识库。(2)为数据和分析方法（包括M&S和混合方法）制定和验证高质量标准。这些将涵盖计算M&S、数字孪生、人工智能、混合方法、标准统计和药物计量学，作为分析方法和替代数据类型和来源，如RWD、电子健康数据、登记、历史监管提交、科学和（非）临床试验。(3)一个基于人工智能的平台，将自动化和优化数据收集，格式化，建模和模拟分析，并实施可信度评估。作为埃赫曼的一部分，该生态系统将应用于五个用例，包括儿科外推和4组罕见疾病的药物获益/风险表征，即共济失调、输血依赖性血红蛋白病、支气管肺发育不良和EMA认证程序中的退行性疾病。将建议进行培训，以使监管评估人员、药物开发人员和临床研究人员熟悉这种新方法。