课题基金 / 基金详情

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

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
负责人:
金额:
$60.61万
依托单位:
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
项目状态:
未结题
起止时间:
2024 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
ERAMET将以药物开发问题为中心,为开发人员和监管机构对儿科和孤儿药的决策提供一种综合方法。这将构成一个透明的药物开发和评估生态系统,这将促进采用建模和模拟(M&S)方法和相关数据类型(包括实际数据,如注册表和电子医疗保健数据)。ERAMET的总体目标是提供并实施一个框架,以建立M&S方法的可信度和相关结果作为监管程序中的证据来源。ERAMET提出的生态系统将基于三个支柱:(1)连接问题、数据和方法的存储库。(2)制定和验证数据和分析方法(包括M&S和混合方法)的高质量标准。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、注册、历史监管提交、科学和(非)临床试验)。(3)基于人工智能的平台,实现数据采集、格式化、建模和仿真分析的自动化和优化,并实施可信度评估。作为ERAMET的一部分,该生态系统将应用于5个用例,包括4组罕见疾病的儿科外推和药物获益/风险特征,即共济失调、输血依赖性血红蛋白病、支气管肺发育不良和退行性EMA认证程序。将提出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。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金