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The 18th FRAME Annual Lecture, October 2019: Human In Silico Trials in Pharmacology
Alternatives to Laboratory Animals ( IF 2.7 ) Pub Date : 2019-11-01 , DOI: 10.1177/0261192919896356
Blanca Rodriguez 1
Affiliation  

Safety and efficacy testing is a crucial part of the drug development process, and several different methods are used to obtain the necessary data (e.g. in vitro testing, animal trials and clinical trials). Our group has been investigating the potential of modelling and simulation as an alternative approach to some of the methods used for testing drugs for cardiac effects. To achieve our goal of developing and promoting novel approaches in drug development, we formed multidisciplinary collaborations that included clinicians, computer scientists and biologists. Our in silico models are based on human data (e.g. magnetic resonance images, electrocardiogram) and on current knowledge of human electrophysiology, thus generating predictions that are directly applicable to humans. Such models are a particularly powerful tool because they encompass different sources of population heterogeneity, which is crucial for drug testing and for assessing how interindividual variability might affect clinical endpoints. Our group has shown that computer modelling can be used to predict the effects of a test drug in a virtual population or in combination with machine learning to predict different phenotypes when a drug is given to a diseased population. Furthermore, our user-friendly drug testing software is freely available and is being adopted by industry in their drug development process. We have been engaging with industry and regulators to show that our models can contribute to the replacement of animals in drug development. Our ambition is to generate models for simulation of different diseases and therapies for investigations from subcellular to whole organ.

中文翻译:

第 18 届 FRAME 年度讲座,2019 年 10 月:药理学中的人体计算机试验

安全性和有效性测试是药物开发过程的关键部分,并且使用了几种不同的方法来获取必要的数据(例如体外测试、动物试验和临床试验)。我们小组一直在研究建模和模拟作为用于测试药物心脏效应的一些方法的替代方法的潜力。为了实现我们在药物开发中开发和推广新方法的目标,我们建立了包括临床医生、计算机科学家和生物学家在内的多学科合作。我们的计算机模型基于人类数据(例如磁共振图像、心电图)和人类电生理学的当前知识,从而生成直接适用于人类的预测。这些模型是一个特别强大的工具,因为它们包含不同来源的人群异质性,这对于药物测试和评估个体间变异性如何影响临床终点至关重要。我们的小组已经表明,计算机建模可用于预测测试药物在虚拟人群中的效果,或者与机器学习相结合来预测当药物给予患病人群时的不同表型。此外,我们的用户友好的药物测试软件是免费提供的,并且在药物开发过程中被业界采用。我们一直在与行业和监管机构合作,以表明我们的模型可以促进药物开发中动物的替代。
更新日期:2019-11-01
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