Prediction of human cardiotoxic QT prolongation using in-vitro multiple ion channel data and mathematical models of cardiac myocytes

使用体外多离子通道数据和心肌细胞数学模型预测人类心脏毒性 QT 延长

• 批准号: NC/K001337/1
• 负责人: Gary Mirams
• 金额: $ 22.44万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NC%2FK001337%2F1
• 关键词: Prediction; human; cardiotoxic; QT; prolongation

The ProblemThe leading cause of withdrawal of pharmaceutical drugs from the market is a disturbance to the heart's rhythm, which occurs rarely, but can cause sudden cardiac death. This is very difficult to predict, so to detect the risk of this happening, experiments are performed by pharmaceutical companies during the development of new drugs. Currently, thousands of animal tests are needed to detect the risk of these new drugs causing side effects on the heart. There are many different experiments, including tests on tissues removed from animals, and later on, studies on conscious animals. A major problem is that these animal experiments give accurate predictions of what will happen in humans in only around 70% of cases.BackgroundThe reason drugs can cause side effects on the heart is that the heart's activity depends on the flow of electrically charged particles - known as ions - in and out of heart muscle cells through channels made of proteins. These ion channels can be blocked by pharmaceutical drugs, and this can cause unwanted disturbances to the heart's rhythm, called arrhythmias. Recent innovations in cell line technologies mean that pharmaceutical companies can now detect to what extent a drug blocks an ion channel as a matter of routine, without using animal experiments. By repeating these experiments for many different ion channels we can screen all of the susceptible ion channels in the heart, and measure the amount of ion channel blocking that occurs as we increase the drug dose.Our ProjectIn this project, we will perform these ion channel screens and use the results to feed into mathematical models for the electrical activity of the heart. We will simulate the effect of a drug on a single heart cell, and then the whole heart, predicting whether a set of drugs will cause harmful side effects. To evaluate our success we will compare our predictions with the results of human clinical trials.BenefitsThese computer simulations are very fast and cheap in comparison with animal experiments, enabling a risk assessment to be performed for more drugs, earlier in development. Since animal experiments are not perfect predictors of the results of human trials we may also be able to improve on their results by using mathematical models of human cells. In doing so, we aim to reduce and replace the current use of animal experiments in assessing drug-induced risks to the heart with computer simulations, and also to make more accurate predictions of what will happen when the drug is given to people.

问题药品从市场上撤出的主要原因是心律失常，这种情况很少发生，但可能导致心脏性猝死。这是很难预测的，所以为了检测这种情况发生的风险，制药公司在新药开发过程中进行了实验。目前，需要进行数千次动物试验来检测这些新药对心脏产生副作用的风险。有许多不同的实验，包括对动物组织的测试，以及后来对有意识的动物的研究。一个主要的问题是，这些动物实验只能在大约70%的情况下准确预测人类的情况。背景药物对心脏产生副作用的原因是心脏的活动依赖于带电粒子（即离子）通过蛋白质通道进出心肌细胞。这些离子通道可以被药物阻断，这可能会导致不必要的干扰心脏的节奏，称为心律失常。细胞系技术的最新创新意味着制药公司现在可以检测药物阻断离子通道的程度，而不需要使用动物实验。通过对许多不同的离子通道重复这些实验，我们可以筛选出心脏中所有敏感的离子通道，并测量随着药物剂量的增加而发生的离子通道阻断量。我们的项目在这个项目中，我们将进行这些离子通道筛选，并将结果输入心脏电活动的数学模型。我们将模拟药物对单个心脏细胞的影响，然后是整个心脏，预测一组药物是否会引起有害的副作用。为了评估我们的成功，我们将我们的预测与人体临床试验的结果进行比较。优点与动物实验相比，这些计算机模拟非常快速和便宜，使更多药物的风险评估能够在开发早期进行。由于动物实验并不能完美地预测人体实验的结果，我们也可以通过使用人体细胞的数学模型来改进它们的结果。在这样做的过程中，我们的目标是减少和取代目前使用的动物实验，以评估药物引起的心脏风险与计算机模拟，并作出更准确的预测会发生什么时，药物给人。