TAILSPIN - Translation of inotropic and lusitropic drug effects from rats to humans based on comprehensive in silico models.

背景：心血管药物不良反应的后期检测是药物开发中的一个主要问题，只有通过提高临床前安全性药理学研究的预测准确性才能解决这一问题。药物监管机构要求评估药物对血压和几个电生理终点的影响。然而，最近的研究表明，评估药物对心脏收缩性和舒张性的影响，即肌力和松弛性药物的影响，同样重要，因为增加/减少收缩性和舒张受损对患者都是有害的。它们的评估通常基于左心室压（LVP）记录的终点，有意识的遥测大鼠是一种流行的动物模型，因为大鼠和人类心脏的兴奋、收缩和松弛有许多相似之处。然而，形态和功能上的差异阻碍了肌力和弹力药物效应从大鼠向人类的转化。目标和方法：该计划的总体目标是开发一种计算方法，以改善从大鼠到人类的肌力和肌力药物效应的转化。这将通过处理四个具体目标来实现。首先，我将建立、校准和验证计算机模型（模拟器），模拟大鼠和人类在给药前后的心室电力学和血流动力学。其次，我将训练和验证高斯过程回归模型（模拟器），快速模拟由大鼠和人类模拟器提供的LVP生物标志物数据。第三，我将对模拟数据进行全局敏感性分析，以量化潜在药物靶点对大鼠和人类LVP生物标志物的影响。第四，我将创建并验证一种翻译策略，该策略基于大鼠模拟器和实验大鼠LVP生物标志物数据，反向识别药物在心血管系统中的作用，然后使用这些信息作为人类模拟器的输入，预测LVP生物标志物药物在人类中的作用。意义：该项目的成功完成不仅将揭示用于评估人类肌力和肌力性药物效应的有意识遥测大鼠模型的优势和局限性，而且还将通过创新的计算方法克服现有的局限性。这将有助于在药物开发的临床前阶段发现不良的肌力和肌力效应。

Background: The late detection of adverse cardiovascular drug effects is a major concern in drug development which can only be tackled by increasing the prediction accuracy of preclinical safety pharmacology studies. Drug regulatory bodies require the evaluation of drug effects on blood pressure and several electrophysiological endpoints. However, recent research has suggested that the evaluation of drug effects on the heart´s contractility and relaxation, referred to as inotropic and lusitropic drug effects, is just as important since both increasing/ decreasing contractility and impaired relaxation can be harmful to patients. Their evaluation is commonly based on endpoints in left ventricular pressure (LVP) recordings and the conscious telemetered rat is a popular animal model because excitation, contraction, and relaxation in rat and human hearts share many similarities. However, morphological and functional differences exist that hamper the translation of inotropic and lusitropic drug effects from rats to humans. Objectives and Methodology: The overall objective of the proposed project is to develop a computational approach that improves the translation of inotropic and lusitropic drug effects from rats to humans. This will be achieved by addressing four specific objectives. Firstly, I will build, calibrate, and validate in silico models (simulators) that simulate rat and human ventricular electromechanics and haemodynamics before and after drug administration. Secondly, I will train and validate Gaussian process regression models (emulators) that rapidly emulate LVP biomarker data provided by the rat and human simulators. Thirdly, I will perform global sensitivity analyses on emulated data to quantify the impact of potential drug targets on the LVP biomarkers in both rats and humans. Fourthly, I will create and validate a translation strategy that identifies inversely, based on the rat emulator and experimental rat LVP biomarker data, how the drug acts in the cardiovascular system and then uses these information as input for the human emulator to predict LVP biomarker drug effects in humans.Significance: The successful completion of the proposed project will not only shed light on the strengths and limitations of the conscious telemetered rat model for the evaluation of inotropic and lusitropic drug effects in humans but will also overcome the existing limitations by an innovative computational approach. This will help to detect adverse inotropic and lusitropic effects already in the preclinical phase of drug development.