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。药品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S心脏收缩和松弛的影响，即变力和促性腺激素药物作用，同样重要，因为增加/减少收缩能力和松弛功能受损都可能对患者有害。它们的评估通常基于左心室压力(LVP)记录的终点，意识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变力和促性腺激素药物作用从大鼠到人类的转化。目标和方法：拟议项目的总体目标是开发一种计算方法，以改进变力和变力药物效应从大鼠到人类的翻译。这将通过处理四个具体目标来实现。首先，我将在电子计算机模型(模拟器)中建立、校准和验证，模拟给药前后的大鼠和人的心室电机械和血流动力学。其次，我将训练和验证由大鼠和人类模拟器提供的快速模拟LVP生物标记物数据的高斯过程回归模型(仿真器)。第三，我将对模拟数据进行全球敏感性分析，以量化潜在药物靶标对大鼠和人类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生物标记物数据，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生物标记物对人类的影响。意义：拟议项目的成功完成不仅将阐明有意识的遥测大鼠模型在评估人类变力和趋性药物效果方面的优势和局限性，而且还将通过创新的计算方法克服现有的限制。这将有助于检测已经处于药物开发的临床前阶段的变力作用和变力作用。

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.