Cellular and ionic causes of variability in the electrophysiological activity of hearts from individuals of the same species are unknown. However, improved understanding of this variability is key to enable prediction of the response of specific hearts to disease and therapies. Limitations of current mathematical modeling and experimental techniques hamper our ability to provide insight into variability. Here, we describe a methodology to unravel the ionic determinants of intersubject variability exhibited in experimental recordings, based on the construction and calibration of populations of models. We illustrate the methodology through its application to rabbit Purkinje preparations, because of their importance in arrhythmias and safety pharmacology assessment. We consider a set of equations describing the biophysical processes underlying rabbit Purkinje electrophysiology, and we construct a population of over 10,000 models by randomly assigning specific parameter values corresponding to ionic current conductances and kinetics. We calibrate the model population by closely comparing simulation output and experimental recordings at three pacing frequencies. We show that 213 of the 10,000 candidate models are fully consistent with the experimental dataset. Ionic properties in the 213 models cover a wide range of values, including differences up to ±100% in several conductances. Partial correlation analysis shows that particular combinations of ionic properties determine the precise shape, amplitude, and rate dependence of specific action potentials. Finally, we demonstrate that the population of models calibrated using data obtained under physiological conditions quantitatively predicts the action potential duration prolongation caused by exposure to four concentrations of the potassium channel blocker dofetilide.cardiac electrophysiology | computational biology | mathematical modeling | systems biology | drug B iological variability is exhibited at all levels in all organs of living organisms. It manifests itself as differences in physiological function between individuals of the same species and often more drastically by significant differences in the outcome of their exposure to pathological conditions. Thus, healthy cardiac cells of the same species and location exhibit a qualitatively similar response to a stimulus, i.e., the action potential (AP). However, significant quantitative intersubject differences exist in AP morphology and duration, which may explain the different individual response of each of the cells (and patients) to disease or drug action.The variability underlying the physiological and pathological responses of different individuals has often been ignored in experimental and theoretical research, ultimately hampering the extrapolation of results to a population level. Experimentalists often average the results obtained in different preparations to reduce experimental error, therefore also averaging out the effects of intersubject variation and resulting in an important loss of information. T...

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na+ and Ca2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

beta-Adrenergic challenges trigger TdP in a reproducible manner in this model of drug-induced LQT1. Paradoxical prolongation and increased temporal and spatial dispersion of repolarization precipitate TdP. Incremental LV systolic aftercontractions precede TdP, suggesting abnormal cellular Ca(2+) handling contributes to the arrhythmogenic mechanism.

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Background and purpose: The regulatory guidelines (ICHS7B) recommending inhibition of the delayed rectifier K þ current (I Kr ), carried by human ether-a-go-go-related gene (hERG) channels in cardiac cells (the hERG test), as a 'first line' test for identifying compounds inducing QT prolongation, have limitations, some of which are outlined here. Experimental approach: hERG current was measured in HEK293 cells, stably transfected with hERG channels; action potential duration (APD) and arrhythmogenic effects were measured in isolated Purkinje fibres and perfused hearts from rabbits. Key results: 576 compounds were screened in the hERG test: 58% were identified as hERG inhibitors, 39% had no effect and 3% were classified as stimulators. Of the hERG inhibitors, 92 were tested in the APD assay: 55.4% of these prolonged APD, 28.3% had no effect and 16.3% shortened APD. Of the 70 compounds without effect on hERG channels, 54.3% did not affect APD, 25.7% prolonged, while 20% significantly shortened APD. Dofetilide (hERG inhibitor; IC 50 , 29 nM) prolonged QT and elicited early after-depolarizations and/or torsade de pointes (TdP) in isolated hearts. Mallotoxin and NS1643 (hERG current stimulators at 3 mM), levcromakalim and nicorandil (no effect on hERG current), all significantly shortened APD and QT, and elicited ventricular fibrillation (VF) in isolated hearts. Conclusion and implications:The hERG assay alone did not adequately identify drugs inducing QT prolongation. It is also important to detect drug-induced QT shortening, as this effect is associated with a potential risk for ventricular tachycardia and VF, the latter being invariably fatal, whereas TdP has an B15-25% incidence of death.

Our data suggest that iCEB (QT/QRS) is a simple but effective ECG surrogate of cardiac wavelength. iCEB is increased in situations that predispose to TdP and is decreased in situations that predispose to non-TdP mediated VT/VF. Therefore, iCEB might serve as a noninvasive and readily measurable marker to detect increased arrhythmic risk.

Key pointsRespiratory distress is a common presenting feature among newborn infants.Prompt investigation to ascertain the underlying diagnosis and appropriate subsequent management is important to improve outcomes.Many of the underlying causes of respiratory distress in a newborn are unique to this age group.A chest radiograph is crucial to assist in diagnosis of an underlying cause.Educational aimsTo inform readers of the common respiratory problems encountered in neonatology and the evidence-based management of these conditions.To enable readers to develop a framework for diagnosis of an infant with respiratory distress.The first hours and days of life are of crucial importance for the newborn infant as the infant adapts to the extra-uterine environment. The newborn infant is vulnerable to a range of respiratory diseases, many unique to this period of early life as the developing fluid-filled fetal lungs adapt to the extrauterine environment. The clinical signs of respiratory distress are important to recognise and further investigate, to identify the underlying cause. The epidemiology, diagnostic features and management of common neonatal respiratory conditions are covered in this review article aimed at all healthcare professionals who come into contact with newborn infants.

Defining an appropriate and efficient assessment of drug‐induced corrected QT interval (QTc) prolongation (a surrogate marker of torsades de pointes arrhythmia) remains a concern of drug developers and regulators worldwide. In use for over 15 years, the nonclinical International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) S7B and clinical ICH E14 guidances describe three core assays (S7B: in vitro hERG current & in vivo QTc studies; E14: thorough QT study) that are used to assess the potential of drugs to cause delayed ventricular repolarization. Incorporating these assays during nonclinical or human testing of novel compounds has led to a low prevalence of QTc‐prolonging drugs in clinical trials and no new drugs having been removed from the marketplace due to unexpected QTc prolongation. Despite this success, nonclinical evaluations of delayed repolarization still minimally influence ICH E14‐based strategies for assessing clinical QTc prolongation and defining proarrhythmic risk. In particular, the value of ICH S7B‐based “double‐negative” nonclinical findings (low risk for hERG block and in vivo QTc prolongation at relevant clinical exposures) is underappreciated. These nonclinical data have additional value in assessing the risk of clinical QTc prolongation when clinical evaluations are limited by heart rate changes, low drug exposures, or high‐dose safety considerations. The time has come to meaningfully merge nonclinical and clinical data to enable a more comprehensive, but flexible, clinical risk assessment strategy for QTc monitoring discussed in updated ICH E14 Questions and Answers. Implementing a fully integrated nonclinical/clinical risk assessment for compounds with double‐negative nonclinical findings in the context of a low prevalence of clinical QTc prolongation would relieve the burden of unnecessary clinical QTc studies and streamline drug development.