In silico human-based methodologies for evaluation of drug cardiac safety and efficacy
At a glance
Co-investigator(s)
R
- Replacement
- Reduction
Contents
Application abstract
Cardiotoxicity is one of the leading causes of failure during drug development and also, more worrying, after marketing approval. Withdrawal due to cardiotoxicity has increased from 5.1 to 33%, including compounds to treat cardiovascular problems as well as drugs not intended to affect the heart such as antihistamines. Current used strategy to screen for adverse contractility effects involves a combination of preclinical in vitro pharmacological profiling, cardiomyocyte assays and in vivo cardiovascular (CVS) studies, and uses a variety of animal species (rats, mice, rabbits, guinea-pigs, dogs, pigs and non-human primates).
In spite of the variety of animal methods for preclinical screening for drug safety, 20-50% of all advanced candidates have to be abandoned due to adverse outcomes, even late in the drug development process.
The main aim is to accelerate the uptake of human-based in silico methodologies for evaluation of cardiac drug safety and efficacy in industry, regulatory and clinical settings.
The specific objectives include:
1) Review, collation and implementation of a comprehensive database of human electrophysiology and contractility in silico multiscale mechanistic models for specific cardiac disease conditions.
2) Development and qualification of in silico human models for the prediction of adverse outcomes in human cardiac electrophysiology and contractility for specific disease conditions, based on existing models, and calibration with in vivo and ex situ recordings.
3) Evaluation studies to compare in silico human-based predictions to clinical outcomes, current animal methods, and in vitro methods including stem cell derived cardiomyocytes.
4) Workshops and dissemination activities to identify and overcome barriers for the uptake of in silico methods in industrial, clinical and regulatory settings.
Project membership involves key partners across 11 countries who will raise the profile of in silico human models for the 3Rs.
Impacts
Publications
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- Lyon A et al. (2018). Distinct ECG Phenotypes Identified in Hypertrophic Cardiomyopathy Using Machine Learning Associate With Arrhythmic Risk Markers. Frontiers in Physiology 9:213. doi: 10.3389/fphys.2018.00213
- Lyon A et al. (2018). Electrocardiogram phenotypes in hypertrophic cardiomyopathy caused by distinct mechanisms: apico-basal repolarization gradients vs. Purkinje-myocardial coupling abnormalities. EP Europace 20(3):102–112. doi: 10.1093/europace/euy226
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- Paci M et al. (2017). Phenotypic variability in LQT3 human induced pluripotent stem cell-derived cardiomyocytes and their response to antiarrhythmic pharmacologic therapy: An in silico approach. Heart Rhythm 14:1704. doi: 10.1016/j.hrthm.2017.07.026
- Passini E et al. (2017). Human in silico drug trials demonstrate higher accuracy than animal models in predicting clinical pro-arrhythmic cardiotoxicity. Frontiers in Physiology 8:668. doi: 10.3389/fphys.2017.00668
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- Tomek J et al. (2017). β-Adrenergic receptor stimulation inhibits proarrhythmic alternans in postinfarction border zone cardiomyocytes: a computational analysis. American journal of physiology. Heart and circulatory physiology 313(2):H338-H353. doi: 10.1152/ajpheart.00094.2017
- Tixier E et al. (2017). Modelling variability in cardiac electrophysiology: a moment-matching approach. Journal of the Royal Society, Interface 14(133). doi: 10.1098/rsif.2017.0238
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