Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop.

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies. The main ideas highlighted were (i) a shift towards human-based methodologies, spurred by advances in new in silico, in vivo, in vitro, and ex vivo techniques and the increasing acknowledgement of the limitations of animal models. (ii) Computational approaches complement, expand, bridge, and integrate in vitro, in vivo, and ex vivo experimental and clinical data and methods, and as such they are an integral part of human-based methodologies in pharmacology and medicine. (iii) The effective implementation of multi- and interdisciplinary approaches, teams, and training combining and integrating computational methods with experimental and clinical approaches across academia, industry, and healthcare settings is a priority. (iv) The human-based cross-disciplinary approach requires experts in specific methodologies and domains, who also have the capacity to communicate and collaborate across disciplines and cross-sector environments. (v) This new translational domain for human-based cardiology and pharmacology requires new partnerships supported financially and institutionally across sectors. Institutional, organizational, and social barriers must be identified, understood and overcome in each specific setting

Multi-scale modelling and simulations into the mechanisms linking neuronal nitric oxide synthase and atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Its incidence is projected to rise due to population ageing and increasing prevalence of associated risk factors. AF alters, or remodels, the affected atrial tissue, promoting future occurrences of itself and increasing resistance to treatment. Mechanisms underlying AF initiation and remodelling are not well understood. Recent experimental evidence indicates that decreased levels of the neuronal isoform of Nitric Oxide Synthase (nNOS) may be related to AF onset and precede remodelling. However, the potential mechanisms cannot be easily elucidated with experiments alone. Furthermore, experiments are complicated by inter-subject variability, which is particularly important in human studies due to the wide heterogeneity of the human population. In this thesis, I use multi-scale modelling and simulations in synergy with experimental information to investigate mechanistic links between nNOS and AF at the level of ionic currents/cellular action potential/whole atria in human. First, I construct populations of models spanning experimentally-observed variability in human atrial myocytes under control conditions. Second, I use those populations of control models to identify key ionic mechanisms underpinning nNOS-mediated regulation of the cellular action potential in human atrial myocytes. I show that two of those currents â IKur and IK1 â play a key role in explaining the phenotypic shortening of the action potential observed under nNOS inhibition conditions and preceding AF-induced tissue remodelling. Finally, I build models of human whole atria and establish that this action potential shortening leads to the establishment of a vulnerable substrate, and hence is the main mechanism of pro-arrhythmia at this level. Overall, I provide a picture of nNOS-mediated mechanisms related to AF onset from ionic currents to the whole organ level. </p

Constructing human atrial electrophysiological models mimicking a patient-specific cell group - dataset

This folder contains all necessary files to reproduce the results of the Conference Paper titled "Constructing Human Atrial Electrophysiological Models Mimicking a Patient-Specific Cell Group" by Anna Muszkiewicz, Alfonso Bueno-Orovio, Xing Liu, Barbara Casadei, Blanca Rodriguez, published in Computing in Cardiology 2014, volume 41, pages 761-764. Figures were produced in Matlab (version R2013b) on Linux. Three Matlab scripts are provided (corresponding t o Figures 1, 2, and 3 in the paper). All data necessary to reproduce the figures in this thesis is also available via Blanca Rodriguez group in Computer Science Department, University of Oxford (on the group server 'Beat', under username of 'annamus', folder 'CinC2014_figures'

Constructing human atrial electrophysiological models mimicking a patient-specific cell group - dataset

This folder contains all necessary files to reproduce the results of the Conference Paper titled "Constructing Human Atrial Electrophysiological Models Mimicking a Patient-Specific Cell Group" by Anna Muszkiewicz, Alfonso Bueno-Orovio, Xing Liu, Barbara Casadei, Blanca Rodriguez, published in Computing in Cardiology 2014, volume 41, pages 761-764. Figures were produced in Matlab (version R2013b) on Linux. Three Matlab scripts are provided (corresponding t o Figures 1, 2, and 3 in the paper). All data necessary to reproduce the figures in this thesis is also available via Blanca Rodriguez group in Computer Science Department, University of Oxford (on the group server 'Beat', under username of 'annamus', folder 'CinC2014_figures'