Replacement of animal models of cardiac arrest and resuscitation strategies using a computer simulation

Cardiac arrest may be caused by a variety of pathologies and events, causing the heart to stop pumping blood around the body and to the brain, causing loss of consciousness and cessation of breathing. Outcome may be improved significantly by the early use of cardiopulmonary resuscitation (CPR). However, the optimal combination of chest compressions and ventilation of the lungs and post-resuscitation care have not been established. Many human trials have attempted to identify the optimal CPR strategy; however the ethical constraints, time scale, the presence of confounding variables, the heterogeneity of the population and sample size present major obstacle. Similarly, many animal models fail to summarize the severity of human clinical cardiac arrest due to interspecies physiological discrepancies and lack of methodical rigour.
Computational modelling offers a novel and powerful approach to research into such inaccessible issues. In contrast to trials on animal models and humans, in-silico models of individualised patient and disease-pathology are amendable to detailed validation, assuring reproducibility and translation into human application.
The PhD student appointed, Clara Daudre-Vignier, is using and further developing the Interdisciplinary Collaboration in Systems Medicine (ICSM) simulation suite, a set of integrated, high-fidelity cardiopulmonary models, developed by Prof Hardman and his team, to:
1. describe the pathophysiological changes associated with cardiac arrest in-silico humans
2. obtain novel understanding of the pathophysiological state of cardiac arrest
3. develop and test new CPR strategies
4. investigate clinical management strategies after cardiac arrest
5. develop new intra- and post-resuscitation individualized strategies.