Physiology's Impact: Applying Mathematics and Advanced Technologies

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease.

The Physiome Project was officially launched in 1997 and has since brought together teams from around the world to work on the development of a computational framework for the modeling of the human body. At the European level, this effort is focused around patient-specific solutions and is known as the Virtual Physiological Human (VPH) Initiative.Such modeling is both multiscale (in space and time) and multiphysics. This, therefore, requires careful interaction and collaboration between the teams involved in the VPH/Physiome effort, if we are to produce computer models that are not only quantitative, but also integrative and predictive.In that context, several technologies and solutions are already available, developed both by groups involved in the VPH/Physiome effort, and by others. They address areas such as data handling/fusion, markup languages, model repositories, ontologies, tools (for simulation, imaging, data fitting, etc.), as well as grid, middleware, and workflow.Here, we provide an overview of resources that should be considered for inclusion in the VPH/Physiome ToolKit (i.e., the set of tools that addresses the needs and requirements of the Physiome Project and VPH Initiative) and discuss some of the challenges that we are still facing.

European funding under framework 7 (FP7) for the virtual physiological human (VPH) project has been in place now for nearly 2 years. The VPH network of excellence (NoE) is helping in the development of common standards, open-source software, freely accessible data and model repositories, and various training and dissemination activities for the project. It is also helping to coordinate the many clinically targeted projects that have been funded under the FP7 calls. An initial vision for the VPH was defined by framework 6 strategy for a European physiome (STEP) project in 2006. It is now time to assess the accomplishments of the last 2 years and update the STEP vision for the VPH. We consider the biomedical science, healthcare and information and communications technology challenges facing the project and we propose the VPH Institute as a means of sustaining the vision of VPH beyond the time frame of the NoE.

The Physiome Project's markup languages and associated tools leverage the CellML and FieldML model databases published in peer-reviewed journals. As these tools mature, researchers can check models for conformance to underlying physics laws, using them to develop complex physiological models from separately validated components

Life is the result of an intricate systemic interaction between many processes occurring at radically different spatial and temporal scales. Every day, worldwide biomedical research and clinical practice produce a huge amount of information on such processes. However, this information being highly fragmented, its integration is largely left to the human actors who find this task increasingly and ever more demanding in a context where the information available continues to increase exponentially. Investments in the Virtual Physiological Human (VPH) research are largely motivated by the need for integration in healthcare. As all health information becomes digital, the complexity of health care will continue to evolve, translating into an ever increasing pressure which will result from a growing demand in parallel to limited budgets. Hence, the best way to achieve the dream of personalised, preventive, and participative medicine at sustainable costs will be through the integration of all available data, information and knowledge.

Bioengineering analyses of physiological systems use the computational solution of physical conservation laws on anatomically detailed geometric models to understand the physiological function of intact organs in terms of the properties and behaviour of the cells and tissues within the organ. By linking behaviour in a quantitative, mathematically defined sense across multiple scales of biological organization--from proteins to cells, tissues, organs and organ systems--these methods have the potential to link patient-specific knowledge at the two ends of these spatial scales. A genetic profile linked to cardiac ion channel mutations, for example, can be interpreted in relation to body surface ECG measurements via a mathematical model of the heart and torso, which includes the spatial distribution of cardiac ion channels throughout the myocardium and the individual kinetics for each of the approximately 50 types of ion channel, exchanger or pump known to be present in the heart. Similarly, linking molecular defects such as mutations of chloride ion channels in lung epithelial cells to the integrated function of the intact lung requires models that include the detailed anatomy of the lungs, the physics of air flow, blood flow and gas exchange, together with the large deformation mechanics of breathing. Organizing this large body of knowledge into a coherent framework for modelling requires the development of ontologies, markup languages for encoding models, and web-accessible distributed databases. In this article we review the state of the field at all the relevant levels, and the tools that are being developed to tackle such complexity. Integrative physiology is central to the interpretation of genomic and proteomic data, and is becoming a highly quantitative, computer-intensive discipline.