Institute for in silico Medicine
Institute for in silico Medicine
1 Projects, page 1 of 1
assignment_turned_in Project2016 - 2021Partners:IISc, Institute for in silico Medicine, Mosaiques Diagnostics AG, MOSAIQUES, Clyde Biosciences Ltd +33 partnersIISc,Institute for in silico Medicine,Mosaiques Diagnostics AG,MOSAIQUES,Clyde Biosciences Ltd,Medviso AB,M D Anderson Cancer Center,Institute for in silico Medicine,M D Anderson Cancer Center,NHS Golden Jubilee,SIEMENS PLC,University of Glasgow,Ninewells Hospital & Medical School,Medical University of Graz,University of Glasgow,Fios Genomics Ltd,Indian Institute of Science IISc,Dassault Systemes Simulia Corp,Graz University of Technology,Dassault Systemes Simulia Corp,Clyde Biosciences Ltd,Medical University of Graz,Medviso AB,UPB,University of Pittsburgh,LGC Ltd,Ansys Europe,Siemens plc (UK),NHS Greater Glasgow and Clyde,Ninewells Hospital & Medical School,ICAR,LGC,Golden Jubilee National Hospital,NHS Greater Glasgow and Clyde,ANSYS (International),University of Pittsburgh,Fios Genomics Ltd,NHS GREATER GLASGOW AND CLYDEFunder: UK Research and Innovation Project Code: EP/N014642/1Funder Contribution: 2,020,880 GBPIn the diagnosis and treatment of disease, clinicians base their decisions on understanding of the many factors that contribute to medical conditions, together with the particular circumstances of each patient. This is a "modelling" process, in which the patient's data are matched with an existing conceptual framework to guide selection of a treatment strategy based on experience. Now, after a long gestation, the world of in silico medicine is bringing sophisticated mathematics and computer simulation to this fundamental aspect of healthcare, adding to - and perhaps ultimately replacing - less structured approaches to disease representation. The in silico specialisation is now maturing into a separate engineering discipline, and is establishing sophisticated mathematical frameworks, both to describe the structures and interactions of the human body itself, and to solve the complex equations that represent the evolution of any particular biological process. So far the discipline has established excellent applications, but it has been slower to succeed in the more complex area of soft tissue behaviour, particularly across wide ranges of length scales (subcellular to organ). This EPSRC SoftMech initiative proposes to accelerate the development of multiscale soft-tissue modelling by constructing a generic mathematical multiscale framework. This will be a truly innovative step, as it will provide a common language with which all relevant materials, interactions and evolutions can be portrayed, and it will be designed from a standardised viewpoint to integrate with the totality of the work of the in silico community as a whole. In particular, it will integrate with the EPSRC MultiSim multiscale musculoskeletal simulation framework being developed by SoftMech partner Insigneo, and it will be validated in the two highest-mortality clinical areas of cardiac disease and cancer. The mathematics we will develop will have a vocabulary that is both rich and extensible, meaning that we will equip it for the majority of the known representations required but design it with an open architecture allowing others to contribute additional formulations as the need arises. It will already include novel constructions developed during the SoftMech project itself, and we will provide many detailed examples of usage drawn from our twin validation domains. The project will be seriously collaborative as we establish a strong network of interested parties across the UK. The key elements of the planned scientific advances relate to the feedback loop of the structural adaptations that cells make in response to mechanical and chemical stimuli. A major challenge is the current lack of models that operate across multiple length scales, and it is here that we will focus our developmental activities. Over recent years we have developed mathematical descriptions of the relevant mechanical properties of soft tissues (arteries, myocardium, cancer cells), and we have access to new experimental and statistical techniques (such as atomic force microscopy, MRI, DT-MRI and model selection), meaning that the resulting tools will bring much-need facilities and will be applicable across problems, including wound healing and cancer cell proliferation. The many detailed outputs of the work include, most importantly, the new mathematical framework, which will immediately enable all researchers to participate in fresh modelling activities. Beyond this our new methods of representation will simplify and extend the range of targets that can be modelled and, significantly, we will be devoting major effort to developing complex usage examples across cancer and cardiac domains. The tools will be ready for incorporation in commercial products, and our industrial partners plan extensions to their current systems. The practical results of improved modelling will be a better understanding of how our bodies work, leading to new therapies for cancer and cardiac disease.
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