New International eHealth Neuro-Musculo-Skeletal Physiome Project

Neuro-Musculo-Skeletal Physiome, or NMS Physiome for short, officially started on January 27th, 2010. This is a VPH Internationalisation cooperation project between the European integrated project VPHOP, and the United States NIH Center for physics-based Simulation of Biological Structures, SIMBIOS.

VPHOP and SIMBIOS are two of the largest research projects worldwide developing technology for personalised, predictive, and integrative musculoskeletal medicine. These two projects are targeting the same strategic objective and developing highly complementary technologies. This unique condition creates an compelling opportunity for international collaboration, one which would dramatically increase the international impact of the work being done by the VPHOP project, and foster global cooperation on one of the grand challenges of biomedical research.

VPHOP, formed by a consortium of 19 partner institutions led by the Rizzoli Orthopaedic Institute, is developing the next generation of health technologies to fight osteoporosis. As part of this endeavour, the personalised modelling of the patient's neuro-musculo-skeletal system is essential.

SIMBIOS provides infrastructure, software, and training to help biomedical researchers understand biological form and function as they create novel drugs, synthetic tissues, medical devices, and surgical interventions. The cluster of projects connected to the SIMBIOS center is investigating a wide scale of biological structures - from molecules to organisms. Driving biological problems include RNA folding, protein folding, myosin dynamics, cardiovascular dynamics, and neuromuscular biomechanics. In particular, the team of one of the two Principal Investigators of SIMBIOS, Scott Delp, based at Stanford University, focuses on the accurate modelling of the neuro-musculo-skeletal system.

In addition to the Rizzoli Orthopedic Institute and to Stanford University, the NMS Physiome project will see the participation of Empirica, SCS, and the University of Bedfordshire, all members of the VPHOP consortium.

NMS Physiome three-years activity will revolve primarily around three objectives:

  • Integrate the community web services developed by VPHOP and SIMBIOS to make teamwork across the two projects easier.
  • Integrate the software tools, MAF and OpenSIM/FEBio, developed in the two projects in order to obtain a better collective tool chest for neuromusculoskeletal modelling.
  • Combining the latest research achievements of the two consortia to better face the grand challenges the multiscale modelling of the musculoskeletal system poses, such as the efficient multiscale modelling of the musculoskeletal system, the creation of accurate patient-specific models from clinically available data, and the development of modelling methods to cope with the probabilistic nature of the neuromotor function.

For further information, please visit:
http://www.biomedtown.org/biomed_town/nmsphysiome/

Most Popular Now

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...