Traditional medical research methods cannot solve modern healthcare systems problems. It is well-known by now that information technologies have revolutionized many areas of research and development. In light of these two facts, OpenSourceResearch organisation (OSRC) was created. OSRC is an open platform to explore, develop and validate new tools to conduct medical research. These innovative tools implement information technologies in medical research through multi-disciplinary research teams approach cherished by OSRC.
Our members can get involved in academic research as well as entrepreneurial creativity, leadership, and problem-solving activities. For this purpose, OSRC aims to create multidisciplinary teams to work out innovative solutions that aim to combat challenges in the healthcare sector by using advances in information technologies and artificial intelligence. OSRC is, in this context, an incubator and an accelerator of innovation in medical care, by developing new tools for medical research. These research tools include: computer simulation models, artificial intelligence in abdomen radiology, big data mining, synthetic and augmented data in addition to crowd science.
What is Computer Modelling and Simulation?
Computer Modelling and Simulation refers to the process of constructing and manipulating computer-based mathematical, graphical or algorithmic representations of real-life systems or phenomena, for the purpose of conducting computer-based simulations to study, predict or optimise the behaviour of the system(s) / phenomena under consideration. The complexities of modern biomedicine are rapidly increasing. Thus, modelling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. Computational modelling has been reliably used in traditional engineering disciplines to support product development and evaluation. The biomedical field, however, has been slower to adopt these approaches.
There are important key aims for computer simulation models. Most models aim to:
- Estimate model parameters and model boundary conditions through both quantitative and qualitative approaches
- Develop mathematical models and computer simulations to study patient journeys across entire care pathways, from the management of health in the home to acute care and specialist services
- Conduct rigorous testing and validation studies of the resulting models and simulations to demonstrate their usability and fitness for the purpose
- Maximising impact through translation from research prototypes to market-ready/user-ready products
- Develop innovative modelling techniques and simulation algorithms with the ultimate aim of supporting patient-specific mission rehearsal, training and procedure navigation
Computer simulation models also have many important applications, such as to:
- Test the effects of interventions by using blood investigations, patients reported outcome measures and daily monitoring charts combined.
- Test the drugs in the randomised trials.
- Assessing surgical outcome.
- Assessing the effect of recovery and enabling planning of early discharge.
- Detect patterns of disease deterioration.
OpenSourceResearch Computer Simulation Model Projects
An exciting new OpenSourceResearch project is planned to explore the utility of computer simulation models in the assessment of pre-operative optimisation bundle in patients with inflammatory bowel disease. This project will address a challenging research question. We know that pre-operative optimization has an impact on post-operative recovery, but proving this is difficult due to the complex nature of both the disease and the intervention. Computer simulation models can combine blood investigations, daily monitoring charts and digitally collected patient-reported outcome measures to predict the patterns of effect with and without optimization.
Another example is CRIMSON which is open-source software that was developed by the University of Michigan. The system uses computerized simulations of the patient’s own blood flow obtained with data gathered from MRI scans and hemodynamic variables. The data is then used to build a highly accurate model of the patient’s own circulatory system which can be used by surgeons to plan surgeries.
Health care research requires complex testing and the collection of accurate data to provide scientists with the information and tools necessary to provide new solutions and improve health outcomes. Computational modelling and simulation have therefore become increasingly popular in biomedical research and have found proven utility in healthcare. The increase in data sources including wearable sensors and digital medical devices will even drive the field of computer simulation models into the new arena.