Today system simulators are used in all types of professions. Health care and nutrition professionals use system simulators to evaluate treatments for patients. More so, vaccine development requires system simulators to assess the safety and efficacy of vaccines before clinical trials. In the world of automobile design, engineers use system simulators to evaluate the fuel economy, safety and overall performance of a vehicle design before constructing a prototype. There are many more applications of system simulators. For civil engineering and environmental engineering projects, buildings are assessed for earthquake and hurricane resistance with system simulators. For factories, system simulators are used to assess the environmental impact of factory for the production of different products, Bitcoins for instance.
The use of system simulators is expected to increase in the educational system. There are several reasons why. The first reason is that system simulators are becoming easier to use. Part of a result of video gaming technology, system simulators no longer require advanced engineering knowledge to understand. During a video game structured earthquake system simulation, one can visually see that the design collapses when the magnitude of the earthquake reaches 7.6 without going through reams of data. Similarly, with a system simulator one can visually see that the race car flies off the track at speeds greater than 200 miles per hour. Cause and effect are visually identifiable.
Today the technology race is on to design system simulators that allow the consumer and the professional to easily understand cause and effect without the need to program. As an example, consumers may want to know the effect of their diet on their health and weight, short term and long term. Nutritional systems help here. One can simply drag and drop diets and different types of patients into the simulator and out comes projected weight gain or weight loss over a specific period. More so, these system simulators can project what health issues one will face with prolonged dietary and environmental stimulus.
The market for system simulations is enormous, easily $100 billion or more. Systems that allow the design of complex systems or determine cause and effect without expensive engineering efforts or in-depth knowledge is one of the driving forces. For example, a nutritionist might want to determine the best diet for a client that has chronic kidney disease, diabetes, or cancer. That’s a complex question that might well require a very accurate patient model that includes data about the patients environmental setting (temperature, humidity and PH of the water they drink) and the current status of patient health parameters (results from blood tests). In a nutritional simulator, in order to automatically create the patient model a data interface may be needed that connects to the patients medical laboratory result records or even real time medical instrumentation.
In a high school educational environment, a nutritional simulator may not need medical technology specifics. As in a game, the student can pick a diet, the patient type or condition and the simulator will determine the health outcomes from the diet over a given period of time. The model may be a statistical model, one that predicts the most probable outcome given the diet and the patient characteristics. The fact that it is a statistical model, as opposed to an exact patient-specific biomedical model is of significance. Statistical models are based on probability from the empirical results of studies. They don’t represent the specific biomedical individualized patient system. So inherently they can not be relied on in totality. They are a best guess.
A precise patient model requires an exact model of the patient’s unique medical, genetical and biochemistry characteristics as well as environmental influences. All of which today is Inherently an art because medical science has not created a model that can be used to simulate outcomes that takes into account an individuals unique biodynamics and the patients interaction with the environment.
