成員：蔡岳峰 林建成

Motivation:
Since the end of last year, covid-19 has been raging worldwide. However, we don’t have a vaccine for the new virus. It usually takes at least 18 months to do research and develop a new vaccine. During the research, scientists will conduct animal and human experiments, which might cause controversy. So, if we could construct a simulated environment, we can reduce the time of experiment and the number of samples required, thus reducing the time and cost of the research and development.

Purpose:
Construct the concept of the simulated environment of animals and humans, and speculate on the required knowledge, the steps to be implemented and the effects it can bring.

Techniques or knowledges related:
Chemistry, deep learning, mathematical modeling, programming, computer-aided analysis, molecular biology, biohydrodynamics, general biology, immunology, etc.

Implementation concept:
After the vaccine is injected into the human body, we must know the flow and distribution of the vaccine to adjust the dose and body position of the vaccine we need, so we need to understand the biological organ structure ( general biology ) ; we also need to know the flow of the vaccine in the human body, so we have to learn the biohydrodynamics. While the vaccine flows around the human body, we also have to analyze the reaction between the vaccine and our human cells, so we need the assistance of immunology, molecular biology, and chemistry.
After we have a large database of vaccines and biological responses, we can use computer-aided analysis to understand the various responses. After there is a relationship between the human body and the vaccine, we start to build a mathematical model. The programming ability is needed to think about the parameters, variables, and object forms needed for modeling. This also requires the use of mathematical modeling techniques. Turning complex biological reactions into mathematical formulas, then use deep learning combined with a large amount of previous vaccine application data to fine-tune the model, and finally generate a biological model for vaccine analysis.

Conceptual results:
We hope that the model we make can be adjusted according to the conditions of different people or animals. By inputting the data from infants to the elderly, from the disabled to healthy people, from being overweight to being too thin, and from patients and pregnant women, some adjustable parameters can be input into the model we constructed, the concentration of pathogens we fight, Dosage and location, we get to know the status of the vaccine, whether it will cause discomfort or fever, and the most important thing is to analyze whether the vaccine is effective.

Benefits:
We believe that this will greatly improve the speed of vaccine development. In the development stage, the vaccine results can be predicted first. Through the fine-tuning of the simulation, we can find the most suitable dose for people with different conditions. In the experimental stage, it is expected to reduce the test time and the number of samples.