Recently, it was learned that the Quantitative Engineering Biology Innovation Cross Team led by the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（SIAT was selected as the 2019 Chinese Academy of Sciences Innovation Cross Team. This is the second Chinese Academy of Sciences Cross Innovation Team selected from SIAT. The main person in charge of the team is Chenli Liu, Director of the Institute of Synthetic Biology of SIAT and Dean of Shenzhen Institute of Synthetic Biology Innovation. The main members of the team include Professor Leihan Tang of Beijing Research Center for Computing Science, professor Xionglei He of Sun Yat-sen University, professor Hepeng Zhang from Shanghai Jiaotong University, professorr Xiongfei Fu and professorr Lei Dai from SIAT.
The close cooperation of the members of the quantitative engineering biology innovation cross team will help solve fundamental and forward-looking major scientific problems, break through major common key technologies and drive application demonstrations. The integration of quantitative biology and synthetic biology can be used to address a series of major challenges facing social development, including reducing and improving the health of the population and protecting the environment, ensuring energy security, and solving agricultural applications of water, soil, and food security, etc. .
In the future, the depth of basic research on artificial life systems, especially the precise description of quantitative relationships, will largely determine the success or failure of applications. Taking clinical medical applications as an example, more in-depth research is needed on the rational design of artificial living drugs, precise quantitative control, prediction of in vivo and in vitro functions, the mechanism from genes to phenotypes, and the fate of living drugs entering the human body. The design and modification of living drugs should fully consider factors such as host cells, expression systems, gene line control, and system robustness, in order to achieve better controllability in time and space and make the treatment more targeted.