The platform utilizes advanced computational models, artificial intelligence (AI) and machine learning (ML) technologies, as well as automated control systems to optimize biosynthesis processes and increase production efficiency. The platform is designed to achieve a high degree of optimization and intelligent management of biomanufacturing processes through precise control and real-time data analysis.
Key core technologies include:
1. Artificial intelligence and machine learning: Using AI and ML algorithms to analyze large-scale data, so as to predict and optimize biological reaction conditions, and achieve self-adjustment and optimization of the process.
2. Biological process modeling and simulation: Develop complex mathematical models to simulate biosynthetic pathways and cell metabolism that help us understand the effects of parameter changes on production and guide experimental design.
3. Automated bioreactor system: Integrated highly automated bioreactor, equipped with real-time monitoring and control equipment to ensure process stability and repeatability.
4. Intelligent diagnosis and predictive maintenance system: The use of sensors and online monitoring technology to collect critical operational data, health status analysis and fault prediction through intelligent algorithms, reduce downtime.
5. Optimization algorithms and decision support systems: Advanced optimization algorithms are used for decision analysis and resource allocation in the production process to maximize output and efficiency.
The core advantage of this research platform is that it can transform complex biological data into actionable information, improve the efficiency of production processes and product quality through intelligent control, and provide strong support for commercial applications in the field of synthetic biology.
Genetic and metabolic engineering research platform