Abstract

As the coronavirus pandemic spread from Asia to the western world, drug discovery came to a near standstill. Most laboratories shut down and instruments and reagents were left untouched, except for the most essential work. The pandemic forced large and small companies, regulatory and government agencies, and academia to tap into technology, particularly artificial intelligence (AI) and machine learning (ML), for providing more than just speed and efficiency. This essay aims to dig deeply in complexity theory to help improve safety and reduce the impact of the next pandemic. It is based on implementing Artificial Intelligence (AI) to provide the safer complex theory with an example of the current situation of COVID-19. While there are no shortcuts around scientific rigor and experimentation, AI can certainly accelerate the discovery of new drugs particularly when combined with high-performance computing (HPC) and quantum computing. Evaluating new AI technologies, particularly in areas of drug discovery where there are few demonstrations of success, can be a real challenge. It is considered that safety improvement of alert systems and the risk factors, in order to organize the safety of health facilities and control the hospital environment before the potential pandemic develops. Here, we will try to apply complexity theory in our dealing with future pandemics based on the situation analysis of previous experiences.