Pandemics have the potential to shake the entire World. But these effects can be mitigated with effective, fast and efficient rollout of Vaccines. However, the making of vaccine itself is a challenge as to find out efficacy and safety data from thousands of volunteers as quickly as possible while countering fake news and misinformation. Artificial Intelligence is key in helping learn about virus and cell interactions while also showing the possibilities new variants have on efficacy. This approach has been used for drug research purposes and is very successful in understanding the relative success of a drug or virus to bind to the cell receptors and with how much affinity. By developing algorithms of cell receptors and antibodies produced among individuals in a population cohort we can compare their interaction with the spike protein and other areas of interest of SARS-COV2. Most importantly affinity of new variants to receptors and antibodies can be compared and therefore conclusions of vaccine efficacy can be made in comparison to the original strain. Furthermore, through fast-paced efficacy trials we can learn about why the vaccine did not work in some people by using Artificial intelligence to point out variations in genetic sequence of cell receptors and enzymes that may help us alter the design of the vaccine to improve efficacy along with learning about allergies by comparing cytokine and chemokine data in blood across donors. By having more informed decisions, vaccine development can be fast-tracked and help us solve the next pandemic swiftly.