Ebola virus and coronaviruses remain pandemic threat agents and cause serious disease in humans. Both types of viruses lead to outbreaks and pandemics that rapidly overwhelm healthcare resources and prove challenging to treat. Speeding up the development of medical countermeasures (MCMs) such as diagnostics, vaccines and anti-virals is key in preventing an outbreak becoming a pandemic. The analysis of samples, using sequencing, from human patients and animal models of these threat agents can provide a wealth of data. However, making sense of this data can often be problematic due to the many hundreds/thousands of samples and hundreds of thousands of data points. This talk will illustrate how AI/ML can be used in real world settings to understand Ebola virus disease to better evaluate therapeutic interventions and secondly predict the future evolution of SARS-CoV-2 for MCM development.