Pardis Sabeti is a professor of computational biology, working to predict and track future infectious disease outbreaks. She explains how sharing data will help us win the war on infectious disease.
In my research, I develop algorithms that help decode the genetic blueprints of infectious microorganisms. The tools we used to fight Ebola and Lassa are in many ways the same as those we are using in the current COVID-19 pandemic. During the 2014 Ebola outbreak in West Africa, my team and I performed large-scale sequencing of Ebola’s viral genome. After publishing the genomic data in a public database, we gained the help of leading global researchers to quickly develop diagnostic testing and contact tracing. The technology is already available. Now, we need to change the process.
My Next Great Impossible is to scale up rapid diagnostic testing to detect and track future disease outbreaks using breakthrough technologies. This includes CRISPR, a unique technology used to detect any sequence of genetic material. We have helped develop a CRISPR-based viral diagnostic called SHERLOCK, which uses a simple paper strip for rapid detection. Critically, to make better use of these technologies, we have created tools to help researchers share this information with the public health community in real time.
I can honestly say that I have found my ideal job – I love looking at data, finding trends, coming up with a hypothesis, and figuring out how to pursue it. I love the hunt and relentless pursuit, all while being able to work with great people. Now, having 50 students and colleagues in the lab who are all working with a common purpose, it is a joy to be in such a vibrant environment.
Q: What kind of mindset do you need to achieve the Next Great Impossible?
A: Collaborating is one of my favorite things about this job; I have learned so much from my partnerships over the years and they have learned from my research group in return.