This podcast is part of a special series featuring the 2022 finalist teams for the INFORMS Franz Edelman Award for Achievement in Advanced Analytics, Operations Research and Management Science, the most prestigious award for achievement in the practice of O.R. and advanced analytics. For more than four decades, the Edelman Award has recognized contributions that are transforming how we approach some of the world’s most complex problems. Finalists for the Edelman Award have contributed to a cumulative impact of more than $336 billion since the award’s inception, as well as countless other nonmonetary benefits. The winner of this year’s award will be announced at the 2022 INFORMS Business Analytics Conference, April 3-5. Joining me for this episode are Dimitris Bertsimas, professor with the MIT Sloan School of Management and Najat Khan, Chief Data Science Officer and Global Head, Research and Development Strategy & Operations with Janssen Research and Development, LLC,  to discuss the finalist entry from the team at Janssen Pharmaceutical Companies of Johnson and Johnson (Janssen). To accelerate the development of the Johnson and Johnson COVID-19 vaccine, the Research and Development Data Science team at Janssen worked with the Massachusetts Institute of Technology (MIT) to co-develop and refine a machine learning-based COVID-19 epidemiological disease spread model, building on MIT’s DELPHI scenario analysis tool, capable of predicting future COVID-19 infection spread months in advance at a global level. This model enabled Johnson and Johnson to expedite a highly accurate clinical trial for the first single-dose COVID-19 vaccine, as well as gain valuable insight on virus variants.