THE RACE FOR ANSWERS

LONG BEFORE THE CORONAVIRUS BEGAN TO spread beyond China, infectious disease experts around the world knew there was ample reason to fear it. Not only was the pathogen highly contagious and lethal, it was also new—scientists had written no medical papers on it, doctors had no vaccines or pills to give their patients. The most effective tools we have, at the moment, are public health measures out of the 19th century such as quarantines and social distancing.

The emergence of Severe Acute Respiratory Syndrome Coronavirus 2019, or SARS-CoV-2, has made plain our vulnerability to a novel pathogen. An estimated 160 million to 214 million people in the United States could be infected over the course of the epidemic, by some estimates. Fatalities could run from 200,000 to 1.7 million people, according to the CDC, and into the tens of millions worldwide.

The lack of treatments is a startling contrast to the sophistication of current medical science, which is in something of a golden age of genomics, machine learning and big data. The coronavirus has caught us flat-footed. Yet, at the same time, it has underscored how far the tools of medicine have evolved in recent years. Just days after local infectious disease experts sent virus samples taken from two patients infected with a suspicious form of pneumonia to the Wuhan Institute of Virology, a world-renowned research laboratory, for analysis, scientists had sequenced the newly emergent pathogen’s RNA and uploaded its entire 30,000-nucleotide genetic code to the cloud.

Across the globe, scientists downloaded it and then began to isolate antibodies. Virologists and computational biologists used machine learning tools to analyze its structure and search for existing drugs that might work against it. Pathologists applied the tools of molecular biology to search for vulnerabilities