In response to the COVID-19 pandemic, researchers from the Massachusetts Institute of Technology have published a pair of studies in a COVID-19 special issue of the Harvard Data Science Review, freely available via open access, describing new methods for accelerating drug approvals during pandemics and for providing more accurate measures of the probabilities of success for clinical trials of vaccines and other anti-infective therapies.
"Randomized clinical trials - where patients are assigned randomly to two groups, one receiving a new treatment and the other receiving a placebo or reference treatment - are the gold standard for determining the safety and effectiveness of a treatment," says Andrew Lo, Ph.D., the study's senior author and the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management. "Only when the treatment group shows significant improvement over the control group, will regulators approve the therapy." He adds, "the current process is designed to protect the public by minimizing the chances of "false positives" (approving ineffective and unsafe therapies), and by and large, it's been very successful."