Machine Learning for Clinical Trials in the Era of COVID-19
STATISTICS IN BIOPHARMACEUTICAL RESEARCH(2020)
Abstract
The world is in the midst of a pandemic. We still know little about the disease COVID-19 or about the virus (SARS-CoV-2) that causes it. We do not have a vaccine or a treatment (aside from managing symptoms). We do not know if recovery from COVID-19 produces immunity, and if so for how long, hence we do not know if "herd immunity" will eventually reduce the risk or if a successful vaccine can be developed-and this knowledge may be a long time coming. In the meantime, the COVID-19 pandemic is presenting enormous challenges to medical research, and to clinical trials in particular. This article identifies some of those challenges and suggests ways in which machine learning (ML) can help in response to those challenges. We identify three areas of challenge: ongoing clinical trials for non-COVID-19 drugs, clinical trials for repurposing drugs to treat COVID-19, and clinical trials for new drugs to treat COVID-19. Within each of these areas, we identify aspects for which we believe ML can provide invaluable assistance.
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Key words
Clinical trials,COVID-19,Machine learning,SARS-CoV-2,The novel SARS-CoV-2 virus and COVID-19,the disease it causes,have changed the whole world,We are facing a global health crisis-characterized as a pandemic by the World Health Organization (WHO)-unlike any in recent history,The international scientific community is struggling to understand both the virus and the disease,This requires efforts at an unprecedented level of international focus and cooperation to preserve clinical trial integrity during the pandemic,to develop and to identify treatments,and to find out under what conditions they are safe and effective
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