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In the past decade we have seen two major Ebola virus outbreaks in Africa, the Zika virus in Brazil and the current outbreak of coronavirus disease which has been named "severe acute respiratory syndrome coronavirus 2" (SARS-CoV-2). There is a strong sense of Déjà vu as the world is caught flat footed without effective treatments to administer to patients. Our team has been actively involved in several small molecule drug discovery efforts for the preceding virus outbreaks. In 2014 we used machine learning to identify 3 new molecules to test for the Ebola virus and these were subsequently shown to be active in vitro and in vivo. We have also been involved in open science approaches that leverage the community to help. In 2016 we launched the OpenZika project as an IBM World Community Grid Project that used distributed computing power of volunteers to dock large numbers of compounds into Zika and related flavivirus targets. This led us into several collaborations in which we validated computational predictions in vitro. With both of these initiatives there was some knowledge of the virus, many compounds had already been tested in the case of Ebola, whereas for Zika initially all we had was the virus RNA sequence. In the current SARS-CoV-2 outbreak, this was a completely new virus and the scientists in China and elsewhere have started from scratch. In the space of a few weeks since the outbreak is acknowledged to have started, there are now compounds suggested as active in vitro and molecules repurposed in clinical trials. While this has been impressive, we propose there may still be gaps in our approach to drug discovery for such outbreaks. There is an opportunity to repurpose additional approved drugs for this virus and we now suggest how these might be identified leveraging prior work on MERS-CoV, SARS-CoV and other viruses. We also describe some of the immense challenges and limitations of the open antiviral drug discovery approaches we have been involved in.

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