I’m pleased to announce the results of our open-source Coronavirus Drug Discovery Competition! In just 2 weeks, hundreds of developers from around the world signed up to join the fight against the novel coronavirus, using publicly available datasets and algorithms to come up with relevant solutions. The top 3 submissions, winning $3500 in prizes, stood out from the rest in terms of their algorithmic and reporting quality. In this episode, I’m going to announce each of their backgrounds, as well as dive into the various machine learning techniques they used to predict a suitable treatment for Coronavirus. The top submission identified a compound called Remdesivir as the the most promising treatment for COVID-2019, due to its high scoring inhibitory potential when docked against the Coronavirus main Protease. Remdesivir was recently shown to be effective in treating the first US patient infected with COVID-2019, but is currently undergoing clinical trials to gain FDA approval. These findings help confirm it’s potential as an effective COVID-2019 treatment. I’ll explain more in the vid, Enjoy! Winning Submissions Announcement blog-post:
Matt O’Connor (1st place):
Thomas MacDougall (2nd Place):
Tinka Vidovic (3rd Place):
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Coronavirus Drug Discovery competitors
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