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Epitopes.world taps AI to predict COVID-19 vaccine success

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A team of researchers hailing from Harvard and Université de Montréal today launched Epitopes.world, It's built atop an algorithm -- CAMAP -- that generates predictions for potential vaccine targets, enabling researchers to identify which parts of the virus are more likely to be exposed at the surface (epitopes) of infected cells. Project lead Dr. Tariq Daouda, who worked alongside doctorates in machine learning, immunobiologists, and bioinformaticians to build Epitopes.world, Fewer than 12% of all drugs entering clinical trials end up in pharmacies, and it takes at least 10 years for medicines to complete the journey from discovery to the marketplace. Clinical trials alone take six to seven years, on average, putting the cost of R&D at roughly $2.6 billion, according to the Pharmaceutical Research and Manufacturers of America.


Jean-Francois "JF" Gagné, the CEO of Element AI on the role automation and AI will play in the…

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Jean-Francois Gagne is the CEO of Elemental AI, a Montreal-based startup which develops artificial intelligence solutions for all kinds of businesses. Elemental operates in a tough market with serious competition from tech giants such as Amazon, Google, and Microsoft. Yet thanks to its innovative training technique, which harnesses simulated data, it has created a unique proposition that has attracted an impressive roster of blue chip customers. Here Jean-Francois calls for a re-think on the assumptions built into the economic equation of international trade as well explaining why he thinks people will collaborate with machines to create new value. Elemental is a partner of the Global AI Summit, an event which will be hosted by Tortoise on May 15th 2020, that will examine the future of the world and look in depth at the role technology, and AI in particular, will play in shaping it.


UN, WHO & Mila Map the AI vs COVID-19 Battlefield

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Despite attempts to contain COVID-19 spread, as of March 26 more than 530,000 people had been infected worldwide and the number of new cases continues to grow at an alarming rate. AI tools have already joined the fight, guiding UAVs to automatically disinfect public areas, tracking disease spread vectors, diagnosing patients, etc. A new project from researchers with the UN Global Pulse Data Science Team, the World Health Organization and the Mila – Quebec AI Institute looks at current studies and programs that are using AI to tackle the COVID-19 crisis and suggests some promising future research directions. The team categorizes the AI applications in three areas; medical, which includes individual patient diagnosis and treatment; molecular, comprising drug discovery-related research; and societal. Most clinical applications of AI during the COVID-19 pandemic response have been in medical imaging diagnosis, amid growing interest in using medical imaging for screening and diagnosis.