Could AI come to the Rescue and accelerate a market-ready Vaccine for Coronavirus (COVID-19)?
Updated: Feb 7
By Joseph K. Hopkins
Other than to avoid exposure of the virus, there’s currently no market-ready vaccine to prevent the Coronavirus disease 2019 (COVID-19). Through the aid of both public and private funding, scientists at selected large and small drug makers (about 10 or so) are working overtime to create a treatment or vaccine that targets the infection caused by the novel Coronavirus.
Bill Gates in his February 28, 2020 “The Blog of Bill Gates” characterized the COVID-19 as a phenomenon that “behaves a lot like the once-in-a-century pathogen we’ve been worried about. I hope it’s not that bad, but we should assume that it will be until we know otherwise.” Understandably so, Gates' comments sparked debate, as opposing views believe that as with other seasonal influenza viruses, the medical community will in short order discover a treatment or vaccine to also combat the novel Coronavirus (COVID-19).
But, could AI be the intelligent computer technology that helps scientists come to the rescue and accelerate a vaccine for the Coronavirus? Another approach to this forward moving effort to eradicate this nasty Virus and future unforeseen ones is the concerted effort by academia and drug discovery companies who are now expanding budgets several times over on AI - machine learning - in a bid to reduce long drug development times and prevent costly failures.
The Special Broadcasting Service (SBS News) recently reported that researchers at South Australia’s Flinders University have been working on the first ‘turbocharged’ Australian influenza vaccine made by artificial intelligence of which is now ready to start clinical trials. An effort that’s been 20 years in the making and with the use of an intelligent computer, Associate Professor Nikolai Petrovski believes "this is the first time that a drug that wasn't invented by a human is going into a real human subject”.
Given increasing public scrutiny about the efficacy of immunizations, most people would agree that bad flu seasons like the one we appear to be experiencing have a tremendous “impact on the global health system”. ‘Turbocharged’ seems a fitting word to describe how AI is working in this instance. Professor Petrovski explains, “Obviously you have to train it or teach it. We took existing drugs that we know work, we took examples of drugs that don't work or have failed. We essentially showed all of that to the AI program called Sam and then Sam came up with its own suggestion of what might be an effective adjuvant, which we then took and tested, and sure enough, it worked”.
In closing, I am sure most the readers would agree, the current drug discovery approach influenza viruses management is very inefficient in both the amount of money and time required to make available reliable treatments and vaccines. Australian chief medical officer Professor Brendan Murphy recently said that “the complexity of drug and receptor interactions is so huge that's it's very definitely enhanced by IT systems and AI systems”. The South Australia’s Flinders University "turbocharged" flu vaccine project is one that is developing AI technology that when added to existing flu vaccines makes the treatment more effective. Frankly maybe this is the talent and mindset required to ready the engines of AI (combing through historical data) to identify drug prospects to test on humans within months and finally come to the rescue and accelerate a market-ready vaccine for Coronavirus disease 2019 (COVID-19).