As COVID-19 continues to ravage parts of the world, global industries, including tech, healthcare and pharmaceutical, are racing to overcome the speed of the virus. However, traditional, standalone R&D efforts led by the healthcare industry can be timely and costly, giving the virus what it wants—more time to spread.
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Some ventures are merging artificial intelligence (AI) into their efforts to find novel drug and re-purposing treatment opportunities, however, AI can only be so helpful in this ongoing fight. In order to accelerate disease treatment and address this critical demand, blending the power of AI and big data with patient biology will enable a more efficient process to discover potential drugs and enhance our understanding of potential effects on patients.
This novel virus demands a novel approach, and you may ask why adding AI, an emerging, practically captivating technology, into existing efforts is not sufficient, or why it’s not a one-size-fits-all solution.
AI is transformative in the capabilities it offers in transforming modern medicine as AI is seen as superhuman—an unrealistic ideal.
Yet, it’s when we in the biopharmaceutical realm are able to strategically combine AI with patient biology and data that it becomes both practical and promising in transforming disease treatment.
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AI is an amazing tool that illuminates the actionable parts of biology that have been affected by disease and helps devise paths to create change.
Take for example the current efforts underway to repurpose existing drugs as a way of fighting the pandemic. As covered by a recent paper in the British Journal of Pharmacology, it re-iterated an unnerving claim that we continue to hear; that a safe vaccination could take 12 to 18 months.
This is where AI fits into this battle, offering an optimistic alternative by assisting in the rapid identification of existing drugs.
Simply put, the world is in a much too precarious position to wait for a vaccine, and drug repurposing has great potential to treat coronavirus infections much faster. Most importantly, it’s the unprecedented capabilities AI presents that can help drug repurposing live up the claim of being a successful alternative.
Why?
Even with this alternative, it’s unlikely that one drug will be found as an effective agent for everyone, meaning a large abundance of drugs will need to be evaluated to identify the best-ranked candidates. Additionally, we cannot afford traditional trial and error approaches to see if a drug works for a certain group over another.
AI can make processes more efficient by grouping various similarities and highlighting the key differentials to enable a precision medicine approach to COVID-19 treatment regimens. We cannot afford traditional trial and error approaches nor can we, as humans, take synthesized outputs and try to digest them into actionable insights in our quest to find a viable treatment.
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