Quantum Machine Learning: Key to Battle against COVID-19
Recently Researchers from Penn State University have discovered to beat coronavirus caused COVID-19: quantum machine learning. The team led by Swaroop Ghosh, Joseph R., and Janice M. Monkowski Career Development Assistant Professor of Electrical Engineering and Computer Science and Engineering state that quantum machine learning is simple the application of machine learning algorithms on the world of quantum physics.
While traditional methods of drug discovery involves researching about chemical molecules, extraction from natural sources or synthesizing it in laboratory, developing compounds, further studying its effects on test subjects and endless trials. The whole procedure from concept to actual market launch of a drug, costs time, resources and is carried out in a hit and trial format, without much hopes of success.
According to Prof. Ghosh, discovering any new drug that can cure a disease is like finding a needle in a haystack. Further, it is an incredibly expensive, laborious, and time-consuming solution. Using the current conventional pipeline for discovering new drugs can take between five and ten years from the concept stage to being released to the market and could cost billions in the process.
He further adds, “High-performance computing such as supercomputers and artificial intelligence can help accelerate this process by screening billions of chemical compounds quickly to find relevant drug candidates.”
“This approach works when enough chemical compounds are available in the pipeline, but unfortunately, this is not true for COVID-19. This project will explore quantum machine learning to unlock new capabilities in drug discovery by generating complex compounds quickly,” he explains.
The funding from the Penn State Institute for Computational and Data Sciences, coordinated through the Penn State Huck Institutes of the Life Sciences as part of their rapid-response seed funding for research across the University to address COVID-19, is supporting this work.
Ghosh and his electrical engineering doctoral students Mahabubul Alam and Abdullah Ash Saki and computer science and engineering postgraduate students Junde Li and Ling Qiu have earlier worked on developing a toolset for solving particular types of problems known as combinatorial optimization problems, using quantum computing. Drug discovery falls under the combinatorial optimization umbrella, which made the transition to COVID-19 drug discovery relatively painless for the team.
Ghosh considers the usage of Artificial intelligence for drug discovery to be a very new area. “The biggest challenge is finding an unknown solution to the problem by using technologies that are still evolving — that is, quantum computing and quantum machine learning. We are excited about the prospects of quantum computing in addressing a current critical issue and contributing our bit in resolving this grave challenge.” he elaborates.