Quantum AI approaches towards drug design

• One of the hardest problems in healthcare today is identification of drug candidates for targets relevant for diseases like cancer. Finding a drug candidate is analogous to finding a needle in the haystack. As a result, drug discovery takes decades and costs billions of dollars. Traditional computational approaches rely on machine learning (ML) which requires millions of training parameters and still fails to find high-quality drug candidate with likelihood to pass the clinical trial. This talk will illustrate viable pathways to harness the immense computational power of quantum computers and quantum AI to design high-quality drug candidates.