A useful quantum computer will need millions of qubits and silicon is the way to get there. At Quantum Motion, we don’t just focus on developing the machine, we are working hand-in-hand with industry to understand when and how quantum computing will make an impact on their most important challenges. A great example is our recent collaboration with Boehringer Ingelheim, University of Toronto, and University of Oxford. Together, we’ve developed a quantum algorithm that tackles one of the central problems in drug discovery: calculating free energy differences to predict how well a molecule will bind to a biological target. While today’s hardware isn’t yet ready to run such demanding algorithms, the research demonstrates a clear milestone for future applications of #quantum computing in pharmaceuticals and motivates us to keep building the most scalable kind of quantum computer, based on #CMOS transistors. Incredible work led by our applications lead Thomas R. Bromley https://lnkd.in/gGxRU66F
How can quantum computing be used for drug design? Calculating free energies is a crucial step to understand how well a drug molecule will bond to a biological target. A recent arXiv upload by authors from Quantum Motion, Boehringer Ingelheim, University of Toronto, and University of Oxford defines a quantum algorithm that computes free energy differences using a technique called thermodynamic integration, offering performance improvements over prior quantum-based approaches. Although this algorithm is too resource intensive for current quantum hardware, it offers a future-facing milestone for the practical application of quantum computing ⭐ https://lnkd.in/e9DKzQd6
