Which part of the drug discovery life cycle can quantum computing impact the most

The promise of quantum computing is to solve unsolvable problems. And companies are already making headway with hybrid approaches — those that combine classical and quantum computing — to tackle challenges like drug discovery for incurable diseases. By accelerating drug molecule simulation and modeling with hybrid quantum computing, startup Qubit Pharmaceuticals is significantly reducing the time and investment needed to identify promising treatments in oncology, inflammatory diseases and antivirals. Qubit is building a drug discovery platform using the Founded in 2020, the Paris and Boston-based company is a member of Qubit has one of France’s largest GPU supercomputers for drug discovery, powered by “By combining NVIDIA’s computational power and leading-edge software with Qubit’s simulation and molecular modeling capabilities, we are confident in our ability to dramatically reduce drug discovery time and cut its cost by a factor of 10,” said Robert Marino, president of Qubit Pharmaceuticals. “This unique collaboration should enable us to develop the first quantum physics algorithms applied to drug discovery.” Tapping Unprecedented Computational Capabilities Computational drug discovery involves generating high-resolution simulations of potential drug molecules and predicting how well those molecules might bind to a target protein in the body. For accurate results, researchers need to perform massive sampling, simulating hundreds of different conformations — possible spat...

By Product • Product Overview The only full-stack, cross-platform quantum ecosystem built for business • Cloud Platform The Leap™ quantum cloud service provides real-time quantum access • Systems The Advantage™ quantum system is the first and only quantum computer built for business • Professional Services The D-Wave Launch program on-boards your business to quantum computing • Software & Tools The Ocean™ suite of open-source tools are accessible via the Ocean SDK for rapid quantum development • • Community Forums Connect with and learn from other quantum developers. • Getting Started Step-by-step approach to building quantum applications today. • Code Samples Search for and run working examples by industry, problem type, and tools or techniques. • Developer Start here! • Documentation Find out more about D-Wave’s quantum technologies and how they work. • Drug discovery is a high-risk, high-reward field, where a blockbuster therapy can deliver life-changing clinical benefits to millions of patients and generate billions of dollars in profit—but more than 90% of new drug development efforts ultimately prove fruitless. Quantum computing can help pharma and biotech companies to stack the odds in their favor. Large pharma companies like GlaxoSmithKline and emerging biotech companies like Menten AI are already exploring how D-Wave quantum hybrid technology can enable faster and more efficient computer-aided drug design. Quantum computing can also contribute to other scientific ...

With a new announcement from IBM and Germany’s Fraunhofer Institute, Europe joins the race Despite being a research and manufacturing powerhouse, Germany, like Europe as a whole, has been lagging behind in what is probably the next tech revolution: quantum computing. Now, IBM, one of the world leaders in quantum computing, has announced a collaboration with the revered Fraunhofer Institute, which includes operating what the company says is Europe’s most powerful quantum computer to date. The new computer belongs to the IBM Q System One class – the first-ever line of commercially available quantum computers. Despite its relatively modest 20 quantum bit (qubit) capacity, it may still greatly benefit German industry, according to some potential clients. BMW, for instance, touted the computer’s ability to help industrial robots find the most efficient way to seal seams on a car. While we all would love to see even more solidly built German cars, what does all this have to do with longevity? It turns out that quantum computers can greatly speed up drug discovery, including new geroprotective drugs. Superposition, interference, and entanglement What makes quantum computing special? In a nutshell, quantum computers utilize the unique characteristics of quantum states. Contrary to regular bits, which can only assume the states 0 or 1, a qubit can be in an indeterminate superposition, with certain probabilities of ending up as 0 or 1 when measured. Other quantum properties that are...

The study includes scientists from Insilico Medicine, Foxconn, Zapata Computing, and University of Toronto. Credit: Insilico Medicine Insilico Medicine, a clinical stage generative artificial intelligence (AI)-driven drug discovery company, today announced that it combined two rapidly developing technologies, quantum computing and generative AI, to explore lead candidate discovery in drug development and successfully demonstrated the potential advantages of quantum generative adversarial networks in generative chemistry. The study, published in the Journal of Chemical Information and Modeling, was led by Insilico's Taiwan and UAE centers which focus on pioneering and constructing breakthrough methods and engines with rapidly developing technologies—including generative AI and The research was supported by University of Toronto Acceleration Consortium director Alán Aspuru-Guzik, Ph.D., and scientists from the Hon Hai (Foxconn) Research Institute. "This Generative Adversarial Networks (GANs) are one of the most successful generative models in drug discovery and design and have shown remarkable results for generating data that mimics a data distribution in different tasks. The classic GAN model consists of a generator and a discriminator. The generator takes random noises as input and tries to imitate the data distribution, and the discriminator tries to distinguish between the fake and real samples. A GAN is trained until the discriminator cannot distinguish the generated da...

Drug discovery has been one of the most challenging and labour intensive processes in pharmacology for the entirety of human history. The preclinical assessment of new chemical formulations for biological activity and ensuring that their targeted therapeutic function works as intended is a big enough hurdle of its own before a substance even moves on to safety assessment and clinical trials. A Brief History of Drug Discovery Previously, the process of drug discovery relied much more heavily on serendipity and an older version of what we could call Phenotypic Drug Discovery today. Phenotypic assessments of active ingredients assess the effect of a substance externally, without detailed knowledge of its internal mechanism of action. A large number of pharmaceuticals originated from the plant kingdom, and their Naturally, while analysing plants for therapeutic agents does remain a valid form of inquiry today, it is not how the majority of modern drug discovery happens. Indeed, just as salicylic acid gave rise to an entire class of painkillers (the non-steroidal anti-inflammatory drugs), so did drug discovery move past the finite resource of different plant species on the planet. This process began with the development of target) of interest. While all three methods remain in some use today, mechanistically driven drug discovery is the most capital intensive, and the most well known. Modern Drug Discovery This process of drug discovery has benefited from advances in computing ...

Drug discovery has been one of the most challenging and labour intensive processes in pharmacology for the entirety of human history. The preclinical assessment of new chemical formulations for biological activity and ensuring that their targeted therapeutic function works as intended is a big enough hurdle of its own before a substance even moves on to safety assessment and clinical trials. A Brief History of Drug Discovery Previously, the process of drug discovery relied much more heavily on serendipity and an older version of what we could call Phenotypic Drug Discovery today. Phenotypic assessments of active ingredients assess the effect of a substance externally, without detailed knowledge of its internal mechanism of action. A large number of pharmaceuticals originated from the plant kingdom, and their Naturally, while analysing plants for therapeutic agents does remain a valid form of inquiry today, it is not how the majority of modern drug discovery happens. Indeed, just as salicylic acid gave rise to an entire class of painkillers (the non-steroidal anti-inflammatory drugs), so did drug discovery move past the finite resource of different plant species on the planet. This process began with the development of target) of interest. While all three methods remain in some use today, mechanistically driven drug discovery is the most capital intensive, and the most well known. Modern Drug Discovery This process of drug discovery has benefited from advances in computing ...

The study includes scientists from Insilico Medicine, Foxconn, Zapata Computing, and University of Toronto. Credit: Insilico Medicine Insilico Medicine, a clinical stage generative artificial intelligence (AI)-driven drug discovery company, today announced that it combined two rapidly developing technologies, quantum computing and generative AI, to explore lead candidate discovery in drug development and successfully demonstrated the potential advantages of quantum generative adversarial networks in generative chemistry. The study, published in the Journal of Chemical Information and Modeling, was led by Insilico's Taiwan and UAE centers which focus on pioneering and constructing breakthrough methods and engines with rapidly developing technologies—including generative AI and The research was supported by University of Toronto Acceleration Consortium director Alán Aspuru-Guzik, Ph.D., and scientists from the Hon Hai (Foxconn) Research Institute. "This Generative Adversarial Networks (GANs) are one of the most successful generative models in drug discovery and design and have shown remarkable results for generating data that mimics a data distribution in different tasks. The classic GAN model consists of a generator and a discriminator. The generator takes random noises as input and tries to imitate the data distribution, and the discriminator tries to distinguish between the fake and real samples. A GAN is trained until the discriminator cannot distinguish the generated da...

By Product • Product Overview The only full-stack, cross-platform quantum ecosystem built for business • Cloud Platform The Leap™ quantum cloud service provides real-time quantum access • Systems The Advantage™ quantum system is the first and only quantum computer built for business • Professional Services The D-Wave Launch program on-boards your business to quantum computing • Software & Tools The Ocean™ suite of open-source tools are accessible via the Ocean SDK for rapid quantum development • • Community Forums Connect with and learn from other quantum developers. • Getting Started Step-by-step approach to building quantum applications today. • Code Samples Search for and run working examples by industry, problem type, and tools or techniques. • Developer Start here! • Documentation Find out more about D-Wave’s quantum technologies and how they work. • Drug discovery is a high-risk, high-reward field, where a blockbuster therapy can deliver life-changing clinical benefits to millions of patients and generate billions of dollars in profit—but more than 90% of new drug development efforts ultimately prove fruitless. Quantum computing can help pharma and biotech companies to stack the odds in their favor. Large pharma companies like GlaxoSmithKline and emerging biotech companies like Menten AI are already exploring how D-Wave quantum hybrid technology can enable faster and more efficient computer-aided drug design. Quantum computing can also contribute to other scientific ...

The promise of quantum computing is to solve unsolvable problems. And companies are already making headway with hybrid approaches — those that combine classical and quantum computing — to tackle challenges like drug discovery for incurable diseases. By accelerating drug molecule simulation and modeling with hybrid quantum computing, startup Qubit Pharmaceuticals is significantly reducing the time and investment needed to identify promising treatments in oncology, inflammatory diseases and antivirals. Qubit is building a drug discovery platform using the Founded in 2020, the Paris and Boston-based company is a member of Qubit has one of France’s largest GPU supercomputers for drug discovery, powered by “By combining NVIDIA’s computational power and leading-edge software with Qubit’s simulation and molecular modeling capabilities, we are confident in our ability to dramatically reduce drug discovery time and cut its cost by a factor of 10,” said Robert Marino, president of Qubit Pharmaceuticals. “This unique collaboration should enable us to develop the first quantum physics algorithms applied to drug discovery.” Tapping Unprecedented Computational Capabilities Computational drug discovery involves generating high-resolution simulations of potential drug molecules and predicting how well those molecules might bind to a target protein in the body. For accurate results, researchers need to perform massive sampling, simulating hundreds of different conformations — possible spat...

By Product • Product Overview The only full-stack, cross-platform quantum ecosystem built for business • Cloud Platform The Leap™ quantum cloud service provides real-time quantum access • Systems The Advantage™ quantum system is the first and only quantum computer built for business • Professional Services The D-Wave Launch program on-boards your business to quantum computing • Software & Tools The Ocean™ suite of open-source tools are accessible via the Ocean SDK for rapid quantum development • • Community Forums Connect with and learn from other quantum developers. • Getting Started Step-by-step approach to building quantum applications today. • Code Samples Search for and run working examples by industry, problem type, and tools or techniques. • Developer Start here! • Documentation Find out more about D-Wave’s quantum technologies and how they work. • Drug discovery is a high-risk, high-reward field, where a blockbuster therapy can deliver life-changing clinical benefits to millions of patients and generate billions of dollars in profit—but more than 90% of new drug development efforts ultimately prove fruitless. Quantum computing can help pharma and biotech companies to stack the odds in their favor. Large pharma companies like GlaxoSmithKline and emerging biotech companies like Menten AI are already exploring how D-Wave quantum hybrid technology can enable faster and more efficient computer-aided drug design. Quantum computing can also contribute to other scientific ...