Drug Design At The Speed Of Quantum
By Scott Buchholz, quantum computing leader, Deloitte Consulting LLP
Across the globe, millions await the development of new or improved drugs to address their health concerns. Many may never see those drugs come to market, as the average drug development timeline is nearly a decade and seems to be growing in complexity.1
Quantum computing breaks free of the binary restrictions of classical computing, and relies on the principles of physics, not math, to solve problems. For example, even powerful supercomputers cannot accurately simulate complex molecular and atomic interactions, but quantum computers have an advantage in solving problems that involve multiple interdependencies and correlations (such as predicting molecular structures). With quantum computers in their toolkits, scientists will be able to conduct more efficient and accurate simulations, which could ultimately lead to more effective drugs for patients.
Accordingly, quantum startups and major pharmaceutical companies alike are exploring quantum computing to speed up the process of moving from hypothesis to drug. Consider that more accurate simulations of complex molecular systems can better predict how drugs will interact. Optimized drug design can identify the most effective molecular structures. And, new therapeutic pathways could open the door to more personalized drugs. The transformation to life sciences could be profound, as we detail below.
Modeling Accurately At The Molecular Level
In early-stage drug discovery and development, pharmaceutical scientists conduct computer-assisted drug discovery. Using tools such as molecular dynamics and density functional theory, they develop computer models and simulations that can predict the impact of millions of macromolecules on diseases and the human body. While such “in-silico” methods are currently neither accurate nor speedy, they’re typically safer at this stage than in vitro methods such as clinical trials. Recent breakthroughs have even captured a great deal of this information in machine learning databases, enabling better understanding of molecular interactions.2
Quantum computers could build on this progress. With their ability to better simulate the behavior of electrons within a molecule, they could reach a level of granularity that would allow them to precisely model protein folding (a key aspect of analyzing disease causes) and help scientists develop new drugs.3 This includes generating scientifically valid evidence, pinpointing a disease’s biological origins and ensuring that such a biological target can be safely manipulated to achieve therapeutic benefits.
Quantum computers could also identify compounds with therapeutically useful, pharmacological, or biological action that could serve as a starting point to improve the strength and precision of the compound. All this could help reduce the time and cost of bringing life-saving drugs to market. For that to happen, significant progress is still needed in quantum computing cost, availability, and applicability.
Optimizing Drug Design
After identifying drug targets through simulation, researchers then have to optimize potential drug candidates on several levels for factors such as absorption, metabolism, and toxicity. Today, computers are often used to calculate the binding affinity of a drug compound to a molecular target, which is an important indicator of efficacy, side effects, and dosage. These calculations can be difficult due to the many complex molecular and thermodynamic interactions at play and take many hours for classical computers to apply on a small scale.
Quantum mechanical calculations on quantum computers, though still in their early stages of implementation, can one day speed up these drug design calculations and optimize them for better quality. This is especially true for drugs that tend to have high toxicity levels, such as those for cancer treatment, that have much room for improvement in absorption and other factors.4 Improving efficacy means that quantum computing could greatly impact the approval rates and overall timeline for creating new drugs.
Personalizing Treatment With New Therapeutics
When it comes to pharmaceuticals, consumers have learned to wait for the long list of potential side effects at the end of every advertisement. That’s because, when it comes to medicine, the cliché is true: each one of us is unique. Traditional computing methods have trouble anticipating the numerous potential interactions of a drug with the myriad traits of each individual. For this reason, the holy grail of drug development is personalized medicine, where therapeutics are tailored to one person. Quantum computing could pave the way toward that goal.
Quantum algorithms can process complex patient data more accurately, identifying genetic variants that may influence an individual’s response to a drug. Treatment plans can then be tailored accordingly. In addition to identifying new pathways for existing drugs, quantum simulations would also aid in designing net-new molecules, such as antibodies and enzymes, that are optimized for specific diseases.
For example, researchers are exploring how quantum computers can identify the most effective combination of therapeutics for cancer patients.5 Such a personalized recommendation could dramatically improve health outcomes by reducing the side effects of chemotherapy treatments. There are challenges to amassing the data needed for such a marked improvement in medicine, but quantum computing could soon be ready for prime time.
Conclusion
Quantum computing holds immense promise for revolutionizing drug development in the life sciences sector. By enabling more accurate molecular simulations, optimizing drug design, and personalizing therapeutics, quantum computing can accelerate the discovery of new therapies, reduce costs, and enhance precision medicine. However, significant challenges exist, including:
- Technical limitations, such as errors and limited qubit counts6
- High costs, such as the infrastructure needed to develop and maintain quantum computers (a reason why many life sciences companies are partnering with specialized quantum firms)
- Integration hurdles, especially into well-established drug development workflows at major pharmaceutical companies
- Regulatory considerations, including ensuring the safety and efficacy of quantum-derived drugs
Life sciences executives should keep abreast of these challenges in a rapidly evolving landscape. Today’s problems may be tomorrow’s opportunities or clear answers. Staying informed about advancements in quantum computing and fostering collaborations with quantum technology firms will be crucial for joining this next wave of innovation in medicine.
Quantum computing is also poised to disrupt the status quo in clinical trials. See my companion article on Clinical Leader here.
References
- https://pmc.ncbi.nlm.nih.gov/articles/PMC9869766/; https://www.nature.com/articles/s41598-024-53211-z
- https://www.nature.com/articles/s41567-024-02411-5
- https://www.forbes.com/councils/forbesbusinessdevelopmentcouncil/2024/10/15/how-quantum-computing-is-accelerating-drug-discovery-and-development/
- https://www.kvantify.com/inspiration/the-convergence-of-quantum-computing-and-early-drug-discovery
- https://quantumzeitgeist.com/quantum-computing-in-healthcare-transforming-medicine-and-research/
- https://www.clinicaltrialsarena.com/features/quantum-computers-drug-development/?cf-view
About The Author:
Scott Buchholz is Deloitte Consulting LLP’s quantum computing leader and national emerging tech research director. He helps clients use technology to transform their organizations, missions, and businesses, and leads efforts in exploration of quantum computing and related technologies. He works across industries to provide actionable advice and insights to use technology to improve performance, effectiveness, and efficiency. In his role as CTO for Deloitte Consulting LLP’s Government and Public Services practice, he works with government clients to use technology to innovate in their operations, technology, and mission delivery.