Quantum Computing Applications in Drug Research
Computing technologies have become crucial to the improvement of drug research, whether through streamlining the drug design process or predicting drug targets and target-drug interactions. These techniques use either the classical computing or quantum computing approach, each useful for certain applications. For instance, classical approaches would be applied to dealing with large molecular systems and are based on empirical models for describing interactions between the molecules or atoms. On the other hand, quantum techniques have been shown promising for accelerated development of more efficient therapies [1].
One of the main technological limitations of the current state of drug research and development is efficiency in optimization problems – finding the best solution by testing all feasible solutions – especially as it concerns designing new drugs with suitable pharmacological profiles. While classical computers are lacking in this area, quantum computers are extremely good at optimization problems due to their ability to leverage parallel states of quantum superposition. In other words, quantum computers are able to model all possible outcomes of a problem at once and thus rapidly process massive amounts of data [2].
Quantum computers are not just faster or more powerful than classical computers, but rather they work in a completely different way – These newer machines control the behavior of atoms and fundamental particles in a very unique manner - while a normal computer has bits that hold binary identities of zeros or ones, a quantum computer’s bits (qubits) hold nonbinary identities, thus each bit lies on a spectrum between zero and one, creating superposition and uncertainty. For example, the superposition of n qubits yields 2n possibilities that can be represented and computed at the same time [2].
In the case of drug development, quantum computers provide the capacity to simultaneously map numerous compounds and their conformations and rapidly identify an appropriate drug candidate among millions of compounds, speeding up the process of comparing the effects and interactions of various drugs. Quantum computers aid in predicting the mechanisms of chemical reactions, repurposing drugs, and developing methods for analyzing large-scale molecules. Overall, they facilitate the creation of more effective therapeutics. This dramatically lowers the costs of novel drug research and development, helps bring new drugs to trial more quickly, and improves the safety of clinical trials [2].
In drug discovery, artificial intelligence (AI) and machine learning (ML) are important tools. While the aim of AI is enhancing success, ML focuses on increasing accuracy and providing self-learning algorithms and knowledge. When quantum computing is applied to improving ML algorithms and accelerating AI, it could allow for more effective performance of complex tasks. For example, while one application of AI is quickly screening billions of chemical compounds to find relevant drug candidates, this only works if enough chemical compounds are available in the pipeline. With quantum machine learning, which involves a combination of ML and quantum computing, rapidly generating complex compounds could allow for a much quicker drug discovery process. This is particularly applicable during the COVID-19 pandemic, where there are not enough chemical compounds available to analyze. In fact, researchers at Penn State University are currently employing quantum machine learning to search for a COVID-19 treatment [1][4].
References:
1. Skoff, Gabriella. “Transforming Drug Development: A Critical Role for Quantum Computing.” Project Q, 7 Apr. 2020, projectqsydney.com/transforming-drug-development-a-critical-role-for-quantum-computing/.
2. Parichehr Hassanzadeh, Towards the quantum-enabled technologies for development of drugs or delivery systems, Journal of Controlled Release, Volume 324, 2020, Pages 260-279, ISSN 0168-3659
3. Savíns Puertas-Martín, Antonio J. Banegas-Luna, María Paredes-Ramos, Juana L. Redondo, Pilar M. Ortigosa, Ol’ha O. Brovarets' & Horacio Pérez-Sánchez (2020) Is high performance computing a requirement for novel drug discovery and how will this impact academic efforts?, Expert Opinion on Drug Discovery, DOI: 10.1080/17460441.2020.1758664
4. Small, Sarah. “Researchers Explore Quantum Computing to Discover Possible COVID-19 Treatments.” Phys.org, Phys.org, 5 May 2020, phys.org/news/2020-05-explore-quantum-covid-treatments.html.
