en.Wedoany.com Reported - A research team at the Technical University of Denmark (DTU) has made progress in accelerating vaccine development using quantum computers. The team combined a generative AI model with a printer-sized quantum computer manufactured by UK startup ORCA Computing to generate novel peptides capable of binding to specific proteins in the human body, a key step in vaccine and immunotherapy development.
Led by Professor Timothy Patrick Jenkins, the research team employed a hybrid approach that connects the quantum computer with traditional processors. This method aims to accelerate AI's ability to predict and generate peptides (short chains of amino acids) that could become vaccine candidates. Laboratory test results showed that, compared to classical models, this hybrid model produced more peptides that successfully bound to target proteins, with the most significant improvements observed when available training data was very limited.
The research team noted that this technology has the potential to accelerate the development of immunotherapies and personalized vaccines, and to improve drug effectiveness for understudied populations, such as those in Asia and Africa. Currently, most medical research focuses on Western populations, leading to a scarcity of genetic data for other groups. The DTU team's hypothesis was confirmed: quantum computers can generate more diverse peptide sequences, particularly for data-scarce targets, helping to address the major challenge in vaccine development of lacking genetic data that represents the full diversity of the human population.
However, the researchers acknowledge that the technology is still in its early stages. DTU PhD student Jonathan Funk explained that current quantum computers are still too small to run full-scale cutting-edge AI models, meaning the complex molecules they can encode are not the normal-sized antibodies typically handled. He added that finding peptides that can bind to specific genes is just one step in vaccine development, and the entire process alone is not sufficient to produce a successful drug. ORCA Computing CEO Richard Murray stated that many industry companies view quantum technology as still "vague and distant," partly due to a lack of clear short-term use cases, but he believes this research demonstrates the potential for short-term commercial applications of quantum technology.
In the future, the DTU team plans to test whether the same workflow can be applied to more advanced models and larger proteins. Professor Jenkins emphasized that generative AI workflows are valuable for neglected diseases that receive only limited research funding. Currently, he is also exploring the use of quantum computers to improve his generative AI methods for designing synthetic antidotes against snake venom. This research provides preliminary evidence of the potential for integrating quantum computers with AI to solve practical problems in the medical field. Through a hybrid approach, it may be possible to overcome data limitations for understudied populations, paving the way for developing more inclusive vaccines and therapies, though the path to full application remains long. Researchers and the pharmaceutical industry can gain initial evidence from this work that quantum computers are already capable of producing measurable benefits in real-world research.
