Quantum computing is expected to accelerate medical research

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The technology is intended to research the development of multiple diseases. "Quantum computing is one of the emerging technologies that will have a profound impact on the life science industry, healthcare providers and, of course, the treatment options for patients," said Dirk Schapeler, Vice President G4A Digital Innovation at Bayer. “For us, quantum computing is still in the initial phase. However, we want to find out how and for which areas we can best use the technology, ”he adds.

What are typical comorbidities to an illness?The project is based on anonymized real data from intensive care patients and aims to analyze and identify relationships between comorbidities and patterns of disease development. This concept complements the approach of clinical studies, which tend to focus on a limited number of patients and well-structured data for the analysis of disease indicators. “We need to better understand the health of patients who have more than one illness. The Atos Quantum Learning Machine will help us analyze the development of an illness and the interaction with comorbidities, ”says Dr. Ulf Hengstmann, G4A Digital Health Innovation Manager from Bayer. “We already know that patients with specific diseases such as heart failure can have several typical comorbidities. Now we have to understand why this is the case and how it affects therapy. ”

"Developing and Researching Specific Use Cases"According to Atos, the simulation capacity of the Atos Quantum Learning Machine can be increased at any time if necessary, thus supporting the scalability of applications in combination with higher workloads. "Quantum computing will fundamentally change the digital age," says Ursula Morgenstern, CEO of Atos Germany. "In order to fully exploit the potential of the technology, customers have to develop specific applications and research how Bayer is doing this project." The challenge for the coming years will be to find applications that can run on early quantum processors. This shows that quantum computing can either solve problems that conventional computing cannot cope with, or it can prove that it is exponentially faster.

Assess the accuracy of the resultsIn parallel to the quantum computing approach, the Joint Research Center for Computational Biomedicine at RWTH Aachen University carries out the analysis on a high-performance computer to evaluate the accuracy and performance of the results of the quantum experiment. “Structural learning of mechanisms from mass data is a research focus of the Joint Research Center for Computational Biomedicine. The combination of quantum computing and machine learning is still new territory to a certain extent. We see great potential here for medical data analysis, ”says Prof. Andreas Schuppert, head of the Joint Research Center. "We are therefore creating a comparative data analysis with a high-performance computer to evaluate the advantages of quantum computing in structural learning."

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