IEEE Quantum News - Fall 2021

Quantum computing: The next big thing in healthcare?

Christoph Zindel, Member of the Managing Board, Siemens Healthineers

IEEE Quantum Newsletter, Fall 2021

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 News Fall 1 healthcare smallHealthcare is facing major challenges globally. The world’s population is growing and getting older. Chronic diseases are on the rise. Medical knowledge is growing exponentially. Costs are exploding, and there’s a shortage of medical professionals. This combination is leading to overworked medical professionals and overloaded healthcare systems. COVID-19 has only exacerbated these challenges. At the same time, the pandemic shows that digitalization is an essential and effective response.

This means that quantum computers (QC) are also part of the answer to the overburdened healthcare systems: their special properties enable them to accelerate digital innovations. True, the performance of traditional computers and their storage capacity is also growing very fast, and for many applications their capacity is sufficient. However, I expect game-changing new possibilities in some areas, especially with regards to optimization problems and machine learning. The coexistence of traditional binary processing computers and QC will be an attractive hybrid approach.

QCs are still in an intermediate development stage: While they're far from ready for commercial use, they've grown well beyond the realm of science fiction. A quote from Richard Feynman (1918-1988), the famous physicist and Nobel Prize winner who developed the field of quantum electrodynamics, describes the complexity of the topic very well. His comment about quantum mechanics: “If you think you understand quantum mechanics, you don’t understand quantum mechanics.” It’s still impossible to forecast just what the potential will be for evaluating medical images, image reconstruction, diagnostics, and treatments. But the initial studies give me lots of hope and huge expectations. So back to the first question: Is quantum computing the next big thing in healthcare? Here are my thoughts:

QC has the potential to break many barriers that limit traditional computers. I therefore expect a huge impact on many different industries: Chemists could develop new polymers, solids, and substances with a higher level of precision. Just think of better materials for lighter airplanes, or fertilizers and pesticides with less impact on the environment. The financial and insurance sector is looking closely for new tools for risk analysis and the dynamic optimization of their portfolios. Another promising field is transportation: preventing traffic jams, reducing wait times, and optimizing transport routes. Healthcare will also be influenced, there’s no doubt about that, just a few examples:

  • Data mining: Heart rate, blood pressure, antibody concentration over time, genetic information, vaccination dates, EKG, data collected during exercise, hormone concentrations, medical images, ancestry: The volume of medical data from a single person can add up to an enormous amount. I expect this field to grow substantially in the future: Just think about the potential of smart watches and sensors. A growing number of medical gadgets will send zettabytes of data about a patient into the cloud, and QC might be able to make sense of this highly diverse information. Lifestyle medicine could move to a whole new level. Our vision is a digital twin of the patient – a growing, lifelong integration of data on an individual person, maybe even including their entire genetic information set (prices for sequencing have dropped drastically). QC and new algorithms will help discover new connections in this information that will enable a more predictive and preventive medicine.
  • Radiotherapy: Cancer is on the rise in many countries. Based on their special skills in optimization, QC could allow simulations of the optimal radiation plan to minimize damage to surrounding tissue. For example, QC could calculate the radiation dose plan, identify organs at risk, and generate a personalized therapy plan by evaluating a much more complex array of data than before. Another advantage could be real-time modification of these plans during radiation therapy: for example, to take into account organ motion.
  • Supersonic drug design: QC can speed up molecular comparison. This is a major part of the important task of finding new drugs much faster and making them more personalized for patients: for example, to treat oncological diseases in a much more targeted approach. This involves intensive computational methods to review molecule matches and predict the positive effects of a therapy or a drug while also reducing negative side effects. Biological molecules are the target of drugs, and the potential interactions between the molecular surface and drug candidates are gigantically high – and QC could bring fundamental progress. First initiatives in this area are underway: a collaboration between Accenture, quantum software company 1Qbit, and the biotech company Biogen*. They’re designing a quantum application of medical solutions for multiple sclerosis, Alzheimer’s, and Parkinson’s. This approach could also strengthen the fight against rare diseases.
  • Protein folding: This complex subject has been studied for over half a century due to the central role of protein’s structures in chemistry, biology, and medicine. Although there’s been some impressive progress recently in this complex area of bioscience with traditional computers, QC could take this to a whole new level. This is also due to the fact that QC can solve certain computer science problems more efficiently than classical computers. The feasibility of such an approach has been shown recently by researchers from IBM and Sorbonne University**.

 

To summarize: QC can perform large-scale comparisons between molecules to do things like identify new active agents much more quickly than is currently possible. I expect QC to be able to discover new connections in the vast quantities of data gathered from wearables and other sensors, which will improve clinical decision-making processes. Quantum computers’ special abilities may lead to in-silico trials with no human subjects. We might also see progress in evaluating sequences of genetic material consisting of billions of components. As in other industries: Yes, QC will be a big thing in healthcare.

 

At the same time, I’m aware of another unique feature of QCs: They can decipher many of the encryption techniques we’re familiar with, which means we’ll need new security measures – in particular, to protect patient data and prevent cyberattacks. At the same time, QC could ensure the safety of sensitive healthcare data by using quantum uncertainty for encryption. Security by design must be our response: However, we have to rethink it in the light of QC. To ensure effective data security, we’ll have to adopt new approaches and no longer simply secure individual devices or processes as we’ve done in the past. Other opportunities provided by QC will help us develop dynamic and accelerated security that will protect data in almost the same way as the human immune system. Protection – everywhere and all the time.

To summarize: I’m convinced that quantum computers will give us a new understanding of the functioning of the human body based on their ability to process large amounts of data in a short time and identify new information and connections. At the same time, by obtaining and making more and more structured medical data from individuals accessible, we’re creating the necessary technical pre-conditions. But there’s one thing we can’t lose sight of:

We’re talking about the health data from individuals, possibly the most personal possession we have. Only if we have people's trust in the correct handling of their information, we can make progress with digital innovation. QC doesn’t change this fundamental reality.

*https://www.accenture.com/cr-en/case-studies/life-sciences/quantum-computing-advanced-drug-discovery

**https://www.nature.com/articles/s41534-021-00368-4

 


 

Christoph.Zindel.newsletterAuthor, Christoph Zindel 

Christoph Zindel, M.D., has been a Member of the Managing Board of Siemens Healthineers since October 2019. Christoph Zindel joined the healthcare business of Siemens in 1998 as Segment Manager and served in diverse management positions with increasing responsibility within the magnetic resonance business unit.

From 2012 on he served as Chief Executive Officer of PETNET Solutions based in Knoxville, TN, United States, before joining Beckman Coulter to head the hematology and urinanalysis business as Senior Vice President, based in Miami, FL, United States. After he returned to Siemens Healthineers in 2015, he served as Senior Vice President and general manager of the magnetic resonance business line and became President of the diagnostic imaging business in 2018.

Christoph Zindel holds a Doctor of Medicine M.D. (Dr.) from the J.W. Goethe University Frankfurt, Germany. He was born in Stuttgart, Germany, in 1961.

 

 

maeva ghonda portraitEditor,  Maëva Ghonda

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