Quantum Machine Learning—A Speedup for Precision Medicine

Quantum Machine Learning—A Speedup for Precision Medicine

In the next 5 years, big data is expected to grow faster in healthcare than in any other sector[1]. By 2025, healthcare data is expected to grow at a CAGR of 36%[2]. One reason for the anticipated rise in healthcare data volume is: precision medicine.

Precision medicine is patient-centered care. In precision medicine, doctors use a holistic approach to uncover unique disease risks to devise tailor made treatments that would work best for an individual patient’s care.[3] It is an emerging practice where a patient’s genetic profile is used to inform medical decisions. In essence, it is data-driven care whereby a patient’s clinical data as well as their data from other factors are considered—for example: genomics, electronic health records, wearables, behavior, social, lifestyle, and environmental influences[4],[5].

The proliferation of such complex healthcare information is producing computational challenges for classical computing. Additionally, the potential insights and analytics which could be gleaned from these disparate data sets stretch the capabilities of classical computing[6]. Quantum computers could unlock value from massive healthcare data lakes. Classical computing and quantum computing cannot be regarded as fungible. Quantum computing could introduce new and different capabilities to strengthen the data management strategies and analytics of healthcare organizations[7]. For instance, the use of algorithms that exploit quantum machine learning to empower healthcare predictive analytics could immensely speed up data-intensive applications[8]. For competitive advantage, leaders championing precision medicine should explore the power of quantum-enhanced machine learning to introduce more accurate risk predictions earlier to improve patient care[9].

About the Author

Maëva Ghonda is a Scientist who also specializes in Corporate Strategy and Competitive Intelligence. As a strategist, Maëva creates investment theses by identifying mega-trends that will profoundly disrupt global commerce.

Maëva Ghonda fell for her true love—Quantum—while working as Quantum Scholar for the Joint Quantum Institute (JQI) for a National Institute of Standards and Technology (NIST) Fellow. She began to discover what is possible with quantum—e.g. Quantum Teleportation and Quantum Money—while reading intricate details of novel quantum-enabled inventions hidden in global patent documents to uncover valuable quantum technology innovations.

Before this fantastic quantum meet-cute, Maëva held cybersecurity risk management roles in healthcare and financial services. As a scientist, Maëva’s research interests include: Quantum Computing, Quantum Cryptography, and Quantum Money.


[1] https://healthitanalytics.com/news/%20big-data-to-see-explosive-growth-challenging-healthcare-organizations

[2] https://healthitanalytics.com/news/%20big-data-to-see-explosive-growth-challenging-healthcare-organizations

[3] https://www.cdc.gov/genomics/about/precision_med.htm

[4] https://www2.deloitte.com/content/dam/insights/us/articles/4149_Davenport-health-care-2027/4149_Davenport-Healthcare-in-2027.pdf

[5] https://www2.deloitte.com/content/dam/Deloitte/us/Documents/process-and-operations/us-cons-translational-research.pdf

[6] https://www.ibm.com/downloads/cas/8QDGKDZJ

[7] https://maevaghonda.medium.com/quantum-computing-re-imagined-c63106d1a792?sk=0ac06480bf6d3fed4cddda0fdc58dad0

[8] https://www.bcg.com/publications/2018/coming-quantum-leap-computing

[9] https://www.ibm.com/downloads/cas/8QDGKDZJ



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Maëva Ghonda

Maëva Ghonda


Maëva Ghonda advises institutional investors and board members on Quantum Computing & IP. She also specializes in Strategy, Risk Management and Sustainability.