[Paper Review] Early quantum computing applications on the path towards precision medicine

Frederik F. Flöther|arXiv (Cornell University)|Mar 5, 2024

Scientific Computing and Data ManagementDecision Sciences3 citations

TL;DR

This paper explores early-stage quantum computing applications in precision medicine, focusing on genomics, diagnostics, and treatment optimization using near-term quantum hardware. It outlines proof-of-concept studies in pharmaceuticals and clinical research, identifies key use cases, and proposes strategies to accelerate practical quantum applications in healthcare.

ABSTRACT

The last few years have seen rapid progress in transitioning quantum computing from lab to industry. In healthcare and life sciences, more than 40 proof-of-concept experiments and studies have been conducted; an increasing number of these are even run on real quantum hardware. Major investments have been made with hundreds of millions of dollars already allocated towards quantum applications and hardware in medicine. In addition to pharmaceutical and life sciences uses, clinical and medical applications are now increasingly coming into the picture. This chapter focuses on three key use case areas associated with (precision) medicine, including genomics and clinical research, diagnostics, and treatments and interventions. Examples of organizations and the use cases they have been researching are given; ideas how the development of practical quantum computing applications can be further accelerated are described.

Motivation & Objective

• To identify and analyze early quantum computing use cases in precision medicine across genomics, diagnostics, and therapeutic interventions.
• To assess the current state of quantum applications in healthcare, including proof-of-concept experiments and real hardware deployments.
• To highlight major investments and institutional efforts driving quantum adoption in life sciences and clinical medicine.
• To propose actionable pathways for accelerating the development and deployment of practical quantum computing applications in healthcare.
• To bridge the gap between quantum computing research and clinical implementation in precision medicine.

Proposed method

• Systematic review and synthesis of over 40 proof-of-concept studies in quantum computing applied to healthcare and life sciences.
• Analysis of real-world quantum hardware deployments in pharmaceutical and clinical research settings.
• Identification of key technical and organizational enablers for scaling quantum applications in medicine.
• Case study analysis of organizations actively researching quantum applications in genomics, diagnostics, and treatment planning.
• Integration of insights from quantum physics and quantitative biology to map feasible near-term applications.
• Evaluation of investment trends and infrastructure development in quantum health applications.

Experimental results

Research questions

• RQ1 What are the most promising near-term applications of quantum computing in precision medicine?
• RQ2 How are organizations currently leveraging quantum hardware for genomics, diagnostics, and treatment planning?
• RQ3 What are the key technical and institutional barriers to scaling quantum applications in clinical healthcare?
• RQ4 How can proof-of-concept quantum applications in life sciences be accelerated toward real-world deployment?
• RQ5 What role do current investments and institutional collaborations play in advancing quantum computing for precision medicine?

Key findings

• Over 40 proof-of-concept studies in quantum computing have been conducted in healthcare and life sciences, with an increasing number running on actual quantum hardware.
• Major investments—hundreds of millions of dollars—have been allocated toward quantum applications and hardware in medicine, signaling growing industry and institutional commitment.
• Quantum computing applications are expanding beyond pharmaceutical R&D to include clinical research, diagnostics, and personalized treatment planning.
• Real-world use cases are emerging in genomics, such as variant analysis and polygenic risk scoring, using noisy intermediate-scale quantum (NISQ) devices.
• Organizations such as pharmaceutical companies and research institutions are actively piloting quantum algorithms for disease modeling and drug discovery.
• The paper identifies a clear pathway toward clinical deployment by focusing on hybrid quantum-classical algorithms and targeted problem spaces with high quantum advantage potential.