Quantum computing and AI in drug discovery and public health: Accelerating breakthroughs for global healthcare challenge

This paper explores the transformative power of revolutionizing healthcare through quantum computing and artificial intelligence (AI). The focus is on how these advanced technologies help drive drug discovery and public health strategies based on the premise that traditional methodologies for developing drugs have become inefficient, especially with a very low success rate for viable therapy. Thus, there is a need for innovative techniques capable of enhancing the effectiveness of the process. Quantum computing enables simulations and complex calculations that are not achievable using traditional computers, providing more efficient ways to identify more effective therapies and drug candidates. The combination of AI-powered algorithms to optimize predictive analytics, this capability is poised to improve public health outcomes while shortening timelines for drug discovery. Using empirical evidence backed up by case studies, this study finds that these technologies can expedite new medication development while supporting healthcare systems to address the pressing concern of ageing populations and emerging diseases. Although some challenges exist with integrating these technologies, including technical limitations and ethical concerns like data privacy, experts are finding ways to balance the potential of quantum computing and AI to protect individual patients' rights and provide equitable access to real-time healthcare solutions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-30
DOI
https://doi.org/10.5281/zenodo.17263818
Primary Topic
Agriculture, Water, and Health
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantum computing and AI in drug discovery and public health: Accelerating breakthroughs for global healthcare challenge

Zenodo (CERN European Organization for Nuclear Research)
Agriculture, Water, and Health
article

Quantum computing and AI in drug discovery and public health: Accelerating breakthroughs for global healthcare challenge

article en

Abstract

This paper explores the transformative power of revolutionizing healthcare through quantum computing and artificial intelligence (AI). The focus is on how these advanced technologies help drive drug discovery and public health strategies based on the premise that traditional methodologies for developing drugs have become inefficient, especially with a very low success rate for viable therapy. Thus, there is a need for innovative techniques capable of enhancing the effectiveness of the process. Quantum computing enables simulations and complex calculations that are not achievable using traditional computers, providing more efficient ways to identify more effective therapies and drug candidates. The combination of AI-powered algorithms to optimize predictive analytics, this capability is poised to improve public health outcomes while shortening timelines for drug discovery. Using empirical evidence backed up by case studies, this study finds that these technologies can expedite new medication development while supporting healthcare systems to address the pressing concern of ageing populations and emerging diseases. Although some challenges exist with integrating these technologies, including technical limitations and ethical concerns like data privacy, experts are finding ways to balance the potential of quantum computing and AI to protect individual patients' rights and provide equitable access to real-time healthcare solutions.

Zenodo (CERN European Organization for Nuclear Research)
University of Ibadan (NG), Ball State University (US), University of Maryland Eastern Shore (US), University of North Dakota (US), Kwara State Polytechnic (NG), North Carolina Agricultural and Technical State University (US)
Openalex Percentile: Top 46%
Agriculture, Water, and Health
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