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Studies in big data

Revolutionizing Drug Discovery and Biomedical Research Through Quantum Machine Learning: Paving the Path to Precision Healthcare

Neetu Ramesh Amlani, S A Deshpande, Shraddha Doye, Omprakash Chandraka

Published Jan 1, 2026• 0 citations
Publisher
DOI
10.1007/978-3-032-00586-1_6

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With the growing complexity of biomedical data, molecular interactions and genomic architectures, there are significant challenges in adapting traditional healthcare analytics and drug discovery systems to meet computational demands. The paradigm of quantum computing has recently come into the spotlight as a potential method to solve multidimensional optimization, molecular simulation and genomic inference problems using concepts like superposition, entanglement, and quantum parallelism. This chapter examines quantum algorithms and hybrid quantum-classical architectures in the drug discovery, protein folding, genomic analysis, and precision medicine applications. It also explores quantum machine learning algorithms such as VQE, QAOA, QSVM, and QNN, which are used for intelligent biomedical analytics. In addition, the conversation also covers cloud-edge quantum healthcare infrastructures, post-quantum security, and real-world healthcare applications, further demonstrating the potential impact of quantum-enhanced healthcare systems.