Abstract
Providing personalized drug therapy to polymedicated patients is a very complex situation, as not even the most powerful supercomputer in the world could, in a reasonable amount of time, process the enormous number of variables required. Fortunately, quantum computing opens up new possibilities in this field, especially thanks to its ability to efficiently combine a large number of variables. We present the basic idea of an extensible algorithm to deal with genetic polymorphisms, pharmacological polytherapy, and clinical condition, and the implementation of a prototype that allows for the calculation of the ideal dose for each patient considering their genomics and drug interaction. To this end, we have applied best practices of quantum software engineering to the development of quantum/classical software systems.
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Acknowledgments
This work is part of the QHealth: Quantum Pharmacogenomics Applied to Aging (2020 CDTI Missions Program) project funded by the Spanish Ministry of Science and Innovation and European Regional Development Fund (ERDF). We would like to thank all the members of the project for their help and collaboration.
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Hevia, J.L., Murina, E., MartÃnez, A., Peterssen, G. (2024). Quantum Software Engineering and Programming Applied to Personalized Pharmacogenomics. In: Exman, I., Pérez-Castillo, R., Piattini, M., Felderer, M. (eds) Quantum Software. Springer, Cham. https://doi.org/10.1007/978-3-031-64136-7_11
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