This open access book explains the state of the art in quantum software engineering and design, independent of specific hardware. It covers theoretical aspects of quantum software and classical software engineering concepts such as agile development approaches, validation, measurement and deployment applied in a quantum or hybrid environment, complemented by a number of different industry applications.

The book is composed of three parts.

       I.          Aspects of Quantum Software Theory

     II.          Quantum Software System Design

   III.          Quantum Software Laboratory

The chapter “Quantum Software Engineering and Programming Applied to Personalized Pharmacogenomics” is part of the third part of the book and refers to several software applications and corresponding laboratory experiences to understand their implications in practice and to avoid repeating past mistakes.

The structure of the chapter “Quantum Software Engineering and Programming Applied to Personalized Pharmacogenomics” [1] is as follows:

1.     Introduction

2.     Quantum Health

3.     Qualitative Description of the Computational Problem

4.     Analytical Description of the Computational Problem

5.     QHealth Information System

6.     Conclusion

7.     References

The authors believe that software systems developed for healthcare must be high quality, extensible, scalable, high performance, and highly secure, given their intended use. Therefore, building reliable software systems for healthcare requires the application of software engineering best practices and the team’s experience in developing critical software solutions.

In this sense, they emphasize that the implementation of projects of this type involving quantum computing has the added complexity that quantum software engineering is just taking its first steps and that the experience accumulated in the design, development and implementation of this type of projects is just accumulating its first use cases. In addition, it has been necessary to ensure the delivery of high quality and professionally tested quantum software solutions, to design a security model specific to quantum projects, to define a management framework for quantum computing services, and to design a valid model for the governance and management of quantum architectures and platforms.

In this chapter, the authors show that providing personalized drug therapy to polymedicated patients is a very complex situation, as not even the most powerful supercomputer in the world could process the enormous number of variables required in a reasonable amount of time. Fortunately, quantum computing is opening up new possibilities in this area, especially thanks to its ability to efficiently combine a large number of variables.

To address the feasibility of applying these new technological possibilities to health services, the authors present the basic idea of an extensible quantum algorithm to deal with genetic polymorphisms, pharmacological polytherapy, and clinical condition, and the implementation of a prototype that allows the calculation of the ideal dose for each patient, taking into account their genomics and drug interactions. To this end, the authors have applied in the PoCs and prototype of the project “QHealth: Quantum Pharmacogenomics applied to aging” the best practices of quantum software engineering to the development of quantum/classical software systems using the QuantumPath® platform.