Introduction

Quantum computing has the most varied applications in the field of medicine and health: drug discovery, reconstruction of DNA sequences, solving genome assembly tasks, classification of medical images, detection of COVID-19 patients with X-rays, etc.

One of the most interesting applications is to predict the interaction and the effect of a drug on a given organism, which is impossible to obtain in practical response time with classical computers due to the large number of variables to be dealt with.. Therefore, only quantum computing will allow us to adequately predict diseases and patient outcomes and make precision medicine a reality. Precision medicine (finding the precise drug for the most specific target) has evolved at an exponential pace over the last few years and fuelled the development of person-centred medicine [1]. One of the key elements in this regard has been the scientific knowledge derived from panomics, he combined analysis of multi-dimensional genomic, transcriptomic, proteomic, and metabolomic data [2]. In fact, there is no personalized medicine without pharmacogenetics or pharmacogenomics, it does not make any sense [3].

QHealth: Quantum pharmacogenomics applied to ageing

Genomics is one of the most significant precision medicine drivers and is considered by many experts as the one with most disruptive potential in healthcare [1]. In our case, we are interested in improving elderly drugs treatment, and we have been working in the QHealth project: “Quantum pharmacogenomics applied to aging”. The overall objective of the project is, first and foremost, human: To increase the longevity and quality of life of the elderly, something to which QHealth will contribute thanks to research into the relationships between genetic determinants and other variables in the health trajectory of the elderly throughout their lives, including the reaction that drugs can trigger in the elderly, in such a way as to predict the possible adverse effects that a given drug may have on the health of an elderly person based on their history of taking drugs, the effects of the drugs and their physiological and genetic determinants.

As stated by Dr. Adrián Llerena, President of the Spanish Society of Pharmacogenetics and Pharmacogenomics, member of the Pharmacogenomics Working Party of the European Medicines Agency (EMA) and Scientific leader of the QHealth project, “If we want a more efficient system that adjusts the medication to people and not to averages, we will have to include biomarkers in the portfolio of services” [4].

For this reason, the quantum treatment of biomarkers occupies a strategic place in the research and development of the QHealth project, and is a determining factor among the indicators to measure the results of this project:

·       Genetic factors (biomarkers) included in the analysis

·       Pharmacological interactions between the different drugs included in the analysis.

·       Potential beneficiaries: the elderly population.

To achieve this goal, QHealth has designed the scientific, methodological and technological models necessary for the conception of the scientific and technical foundations of a hybrid classical/quantum system, capable of performing optimizations and simulations impossible to perform in reasonable execution times in classical computers, which, thanks to the integration with classical health applications, provides the results of the system to health professionals in charge of prescribing drugs to the elderly. The hybrid system will not only have a human impact, but it will also have an economic impact because it will make it possible to optimize the investments that health systems make in financing drugs and in dealing with the adverse effects that drugs often cause in the elderly.

The project has a total budget of 5,160,477.00 euros and has received a grant of 3,671,281.69 euros from the CDTI (Center for the Development of Industrial Technology of Spain). The project has been supported by the Spanish Ministry of Science and Innovation and by the ERDF (European Regional Development Fund). It involves a multidisciplinary team of researchers and technologists from the aQuantum (by Alhambra IT), Gloin, and Madrija companies and the University Institute of Biosanitary Research of Extremadura in collaboration with the Pharmacogenetics and Personalized Medicine Unit, the University of Extremadura, and the University of Castilla-La Mancha.

Therefore (Figure 1) QHealth builds a hybrid quantum system combining health-care applications and data analytics with quantum computing. Quantum technologies already allow, at the present time, to perform optimizations and simulations whose realization in classical hardware is not possible within acceptable deadlines. This hybrid system, in combination with classical health applications, will give its outputs to medical professionals involved in prescribing drugs to elderly adults. In a further extension, we also envisage application in the case of younger persons with difficult drug treatment and health conditions, trying to reduce the negative impacts of drugs due to their correlation and mutual side-effects when used in combination. Using the case histories and the socioeconomic and genetic variables of the persons being analysed, we can then also make recommendations for suitable drug treatments and provide risk assessment before they are prescribed.