This is based on the concept that precision medicine can be applied to improve individual well-being. The concept combines the study of the genome with a diverse range of biochemical and microbiological data.
The ability to integrate the information that our biomarkers provide us with our genetic information can be crucial in initiating a specific preventative treatment or attempts to improve our health. For example, this concept would be essential to a program which sought to improve the glycemic profile in cases where our genes show that a specific type of individual or group have a propensity to suffer from diabetes.
Dr. Moisés de Vicente – Medical Director Neolife Madrid
A study published in the Nature Biotechnology journal suggests that the continuous collection of personal biological data can improve our understanding of health and diseases.
Each person is unique and in essence is unrepeatable. Not only on an intellectual level but also on a sentimental and ‘way of being’ level. Each individual contains an immense amount of biological data that make us different from each other. This data set includes our genomic information, metabolites, proteins, microbiome composition, etc. The interaction of all these systems that coexist in our body, and how they react to external or internal aggression, is what will determine our disease state (human condition). In this way, if we could understand the data in greater detail, as well as the intrinsic relationships which exist between them then we could obtain some crucial information to allow us to preserve our health. 
This concept is the basis for the 100 Wellness Project, whose preliminary results have recently been published in the Nature Biotechnology journal and suggest that the continuous collection of personal biological data can improve our understanding of health and diseases. The researchers collected all types of data (genomic, biochemical and personal) from 108 patients over a period of 3 months. Also, through the use of digital instruments they collected and quantified details from their daily activities. The results obtained focused on four types of diseases that are related to aging: cardiovascular risk, malnutrition, diabetes and inflammation. They used powerful analytical tools which allowed them to integrate all the information together. This process is known as “Scientific well-being” which is a new concept that precision medicine can be applied to improve individual well-being. The concept combines the study of the genome with a diverse range of biochemical and microbiological data. Such a process enables us to integrate the information that our biomarkers provide us with our genetic information that can be crucial to, for example, initiating a specific treatment or program in order to improve our glycemic profile in cases where our genes show that there is a propensity for the patient in question to suffer from diabetes and our markers do not yet meet the criteria established by the different societies to provide a definitive diagnosis. At Neolife we use a significant amount of biomarkers which allows us to establish the health status of our patients. In addition to this, we conduct genetic studies that allow us to establish the likelihood that a chosen person may suffer a disease. Then using this knowledge we carry out preventive medicine programs that allow us to optimize our parameters in the most efficient way in order to avoid the occurrence of subclinical injury, or, if this is already present, to delay the progression to the greatest extent possible.
BIBLIOGRAPHY
(1) Price ND, et al. A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nat Biotechnol. 2017 Jul 17. doi: https://dx.doi.org/10.1038/nbt.3870 (2) Institute for Systems Biology and Arivale “Pioneer 100 Study” Establishes Foundation for New Industry of Scientific Wellness. https://www.systemsbiology.org/news/2017/07/17/pioneer-100-study/ (3) Cross R. Scientific wellness’ study—and a famed biologist’s spinoff company—divide researchers. 2017. Doi: https://dx.doi.org/10.1126/science.aan7123