Note 1. It should be noted that the current project does not restrict itself from the outset to any particular kinds of parameter data or hypothesis. The information theoretical approach allows to utilize any kind of data, at any level, into a single open and upgradeable diagnostic model. Thus it can, for example, combine diverse biochemical, molecular-biological, cellular, tissue, physiological, functional and other parameters related to aging. Thus the more parameters of different kinds we may be able to obtain, and the larger the investigated sample that we will be able to obtain – the stronger and more informative and predictive the diagnostic model will be. The team can also be expanded as necessary, especially with the addition of physicians, biologists and data technicians. New collaborations can be formed with relevant organizations, particularly those involved in biomedical data mining, diagnostic research and health information distribution. Due to the open and cumulative nature of this project, it can be scaled up to almost any dimension, depending on the funding, number of people involved and accessibility of data.
Note 2. The sought investments sums mentioned above are in USD, the minimum investment is for 1 year, and the required investment is for the complete project period of 3 years.
CD Technologies – Comorbidity Detection Technologies (CDT) – is a dynamic multidisciplinary company dedicated to mathematical diagnostic modeling of aging and aging-related diseases, for the purposes of their early preventative and personalized therapy. CDT develops the practically applicable and at the same time sophisticated expert software system for indication of physiological age, for early diagnosis of aging-related ill health and personalization of aging-related and healthspan extending treatments – “The Quantified Longevity Guide – QLG”. The system will facilitate early detection and corresponding preventive early treatment of major aging-related diseases, such as cancer, Alzheimer’s disease, heart disease and diabetes, based on the assessment of physiological age.
The main advantage of the proposed system is its methodology that can provide an integrated approach that will take into consideration the non-linear interrelation of a multitude of parameters – biomarkers and intervention factors, using information theoretical measures, such as entropy and mutual information, rather than linear statistical measures. The proposed Expert Software System will use the methodology of information theory that will uniquely allow the selection of the most beneficial and economical individual factors and factors’ combinations for combating chronic age-related diseases and increasing the health span, indicating physiological age as a cost-effective method of preclinical diagnosis for a variety of chronic age-related diseases, while enabling long-term evaluation and prediction of effectiveness of individual and combined therapies.
Endpoint product capabilities: Basic computational software technologies, algorithms, diagnostic models, tools and platforms will be developed that will serve physicians, biomedical researchers and general health-conscious consumers.
See: Blokh D and Stambler I, 2016. The application of information theory for the research of aging and aging-related diseases. Progress in Neurobiology, http://dx.doi.org/10.1016/j.pneurobio.2016.03.005