Quantified Longevity Guide

Quantified Longevidy Guide (QLG) – is a dynamic multidiscipinary research and development project dedicated to mathematical diagnostic modeling of aging and aging-related diseases, for the purposes of their early preventative and personalized therapy.

Quantified Longevity Guide develops a 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 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 in terms of methodology: Providing 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 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.

In addition to diagnostic modeling, QLG team of experts in bioinformatics, biology, social and research aspects of aging and aging-related diseases performs consultancy, analysis and education services for the public and the professional community on aging and longevity research, facilitates the communications between the public and researchers on the one hand, and between the researchers and potential sponsors and decision makers on the other.

 QLG is a project of the Israeli Longevity Alliance (ISRLA) in cooperation with Vetek (Seniority) Association – the Senior Citizens Movement (Israel)

The QLG project has been a recognized commitment at the European Innovation Partnership on Active and Healthy Aging (EIP-AHA) within the action group: A3 Lifespan Health Promotion & Prevention of Age Related Frailty and Disease


It was also included in the “Directory of Research on Ageing in Africa 2004-2015″ (UN, 2015), pp. 80-81 of the report. Full report

The results of this project have been presented at international conferences on aging and disease of the International Society on Aging and Disease (ISOAD) in Beijing, China, in 2014, Stanford, US, in 2016, and Nice, France, in 2018 and other conferences. 


Please address project-related correspondence to Ilia Stambler ilia.stambler@gmail.com

Selected Publications

Blokh D, Gitarts J, Stambler I. An information-theoretical analysis of gene nucleotide sequence structuredness for a selection of aging and cancer-related genes. Genomics & Informatics, 18(4), e41, 2020. https://doi.org/10.5808/GI.2020.18.4.e41

Mizrahi EH, Lubart E, Stambler I, Adunsky A. The association between Norton scale gain and functional outcome among older hip fracture patients. Nursing Open, 8(2), 539–545, 2021. https://doi.org/10.1002/nop2.658

Blokh D, Stambler I, Gitarts J, Pinco E, Mizrahi EH. Information-theoretical analysis of blood biomarkers for age-related hip fracture risk evaluation. Applied Medical Informatics, 43(1), 14-23, 2021. https://ami.info.umfcluj.ro/index.php/AMI/article/view/797

Stambler I and Moskalev A. Editorial: clinical evaluation criteria for aging and aging-related multimorbidity. Frontiers in Genetics. Genetics of Aging, 12:764874, 2021. https://doi.org/10.3389/fgene.2021.764874

Stambler I, Alekseev A, Matveyev Y, Khaltourina D. Advanced pathological ageing should be represented in the ICD. Lancet Healthy Longevity, 3(1), E11, 2022. https://doi.org/10.1016/S2666-7568(21)00305-6

Blokh D, Stambler I, Lubart E, Mizrahi EH. An information theory approach for the analysis of individual and combined evaluation parameters of multiple age-related diseases. Entropy, 21(6), 572, 2019. https://doi.org/10.3390/e21060572

Blokh D and Stambler I, 2014. Estimation of Heterogeneity in Diagnostic Parameters of Age-related Diseases. Aging and Disease, 5, 218-225 http://www.aginganddisease.org/EN/10.14336/AD.2014.0500218

Blokh D and Stambler I, 2015. Information theoretical analysis of aging as a risk factor for heart disease. Aging and Disease, 6, 196-207 http://www.aginganddisease.org/EN/10.14336/AD.2014.0623

Blokh D and Stambler I, 2015. Applying information theory analysis for the solution of biomedical data processing problems. American Journal of Bioinformatics, 3 (1), 17-29 http://thescipub.com/abstract/10.3844/ajbsp.2014.17.29

Blokh D, Afrimzon E, Stambler I, Korech E, Shafran Y, Zurgil N, Deutsch M, 2006. Breast cancer detection by Michaelis-Menten constants via linear programming. Computer Methods and Programs in Biomedicine, 85, 210-213 http://www.ncbi.nlm.nih.gov/pubmed/17188399

Blokh D, Stambler I,  Afrimzon E, Shafran Y, Korech E, Sandbank J, Orda R, Zurgil N, Deutsch M., 2007. The information-theory analysis of Michaelis–Menten constants for detection of breast cancer. Cancer Detection and Prevention, 31, 489-498 http://www.ncbi.nlm.nih.gov/pubmed/18061365

Blokh D, Zurgil N, Stambler I, Afrimzon E, Shafran Y, Korech E, Sandbank J, Deutsch M., 2008. An information-theoretical model for breast cancer detection. Methods of Information in Medicine, 47, 322-327 http://www.ncbi.nlm.nih.gov/pubmed/18690365

Blokh D, Stambler I, Afrimzon E, Platkov M, Shafran Y, Korech E, Sandbank J, Zurgil N, Deutsch M., 2009. Comparative analysis of cell parameter groups for breast cancer detection. Computer Methods and Programs in Biomedicine, 94, 239-249 http://www.ncbi.nlm.nih.gov/pubmed/19231022

Blokh D, 2013. Information-Theory Analysis of Cell Characteristics in Breast Cancer Patients. International Journal on Bioinformatics & Biosciences (IJBB), 3 (1) http://wireilla.com/papers/ijbb/V3N1/3113ijbb01.pdf

Stambler I, 2015. Stop Aging Disease! ICAD 2014. Aging and Disease, 6 (2), 76-94 http://www.aginganddisease.org/EN/10.14336/AD.2015.0115

Jin K, Simpkins JW, Ji X, Leis M and Stambler I. 2015. The Critical Need to Promote Research of Aging and Aging-related Diseases to Improve Health and Longevity of the Elderly Population. Aging and Disease, 6(1), 1-5 http://www.aginganddisease.org/EN/10.14336/AD.2014.1210

Blokh D and Stambler I, 2017. The use of information theory for the evaluation of biomarkers of aging and physiological age. Mechanisms of Ageing and Development, 163, 23-29 https://www.sciencedirect.com/science/article/pii/S0047637416301567?via%3Dihub

Blokh D, Stambler I, Lubart E, Mizrahi EH, 2017. The application of information theory for the estimation of old-age multimorbidity. Geroscience, 39(5-6), 551-556 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5745215/

Blokh D and Stambler I, 2017. The application of information theory for the research of aging and aging-related diseases. Progress in Neurobiology, 157, 158-173 https://www.sciencedirect.com/science/article/pii/S0301008215300599

Stambler I, 2017. Recognizing degenerative aging as a treatable medical condition: methodology and policy. Aging and Disease, 8(5), 583-589 http://www.aginganddisease.org/EN/10.14336/AD.2017.0130