Abstract 13
 
Population specific deep biomarkers of human aging Print
 
P. Mamoshina1,2, K. Kochetov3, E. Putin3, A. Aliper3, F. Cortese4,5,6, W.-S. Lee7, S.-M. Ahn7, N. Skjodt8,9, O. Kovalchuk8,9, A. Zhavoronkov3,5
1Pharma AI, Insilico Medicine, Inc, 2Computer Science Department, University of Oxford, Oxford, United Kingdom, 3Pharma AI, Insilico Medicine, Inc, Baltimore, MD, United States, 4Department of Biomedical and Molecular Sciences, Queen’s University, Kingston, ON, Canada, 5Biogerontology Research Foundation, Oxford, United Kingdom, 6Canadian Longevity Alliance, Kingston, ON, Canada, 7Gachon University Gil Medical Center, Incheon, Republic of Korea, 8Canada Cancer and Aging Research Laboratories, Ltd, 9University of Lethbridge, Lethbridge, AB, Canada
 
Restricted experimental possibilities of studying human aging and the overall low translation rate to the clinic in most of therapeutic areas complicates the search for desirable anti-aging therapies, and so far only a few geroprotectors (i.e anti-aging molecules) have shown potential efficacy in humans. Biomarkers of aging, also known as aging clocks, are promising tools with the potential to track age-related changes and evaluate the therapeutic efficacy of clinical healthspan-extending interventions according to their effect upon levels of recognized biomarkers of aging, without the need to resort to long and costly longitudinal studies on lifespan. Previously, we showed that blood biochemistry could be used to assess the biological age of the patient using blood test values (1). Here we report a series of population-specific deep learning-based aging clocks and the list of the most important blood markers in age prediction for each population.
1. Putin, E. et al. Deep biomarkers of human aging: Application of deep neural networks to biomarker development. Aging 8, 1021-1033 (2016).
Disclosure: Nothing to disclose


Assigned speakers:
Polina Mamoshina , Insilico Medicine, Inc , Oxford , United Kingdom

Assigned in sessions:
13.09.2017, 10:30-12:00, Innovation Forums, Artificial intelligence and blockchain in healthcare, Kairo 1-2