Aging.AI1.0


How old by a basic blood test!

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This is a deep-learned predictor of your age made with a deep neural network trained on hundreds of thousands anonymized human blood tests. Enter your data below and Aging.ai will guess your age and… gender (no pun intended if we miss). Anonymized statistical data was processed in collaboration with the largest independent diagnostics provider in Eastern Europe, Invitro. No patient records were used in the study.

Please use the following citation when referencing Aging.AI 1.0:
Putin E. et al, Deep biomarkers of human aging: application of deep neural networks to biomarker development. Aging (Albany N.Y.) 8, 1021–1033. doi: 10.18632/aging.100968




First choose the sample metric: 

Enter your weight: kg         Enter your height: cm       Do you smoke?  
Blood Marker* Your Value Units and Sample Metric***
Albumin** 35 - 52 g/l
Glucose** 3.9 - 5.8 mmole/l
Alkaline phosphatase** 20 - 120 U/l
Urea**(BUN) 2.5 - 6.4 mmole/l
Erythrocytes** (RBC) 3.5 - 5.5 106 /mcl
Cholesterol** 3.37 - 5.96 mmole/l
RDW** 11.5 - 14.5 %
Alpha-2-globulins** 5.1 - 8.5 g/l
Hematocrit** 37 - 50 %
Lymphocytes** 20 - 40 %
Alpha-amylase 28 - 100 U/l
ESR (by Westergren) 2 - 30 mm/h
Bilirubin total 1.7 - 21 mcmole/l
Bilirubin direct < 4.6 mcmole/l
Gamma-GT < 32 U/ml
Creatinine 53 - 97 mmole/l
Lactate dehydrogenase < 248 U/l
Protein total 64 - 83 g/l
Alpha-1-globulins 2.10 - 3.50 g/l
Beta-globulins 6.0 - 9.4 g/l
Gamma-globulins 8.0 - 13.5 g/l
Triglycerides 0.68 - 1.90 mmole/l
Chloride 101 - 110 mmole/l
HDL Cholesterol < 3.3 mmole/l
LDL cholesterol (by Friedewald) 1.81- 4.04 mmole/l
Calcium 2.15 - 2.65 mmole/l
Potassium 3.4 - 5.1 mmole/l
Sodium 136 - 146 mmole/l
Iron 7.20 - 25.90 mcmole/l
Hemoglobin 11.7 - 15.5 g/dl
MCH 27 - 31 pg/cell
MCHC 31.5 - 35.7 g/dL
MCV 82 - 95 fl
Platelets 150 - 450 103 /mcl
Leukocytes (WBC) 4 - 10 103 /mcl
ALT < 41 U/l
AST < 47 U/l
Basophils < 1.0 %
Eosinophils < 5.0 %
Monocytes 3 - 9 %
Neutrophils 45 - 70 %
Show Additional Markers
(improves accuracy by ~10%)
* This should be in your clinical biochemistry blood test results
** Required parameter for minimal prediction accuracy of 70% within 10 year frame
*** We can not show you reference values before knowing your age apriori, so this is only a reference metric

Click on a marker to know more about what it is. Knowing your blood biochemistry markers is the new ABCs. Everyone should know it.

Our team is expert in human gene expression data analysis, biomarker development and drug discovery for aging research, so this predictor is a small by-product of our work. But if we see that people like it, we will develop a biomarker, where you will be able to log in and track the changes in predicted age while testing some of the interventions like diet, exercise or supplements to see if any of these “make you younger”.

If you decide to use this system, all data submitted will be used for research purposes and will be used to help train the predictor, so it will not be possible for us to delete it. Please do not submit anything if you don’t want your data to be used freely.

Since it is basic blood biochemistry and we don’t know who you are, we don’t see a reason not to use it. You are probably much more exposed if you are posting pictures on social networks. Our team’s mission is to extend human longevity, do it in humans with a goal of producing 10 billion quality-adjusted life years (QALY) to Facebook users by 2020 and develop tools for anyone to engage in aging research. Please let us know if we guessed right and share your results on Facebook.

After extensive testing we may publish this multi-DNN system in a peer-reviewed journal as we usually do. In the meantime, please check out some of our publications.

Please see our press release at EurekAlert

Here is a 5-minute video if you would like to learn more about Insilico Medicine: enter image description here


How to partner with us

We are driven by our mission to extend healthy human longevity and when you partner with us, you contribute to solutions that benefit everyone.

If you’re interested in sponsoring a research project or simply accessing our extensive research infrastructure, we’ll help you launch a successful and rewarding collaboration with researchers who are leaders in their fields.

We closely work with academic partners to develop deep biomarkers of human aging and health status.

View partnership case studies.

Check out Insilico Medicine publications

Contact the Pharma.AI research team for inquiries about academic and sponsoring opportunities at poly(at)pharma.ai.


In collaboration with:
DNNs were trained on NVIDIA GPU


We thank NVIDIA for providing valuable GPU equipment for deep learning to Insilico Medicine.