Friday, December 23, 2016

Aging.AI 2.0 launches to provide a biomarker of aging with less parameters

Aging.AI 2.0 is now available for testing. Please use your recent blood test to guess your age. 

The system is available at http://www.Aging.AI

Citation (full text):
Putin, Evgeny, Polina Mamoshina, Alexander Aliper, Mikhail Korzinkin, Alexey Moskalev, Alexey Kolosov, Alexander Ostrovskiy, Charles Cantor, Jan Vijg, and Alex Zhavoronkov. "Deep biomarkers of human aging: Application of deep neural networks to biomarker development." Aging 8, no. 5 (2016): 1-021.

Sunday, August 14, 2016

"Regeneration Intelligence" For Diagnosis of Lung and Liver fibrosis and Glaucoma

Collaboration of Insilico Inc. with Atlas Regeneration Inc, Vision Genomic Inc and Howard University has given two high impact papers to explain use of newly developed Regeneration Intelligence tool for the identification of perturbation in pathways of lung and liver fibrosis and glaucoma. It can be used as diagnosis tool for the fibrosis that is often mis-diagnosed.

A) Lung and Liver Fibrosis

Fibrosis is a age related condition that is marked by the accumulation of extracellular matrix that occurs in wide range organs. This leads to changes in the structural and functional properties of organ that leads to pathological conditions. Lungs and liver are the most commonly affected by fibrotic situation leading to development of idiopathic pulmonary fibrosis (IPF) and hepatic fibrosis.

Figure 1 a - c
The figure 1 a) & b) shows venn diagram of common pathway up-regulated and down regulated respectively for lung and liver fibrosis c) venn diagram d) PAS values for 20 common signaling pathway of lung and liver fibrosis

By their new Regeneration Intelligence algorithm they were able to pin down to TFG-beta, IL6 and ILK signaling pathways, which were found to be conserved in fibro-genesis. The software provides a validated mathematical frame work for assessment of signaling pathway alteration that drives the fibrosis in organs like lungs and liver.

This work supports a theory that conserved signaling elements may shared by various fibrotic organs. It provides a new evidence that evolutionary conserved pathways can be used as therapeutic drug targets. The work was highlighted in Eureka Alert Science Magazine and Business Standard news letter. The scientific paper can be downloaded from this here.

B) Glaucoma 

Glaucoma is also kind of fibrotic condition. Primary open angle glaucoma (POAG) is most common form of glaucoma that is characterised by free aqueous humor (AH) outflow and logging between iris and cornea that do not get drained from trabecular meshwork (TM) due to clogging of the channels.  This causes damaging effect on the mesh like Lamina Cribrosa (LC) through which optic nerve bypass. They have used a software suite, AMD medicine to understand the molecular pathway that causes the accumulation of AH and prevention of its outflow by carrying out intracellular signalling pathway activation (SAP).                           Accepted paper can be found here

Figure 2:  It shows the pathology of formation of glaucoma due to increase intra ocular pressure due to blockage in the removal of AH. A) shows TM and optical nerve head containing TC. B) shows TM located between cornea and iris. It shows that AH produced by ciliary body is moved towards anterior end shown by arrows and expelled into schlemm's canal via TM.  C) shows flow of AH into schlemm's canal through juxtacanaliular tissue. AH outflow is blocked due to clogging in TM leads to increase in intra ocular pressure. D) Optic nerve head containing axon of RGC and lamina cribrosa structure. E) shows morphology of collagen fibres of lamina cribrosa. F) SEM trabecular meshwork and G) SEM of lamina cribrosa.

They have found that  TGF-beta causes activation of pro-fibrotic pathway in TM and LC. This activated pro-fibrotic pathway causes extracellular matrix re-modelling in TM and LC. This makes TM less efficient in draining the AH. This causes LC more susceptible to damage due to increase intra ocular pressure caused because of increased AH. They propose molecular pathways that could be used for developing therapeutic intervention against glaucoma. The significance of the finding was recently discussed Eureka Alert Science Magazine and Medical News. These two papers shows a proof principle that there are some common age related signalling pathways that are shared by organs. Regeneration Intelligence based mathematical frame work gives an opportunity to explore this tool towards study of common signatures for age related fibrosis in other organs of human body. This may give us an opportunity to design an effective therapeutic strategy to fight age related disease like fibrosis.

Friday, July 15, 2016

Companies Coming Together To Fight Ageing

Mergers Can Solve Ageing Problem!!

Merger of scientific brain may help to find out newer ways to fight ageing.

A. LifeExtension

Life extension is currently a 35 billion dollar supplement producing company. The company has nearly 20 years history of developing innovative products to fight ageing and age related diseases. History of the company in antiaging research:

* 1983: Their research showed that low doses of aspirin may help in reducing the incidence of heart attack. They also recommended the use of co enzyme Q10 (CoQ10) as an anti ageing nutrient.
* 1992: Introduction of melatonin in America for anti-ageing therapy
* 1996: Published research to check the level of fibrinogen as risk factor for cardiovascular disease
*1997: Introduced s-adenosyl methionine (SAM) for alleviating depression, arthritis and liver diseases.
*2000: They found that taking hight level of antioxidants for extended period of time helps in reducing the atherosclerosis
*2006: A relatively better form of CoQ10 that is absorbed relatively better than parent product.
*2010: They stressed that pomogranate, resveratrol and quercetin may help in fighting ageing.
*2012: Introduced a product featuring oleuropein that helps in modulation of arterial resistance and stiffness.
*2013: Introduction of supplements that consists of polyphenols gastrodin that works as brain shield against antioxidants, inflammatory and excitatory damage.
*2014: Introduction of formulation that supports adenosine monophosphate activated protein kinase (AMPK)
*2015: Introduction of pollen extract that promote prostate function and healthy urination.

B. Insilico Inc Collaboration With Life Extension

In silico Inc. has been a major point of attraction in my blogs about ageing. The company is being operated from John Hopkins University. They are a group of computational biogenrontologists who believe that they can cure ageing. The group is extensively working in the field of developing computational models for coming closer and closer to fight ageing.

Insilico Inc. joins hands with larger number of pharmaceutical company in the pursuit of slowing down the ageing process. Recently they have collaborated with Life Extension (a supplement producing company) with the aim of slowing that ageing process. With the long history of Life extension and progressive nature of Insilico Inc. there is a possibility of introduction of range of geroprotectors that may slow down the ageing process early next year (News Published: a) and b)

C. In Silico Inc. Collaboration With BioTime Inc.

BioTime Inc is a clinical stage regenerative medicine company that was focuses on the development of newer technologies fight ageing via. pluripotent cells. Unlike other pharmaceutical products that works on the basis of molecular drug targets, pathways and genetic expression profiles; BioTime's approach has been at the cellular level. Where the pluripotent cells can replace the damaged cells to provide therapeutic output. The simple it sounds the more complex it is. Regeneration of tissue from embryonic cells and formation of scar tissue for an adult for therapeutic purpose is extremely complex process. Hence, in June 2016 they collaborated with Insilico Inc. to study this complex process via machine learning method. The idea of this collaboration was combine the technological advances of AI by Insilico Inc. and pluripotent cells based therapy by BioTime to produce next generation therapeutic solutions for cancer and age related disease..

In this context, AI was developed by BioTime Inc called as Embryonic.AI. It is transcriptomic based classifier that can be used for searching the queries to check how much close is the sample to the embryonic state. Embryonic. AI is basically a deep learning machine that is validated based on the thousands of samples that representative of the human embryonic stem cells. This includes human embryonic stem cells (ESC), induced pluripotent stem cells (IPSC), embryonic progenitor cells (EPC), adult stem cells (ASC) and adult cells (AC). Once the query it provided to the AI it gives out score that acts as a measure of the development stage of cells. Where ES=1 represents embryonic state and ES=0 represents adult cellular states. Here is link to the FAQs that can be used for more details

Monday, May 30, 2016

Deep Neural Networks: New Drug Discovery To Repurposing

Yet another exciting paper published by InSilico Inc in addition to their work on developing the model based on Deep Neural Networks on the prediction of human age... (paper can be downloaded here). Summary of the work can be seen in our previous blog posts here

This month paper was published about the use of Deep Neural Networks (DNN) in new drug discovery and repurposing using transcriptomic data.

The paper got recently published in Molecular Pharmaceutics....... can be downloaded from here

Deep learning is an artificial intelligence (AI). It utilises higher level or multilayer of the neuron to model the high level of abstraction of data. 

The paper published clearly shows that AI neural network was able to predict the therapeutic use of a large number of medicine depending on gene expression data that is obtained from high-throughput experiments on human cell lines.

The significance of the work got recently published in Eureka News Alert

Image from Paper that Shows Training of DNN for Drug Discovery
The study uses 678 drugs affecting A549, MCF-7 and PC-3 cell lines from LINCS library developed by NIH that is linked to 12  therapeutic categories established by MeSH (Medical Subject Heading). The library is maintained by NLM. So basically researchers trained DNN by utilising both  transcriptomic data using a scoring algorithm for samples that are perturbed with different concentration of the drug after 6 or 24 hours. The cross-validation of the model showed that DNN achieved 54.6% accuracy in correctly predicting one out of 12 therapeutic categories for each drug. Interestingly, a large number of the drugs that were misclassified by DNN was found to have dual therapeutic utility. This suggests that may be the confusion matrix used for DNN can be used for drug repurposing

This is the first study where DNN based model was developed on the basis of transcriptomic data for predicting the therapeutic use of the drug. Hence, it was proof of concept study that DNNs can be used for annotation of drugs using transcriptomic signatures. Hence, they used this finding to progress towards the development of a pipeline program in order to accelerate the preclinical of drugs for most any therapeutic category. They believe that if this technique can be extrapolated to invite signatures then maybe this can double the number of molecules in drug discovery studies. 

Sunday, April 10, 2016

Anti-ageing Molecules Translation to Clinic And Conference

Aging is a major risk factor for a number of chronic diseases, including cancer, type II diabetes, atherosclerosis, hypertension, myocardial infarction, stroke, and neurodegenerative diseases. In animal models, treatments that extend lifespan often protect against these chronic diseases and there is a reason to believe that a similar approach might work in humans. Therefore, the geroscience concept, which aims to prolong the healthy state of the human body, is likely to become a key paradigm of biomedicine in developed countries in coming decades (Seals et al., 2015) .

Today, more than 200 substances belong to this group, each reported to slow aging and/or increase lifespan in a variety of organisms, including yeasts, nematodes, fruit flies, and rodents, according to the database. Despite such an impressive rate of discovery, not a single geropro- tector has yet reached the pharmaceutical market as a recognized intervention targeting aging.

This is due following reasons

a) There is no unified mechanistic concept of aging, and primary triggers of aging are still poorly understood.

b) There is no comprehensive system of objective human aging biomarkers.

c) Aging is not recognized as a disease or a complex of syndromes

d) The scientific community has no consensus view on the concept of geroprotectors, on selection criteria for potential geroprotectors, or on the development of appropriate classification schemes, efficiency ratings, and approaches for predicting and modeling geroprotective properties.

This issue has been previously discussed in researchgate and other sites..

According to GeneAge Database....there are around 1825 genes whose knockdown, knockout or overexpression is known to result in an increase in life span.

In recent review article published by Dr. Alex Zhavoronkov discusses about the primary selection criteria for the geroprotectors..........................................................Click here for downloading the article

Most commonly used geroprotectors

Dihydroergocristine methanesulfonate
Ellagic acid

All these molecules are et

In addition the there is a conference on longevity in here for registration

Recent studies shows that these molecules may be anticancer drugs but may also be useful in attaining longevity. People interested in longevity conference and to learn more about the recent advancement in cancer therapy can visit the above page.