Insilico to present the latest advances in AI for drug discovery at Advanced Pharma Analytics Summit

Tuesday, January 16th, 2018, Baltimore, MD - Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery, announces the presentation of Polina Mamoshina, Senior Research Scientist involved in multiple deep learning projects at the Pharmaceutical Artificial Intelligence division of Insilico Medicine, at 5th annual Advanced Pharma Analytics Europe Summit, January 31, 2018.

The presentation will cover the recent advances in the applications of generative adversarial networks (GANs) for new molecules development in drug discovery. The fundamental principle of GANs is adversarial training based on game theory results: competition between the Generative and Discriminative networks leads to joint evolution and almost perfect results. Insilico Medicine was the first company to integrate the advances of GAN architecture into a comprehensive drug discovery pipeline with the goal to enable the deep neural networks to produce perfect molecules for the specific set of diseases including different cancers, neurodegenerative diseases such as Alzheimer's disease, virus infections, and more. 

"Generative adversarial networks (GANs) revolutionised deep learning and found its applications in several areas, including realistic image synthesis, text-to-image synthesis or even animating movie, etc Vast amounts of data collected within pharmaceutical industry can be utilised to build similar models. Nowadays, the target itself is not a competitive advantage, in most cases the value is in a molecule. At Insilico Medicine, we build GANs that work on multiple representations of the chemical structures to expand and navigate through the chemical space. Automated discovery of novel chemotypes with certain properties against specific targets offered by GANs shows a great promise to significantly facilitate early drug design stages", said Alex Aliper, President of EMEA in Insilico Medicine, Inc.

"It is a privilege for me to speak alongside the leaders in the industry at the 5th annual Advanced Pharma Analytics event. As usual, it brings together thought experts to discuss new technologies on drug discovery. Technologies based on AI have a great potential to change drug discovery process dramatically mainly by speeding it up introducing a limited amount of highly promising molecules instead of thousands with unknown activities and possibly increase the drug space, finding new drugs, a new mechanism of action, new chemistry", said Polina Mamoshina, Senior Research Scientist in Insilico Medicine, Inc.

The 5th annual Advanced Pharma Analytics Europe Summit is dedicated to supporting the growing biopharmaceutical community and provides opportunities to showcase advanced pipelines to maximize successful outcomes with cutting-edge data science and analytics. The meeting will transpire 30-31 of January 2018. 

Insilico Medicine is the first company applied deep generative adversarial networks (GANs) to the generation of new molecular structures with specified parameters and published seminal papers in Oncotarget and Molecular Pharmaceutics. Another paper published in Molecular Pharmaceutics in 2016 and demonstrated the proof of concept of the application of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data, received the American Chemical Society Editors' Choice Award. One of the recent papers published in November 2017 described the application of the next-generation AI and blockchain technologies to return the control over personal data back to the individual.

The latest paper published in the Journals of Gerontology exhibited the new artificial intelligence algorithm determining the biological age with high precision and having a potential to reveal whether lifestyle changes and medicinal products can increase people's chances of living a long and healthy life. 

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About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D and management resources in Belgium, Russia, UK, Taiwan and Korea sourced through hackathons and competitions. 

The company utilizes advances in genomics, big data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related duiseases. Insilico pioneered the applications of the generative adversarial networks (GANs) and reinforcement learning for generation of novel molecular structures for the diseases with a known target and with no known targets. In addition to working collaborations with the large pharmaceutical companies, the company is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging. Through a partnership with LifeExtension.com the company launched a range of nutraceutical products compounded using the advanced bioinformatics techniques and deep learning approaches. It also provides a range of consumer-facing applications including Young.AI and Aging.AI and operates Chemistry.AI intended to capture the tacit knowledge of medicinal chemists. 

Through a partnership with the BitFury Group, the company is working on a range of AI solutions for blockchain to help return the power over life data back to the individual. The company raised venture capital and partnered with Juvenescence Limited, a holding company focused on longevity biotechnology. The company aspires to become the "Bell Labs" for artificial intelligence and associated technologies for healthcare and longevity biotechnology and commercialize its research by forming subsidiaries around the specific technologies and licensing the intellectual property, molecules and data to the biotechnology and pharmaceutical companies. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. In 2018, the company was named the one of the global top 100 AI companies by CB Insights. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD
zhu@pharma.ai
Website: http://www.Insilico.com

Official Summit Website: http://advancedpharma-analytics.com

Population-specific deep biomarkers of aging

Thursday, Jan. 11th, Baltimore, MD - Today, Insilico Medicine, Inc., a Baltimore-based company specializing in the application of artificial intelligence for drug discovery, biomarker development and aging research, announced a publication of a research paper titled "Population-specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern-European patient populations" in The Journal of Gerontology. 

In the paper, the authors present a novel deep-learning based hematological human aging clock, a biomarker that predicts the biological age of individual patients. This big data study uses a large dataset of fully anonymized Canadian, South Korean and Eastern European blood test records to train an aging clock. The developed model predicts the age better than models tailored to the specific populations highlighting the differences of subregion-specific patterns of aging. In addition, the developed clocks were shown to be a better predictor of all-cause mortality than chronological age. The paper includes co-authors from Gachon University Gil Medical Center, University of Copenhagen, University of Alberta, and the Biogerontology Research Foundation. 

"If we are to develop actionable biomarkers of aging, we need a comprehensive and robust approach. Such an approach can only be developed using a large number of samples from multiple populations. We are working on multiple biomarkers using deep learning and incorporating blood biochemistry, transcriptomics, and even imaging data to be able to track the effectiveness of the various interventions we are developing". said Polina Mamoshina, a senior research scientist at Insilico Medicine.

"The pursuit of biological aging clocks is a major focus point of the aging field and is a key step in the development of interventions in human aging. This paper represents the evolution of the first easily adaptable clock that can be applied at a population level regardless of population biases. The clock is very cost-effective, without the requirement of next-generation sequencing or other specialized equipment. It is therefore extraordinarily suited for testing aging-interventions in multiple settings across the globe." said Morten Scheibye-Knudsen, MD, Head of the Biology of Aging Laboratory, Center for Healthy Aging, and associate professor, University of Copenhagen.

"Development of effective biomarkers of age is one of the most pressing goals in geroscience today, as it lays the foundation for efficient preclinical and clinical evaluation of potential healthspan-extending interventions. Humans live a long time, and testing the effect of gerontological interventions in humans using lifespan gains as the main criterion for success would be wildly impractical, necessitating long and costly longitudinal studies. By developing accurate biomarkers of aging, the efficacy of potential healthspan-extending interventions could instead be tested according to changes in study participants' biomarkers of age. While significant attention is paid to the development of highly accurate biomarkers of aging, less attention is paid to developing actionable biomarkers of aging that can be tested inexpensively using the tools at hand to the majority of researchers and clinicians. We developed the deep-learning based, blood biochemistry aging clock presented in this paper in the hopes of making progress toward the goal of more actionable biomarkers of aging" said Franco Cortese, co-author of the paper and Deputy Director of the Biogerontology Research Foundation.

"This work demonstrates the synergy between artificial intelligence and aging research. Every living being has age as a feature and it is possible to engage in multi-national collaborations using the very simple data types to assess the population specificity of age predictors. Our group is using advanced AI for multiple clinical applications and has a working collaboration with IBM Watson, but working with Insilico Medicine is a pleasure", said Lee Uhn, PhD, Chief of Artificial Intelligence at the Gachon University Gil Medical Center. 

"Age is one of the features possessed by every living creature. In 2015 we made a very neat discovery - when we train the deep neural networks to predict the age of the person, the DNNs capture the most biologically-relevant features and can be re-trained on diseases and can be used to integrate the multiple data types and also extract the most important features within each data type and across the data types. In this paper we show one of the proofs of concept on a very simple and abundant data type that we can now assess the population-specificity of the predictors, the importance of ethnicity and population group in age prediction and the differences in the most important features contributing to the accuracy of these predictors", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc. 

This work may help improve clinical trial enrollment practices, assess the population specificity of a variety of the biomarkers and pave the way for the development of more complex multi-modal biomarkers of aging and disease. 

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For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD 
zhu@pharma.ai 
Website: http://www.insilico.com

About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D offices and resources in 6 countries sourced through hackathons and competitions. The company utilizes advances in genomics, big-data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company is pursuing internal drug discovery programs in cancer, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging. Through its Pharma.AI division, Insilico provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies, foundations and national governments globally. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact and CB Insights named Insilico Medicine to the prestigious top 100 AI companies.  http://www.insilico.com

Insilico Medicine to Keynote at the A4M Las Vegas alongside Peter Diamandis and Valter Longo (IMAGE)

Wednesday, 13th of December, 2017, Baltimore, MD - Insilico Medicine, a Baltimore-based company specializing in the application of artificial intelligence for drug discovery, biomarker development and aging research, is pleased to announce the lecture of its founder and CEO, Dr. Alex Zhavoronkov, at 25th Annual World Congress, 14-16 Dec 2017, organized by American Academy of Anti-Aging Medicine (A4M).

Dr. Zhavoronkov's session will focus on the latest advances in artificial intelligence for development and tracking of anti-aging interventions. The lecture will cover the novel approach of developing evidence-based nutraceuticals via in silico prediction, in vitro and in vivo validation and post-marketing analysis using Young.AI project. Young.AI, currently in the beta-test version is an online service for tracking the biological age using the deep-learned photographic and basic blood biochemistry-based predictors.

"It is a privilege to speak alongside Peter Diamandis, Valter Longo, Michael Weiner and the others at the 25th annual A4M event. Insilico Medicine aspires to be the leader in artificial intelligence for longevity biotechnology and one of the many areas we are working on our evidenced-based nutraceuticals. Millions of people are consuming a broad range of nutraceuticals on a daily basis and do not track their progress. By introducing a range of nutraceuticals identified using AI and a pilot system to track their progress - Young.AI, we are trying to develop a novel drug discovery cycle that may substantially reduce the failure rates and the discovery and development time in the pharmaceutical industry", said Alex Zhavoronkov, PhD, the founder and CEO of Insilico Medicine, Inc.

"Issues following the development of novel molecules into medicines are undeniable, especially in the field of aging. Safe nutraceuticals offer one of a few ways to speed up the translation of anti-aging interventions into humans. With recent developments in the field of actionable biomarkers of biological age these interventions can be quickly evaluated by Young.AI platform", commented Alex Aliper, President of EMEA, Insilico Medicine, Inc.

Insilico Medicine was the first company to apply deep generative adversarial networks (GANs) to the generation of new molecular structures with specified parameters and published seminal papers in Oncotarget and Molecular Pharmaceutics. Another paper published in Molecular Pharmaceutics in 2016 and demonstrated the proof of concept of the application of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data, received the American Chemical Society Editors' Choice Award. One of the recent papers published in November 2017 described the application of the next-generation AI and blockchain technologies to return the control over personal data back to the individual. 

"In the age of personal and healthcare data, it's highly important to track, understand and control your data. With Young.AI beta everyone can take advantage of the recent advances in deep learning technology to track the aging process at every level and evaluate the importance of different biomarkers. In order to better understand the effectiveness of the lifestyle as well as supplement and drug intake, Young.AI system incorporates various types of interventions and metadata", said Alexander Zhebrak, the director of product development and CTO of Insilico Medicine, Inc.

The 25th Annual World Congress in Las Vegas marks a quarter of a century since A4M began its original mission: to build awareness and deliver innovative, cutting-edge scientific education focused on longevity, and prolonging the human lifespan. The audience of the congress spans the globe, and its invited speakers, keynotes, and faculty panels assist attendees in implementing and integrating new therapies into practice.

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For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD 
zhu@pharma.ai 
Website: http://www.Insilico.com

Official Congress Website: https://www.a4m.com/world-congress-2017/home

About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D and management resources in Belgium, Russia, UK, Taiwan and Korea sourced through hackathons and competitions. 

The company utilizes advances in genomics, big data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. Insilico pioneered the applications of the generative adversarial networks (GANs) and reinforcement learning for generation of novel molecular structures for the diseases with a known target and with no known targets. In addition to working collaborations with the large pharmaceutical companies, the company is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging. Through a partnership with LifeExtension.com the company launched a range of nutraceutical products compounded using the advanced bioinformatics techniques and deep learning approaches. It also provides a range of consumer-facing applications including Young.AI and Aging.AI and operates Chemistry.AI intended to capture the tacit knowledge of medicinal chemists. 

Through a partnership with the BitFury Group, the company is working on a range of AI solutions for blockchain to help return the power over life data back to the individual. The company raised venture capital and partnered with Juvenescence Limited, a holding company focused on longevity biotechnology. The company aspires to become the "Bell Labs" for artificial intelligence and associated technologies for healthcare and longevity biotechnology and commercialize its research by forming subsidiaries around the specific technologies and licensing the intellectual property, molecules and data to the biotechnology and pharmaceutical companies. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

Insilico Medicine Named to the Global Top 100 AI Companies by CB Insights

INSILICO MEDICINE NAMED TO THE 2018 AI 100, HIGHLIGHTING ADVANCEMENTS IN DEEP LEARNING FOR DRUG DISCOVERY AND LONGEVITY BIOTECHNOLOGY

CB Insights today named Insilico Medicine to the prestigious AI 100, a select group of promising private companies working on groundbreaking artificial intelligence technology. CB Insights CEO and co-founder Anand Sanwal will reveal the full list of the second annual AI 100 companies at the A-ha! conference in San Francisco.

"Last year's AI 100 enjoyed amazing success in the year since earning this recognition. 55 of them went onto raise additional funding nearing $2B and 5 were acquired. This year's list was culled from 1000+ applications and looks even more impressive. These are companies using artificial intelligence in industries from drug discovery and cybersecurity to robotics and legal tech. I'm happy that CB Insights is able to shine a light on the founders and companies that will revolutionize these industries and look forward to seeing what they do in 2018 and beyond." said CB Insights CEO Anand Sanwal.

The CB Insights research team selected the AI 100 companies based on criteria, examining company-submitted data and the company’s Mosaic Score. The Mosaic Score, based on CB Insights’ National Science Foundation-funded algorithm, measures the overall health and growth potential of private companies. Through this evidence-based, statistically-driven approach, the Mosaic Score can help predict a company’s momentum, market health and financial viability. 

“In 2014 Insilico Medicine made a bet on the deep learning technology and since then established over 250 industry and academic collaborations in both drug discovery and biomarker development and we became an innovation driver for the pharmaceutical industry. We are very happy to be recognized as one of the top 100 global AI companies by CB Insights, one of the top industry analysts,” said Alex Zhavoronkov, PhD, the CEO of Insilico Medicine, Inc

In May 2017 Insilico Medicine was named top 5 AI companies for social impact by Nvidia. It pioneered the application of the generative adversarial networks (GANs) and reinforcement learning to generation of new molecular structures with the specific set of characteristics. It also pioneered using age as the main feature for multi-modal multi-omics data integration, biomarker development, target identification and transfer learning. 

“In 2014 we just got our signaling pathway perturbation analysis algorithms to work very well after several years of hard work and got venture capital to develop them further. We even got some freedom and the tools to focus on our primary interest - aging research. So the idea of refocusing the company into deep learning, which was very new back then was met with some internal resistance. But nowadays we probably have one of the most efficient and productive DL teams in the world. We are hiring through hackathons and competitions in the many countries, where the DL talent is not overpriced and bridge the gap between the DL scientists, biologists and medicinal chemists very quickly. We also perform literature reviews at least twice a week to ensure that we incorporate all of the latest advances in DL into our models. We are happy to see that this hard work is recognized by CB Insights.” said Alex Aliper, president of Europe, Insilico Medicine, Inc.

Insilico Medicine was the first company to apply deep generative adversarial networks (GANs) to the generation of new molecular structures with specified parameters and published seminal papers in Oncotarget and Molecular Pharmaceutics. Another paper published in Molecular Pharmaceutics in 2016 and demonstrated the proof of concept of the application of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data, received the American Chemical Society Editors' Choice Award. One of the recent papers published in November 2017 described the application of the next-generation AI and blockchain technologies to return the control over personal data back to the individual. 

About CB Insights
Our team builds technology that helps corporations guess less and win more. We aggregate and analyze terabytes of data and use machine learning, algorithms and data visualization to help corporations replace the three Gs (Google searches, gut instinct and guys with MBAs) so they can answer massive strategic questions using probability not punditry.

Contact:
Farrah Kim, Senior Public Relations & Communications Manager
fkim(at)cbinsights.com
212-292-3148

For more information about the AI 100, visit:
https://www.cbinsights.com/research-ai-100

About Insilico Medicine, Inc
Insilico Medicine, Inc. is an artificial intelligence company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D resources in Belgium, Russia, and the UK sourced through hackathons and competitions.

The company utilizes advances in genomics, big-data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company is pursuing internal drug discovery programs in cancer, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging.

Through its Pharma.AI division, Insilico provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies, foundations and national governments globally. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. http://www.insilico.com

Contact:
Qingsong Zhu, PhD

zhu(at)pharma.ai

Study using artificial intelligence to identify compounds that mimic the longevity effects of calorie restriction published in November 2017 issue of Aging Journal

GEROPROTECT™ Longevity A.I.™ From Life Extension® provides anti-aging extracts that targets the anti-aging pathways as calorie restriction mimetics found in the study.

A study published in the November 15, 2017 issue of the Aging Journal addressed the need to identify nutraceuticals—safe, naturally-occurring compounds—that mimic the anti-aging effects of calorie restriction, and revealed how these compounds were identified using artificial intelligence. 

Calorie restriction is associated with enhanced longevity. However, for many it is an impractical or impossible long-term strategy. Thus, the goal of this study was to identify compounds that activate the same anti-aging pathways as a calorie restriction mimetic.

The study, a collaboration between Insilico Medicine and Life Extension, applied gene expression data from the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 dataset to map the gene- and pathway-level signatures of a calorie restriction mimetic and screened for matches among over 800 natural compounds. They then predicted the safety of each compound with an ensemble of deep neural network classifiers. 

Several complementary approaches were employed including conventional statistical methods, pathway scoring-based methods, and training of deep neural networks (DNN) for signature recognition. To evaluate potential adverse effects of top-scoring natural compounds, a set of deep learned predictors, trained on transcriptional response data, were utilized.

This study also revealed promising candidates for future experimental validation while demonstrating the applications of powerful screening methods for this and similar endeavors. Moreover, the scientific research opportunities that this presents are as endless as the contributions that a socially and economically active, secure and healthy aging population can bring to society.

Life Extension utilized the findings of this artificial intelligence empowered study to develop a novel dietary supplement called GEROPROTECTTM Longevity A.I. Longevity A.I, is an innovative combination of three natural nutrients, withaferin a, gamma-linolenic acid, and ginsenoside Rg3 from Asian ginseng, that mimic known metabolic regulators of the same anti-aging pathways targeted by calorie restriction mimetics, which have long been associated with increased life expectancy.

"GEROPROTECT™ Longevity A.I.™ is the only formation to combine three potential life-prolonging ingredients into a single supplement," said Andrew G. Swick, Ph.D., senior vice president, product development and scientific affairs at Fort Lauderdale, Fla.-based Life Extension. "This unique formulation based on proprietary artificial intelligence technology contains these geroprotector ingredients in concentrations several magnitudes higher than conventional dietary supplements. We suggest that this novel formulation should be a keystone product in all life extensionists' supplement regimens."

Insilico, a next-generation artificial intelligence company specializing in the application of deep learning proprietary technology for biomarker development and aging research, used pioneering high-performance computer simulations to probe of the effect of extracts on anti-aging pathways.  

The company is located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore. Insilico utilizes advances in genomics, big-data analysis, and deep learning for developing products for various health related industries. 

"We researched thousands of natural compounds and their combinations using our proprietary deep-learning artificial intelligence technology to identify the optimal combination of ingredients that activate the same anti-aging pathways as a calorie restriction mimetic," said Alex Zhavoronkov, Ph.D. and chief executive officer of Insilico Medicine, Inc. "Without this technology our search to swiftly fight back against aging would have literally taken decades to determine and achieve."

Full text of the study can be found at http://www.aging-us.com/article/101319/text#fulltext.

For over 37 years, Life Extension has been a pioneer in funding and reporting the latest anti-aging research and integrative health support while offering superior-quality dietary supplements. Life Extension develops and manufactures more than 350 science-based formulations that set the standard for quality, purity, and potency. A trailblazer in the $37 billion U.S. dietary supplements industry, Life Extension has a long history of offering prescient health guidance to American consumers, often years ahead of the mainstream medical establishment. Life Extension is an organization dedicated to finding new scientific methods to enhance and expand the healthy human life span. It funds research programs aimed at developing new scientific breakthroughs and has donated more than $175 million to anti-aging studies.

Chemistry.AI to analyze the brain activity of medicinal chemists for AI-powered drug discovery

Insilico announces a new crowd-sourced platform that will use EMOTIV's neuroscientific data collection and processing to perform the first Turing test for molecules generated using AI and to involve the medicinal chemists into AI-powered drug discovery

Wednesday, 22nd of November, 2017, Baltimore, MD, Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery announced the launch of the first phase of the Chemistry.AI program. Chemistry.AI is a crowd-sourced platform for analyzing the brain's response of medicinal chemists to the molecules developed using artificial intelligence technologies and other expert medicinal chemists. The neuroscientific response is evaluated by analyzing the brain activity of the medicinal chemists using a ubiquitous mobile electroencephalography (EEG) device called EPOC+ produced by EMOTIV. EPOC+ also provides data about head motion and certain facial expressions. EMOTIV, the world leader in consumer EEG offers brain sensors and cloud-computing solutions to scale the collection and processing of behavioral and brain data that will be used together with eye-tracking and video monitoring techniques in the current project.

"Using our mobile sensors and cloud computing solutions to better understand the brain activity of medicinal chemists, will provide unique insights on what distinguishes experts chemists from others, that no other methodology could", said Tan Le, CEO of EMOTIV (@tanttle)

"Medicinal chemists with several years of experience have the ability to distinguish the good molecules from the bad ones just by looking at their structure or its numerical properties and various scores. Depending on their prior experience with the various types of chemistry, e.g. kinase chemistry or GPCR chemistry and their background, their assessment is often biased. With Chemistry.AI we are hoping to achieve two major goals: capture the tacit knowledge possessed by medicinal chemists and put the output of the molecules generated using AI to the test by some of the best human scientists in a version of a Turing test", said Alex Zhavoronkov, PhD, the founder of Insilico Medicine, Inc. 

Medicinal chemistry is among one of the most important and intellectually-challenging professions on the planet. It takes decades of training and experience to learn the properties of the thousands of molecules and their effects on the biological systems, model organisms and diseases. Decisions made by the medicinal chemists affect the lives of billions of people and may result in the billions of dollars of gains or losses for the pharmaceutical companies.

Experienced medicinal chemists have the ability to accurately describe the properties and the possible effects of the molecule just by looking at its structure, as well as at the various numerical parameters.

They may favour certain molecular structures because of their experience with the hundreds of thousands of molecules they encountered previously and the emotional response to the molecule is usually biased and related to the molecules and the classes of molecules they are most familiar with.

Chemistry.AI will provide a platform for the medicinal chemists to look at the various classes of molecules and measure their brain activity and other physiological parameters during the exposure to the molecule.

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For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD 
zhu@pharma.ai

Website: http://www.Insilico.com

About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D resources in Belgium, Taiwan, Russia, and the UK sourced through hackathons and competitions.

The company utilizes advances in genomics, big-data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company is pursuing internal drug discovery programs in cancer, dermatological diseases, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging itself.

Through its Pharma.AI division, Insilico provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies, foundations and national governments globally. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. http://www.insilico.com

About EMOTIV

EMOTIV is the leading mobile bioinformatics company, advancing understanding of the human brain using electroencephalography (EEG). Its mission is to empower individuals to understand their own brain and accelerate brain research globally. 

EMOTIV has developed unique machine learning algorithms that allow the user to track cognitive performance, detect facial expressions and control both virtual and physical objects via trained mental commands.

EMOTIV leads the field of mobile brain sensors in terms of innovation, technology and support from the scientific community. Its technology is currently being used in more than 110 countries by more than 80,000 individuals who own one of its brainwear. It has been validated and included in over 4,000 publications. EMOTIV believes in the power of the human brain and the ability to tap into its potential to open up new possibilities for improving performance, health, wellness and ultimately, prevent disease. https://www.emotiv.com/

Converging blockchain and next-generation AI technologies to accelerate biomedical research

Blockchain and AI researchers propose a new model to return the control over human life data to the patients and accelerate biomedical research

Wednesday, 15th of November, 2017, 10AM EST, Baltimore, MD, Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for drug discovery announced the publication of a new peer-reviewed research paper titled" Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare" in Oncotarget. Insilico Medicine scientists specializing in deep learning collaborated with the scientists and developers from the Bitfury Group, the world's leading full service Blockchain technology company, specializes in securing the Blockchain and deploying cutting edge hardware and software solutions to governments, institutions, and corporations. In the paper the groups presented the first attempt to assess the value of time and the combination value of personal data in the context of an AI-mediated health data exchange on blockchain. 

"Most people do not understand what life data they have, how valuable and dangerous this data may be and do not have any control over how their life data is being used. The policy makers are trying to address this problem by introducing new regulations that make it expensive and difficult for the innovators to turn the human life data into life-saving products. In this paper we propose a blockchain-enabled solution to help people become aware of and take control over their data and profit from licensing the data to the innovators", said Polina Mamoshina, Sr. research scientist at Insilico Medicine. 

In this research paper scientists introduce new concepts to appraise and evaluate human life data, including the combination-, time- and relationship-value of the data and present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.

"We are enthusiastic that blockchain technology can help solve one of the major problems in modern healthcare - patient data management. We are even more excited that Insilico is building this solution on our open-source Blockchain framework, Exonum. An Exonum-based Blockchain provides security, transparency and reliability, which will significantly improve overall efficiency and patient satisfaction as well as provide an avenue for easier auditing. We look forward to sharing our progress", said George Givishvili, Chief Marketing Officer of Bitfury company.

Blockchain technology enables the creation of a distributed and secure ledger of personal data, where patients are in control, own their data, and monitoring of access privileges and understanding of who looked at the data. Most importantly, blockchain technology allows for the creation of a data-driven marketplace, where patients can earn tangible rewards for making their data available to the application development community, pharmaceutical and consumer companies, and research institutions and generating new data through regular and comprehensive tests and checkups. Presently, only a few patients worldwide have the comprehensive data sets containing their clinical history combined with the genetic, blood biochemistry and cell count profiles, lifestyle data, drug and supplement use and other data types, because they do not see the value in this data and do not get tested regularly. On the other hand, the pharmaceutical and consumer companies alike are willing to pay substantial amounts for the large numbers of personal data records required to train their AI. These funds can be used to subsidize the regular testing by the patients, uncover the new uses for the various data types and develop sophisticated diagnostic and treatment tools.

"In the post neoclassical world, healthy productive longevity will be the new driver of economic growth. Creating an economy around human life data and returning the ownership and the control over life data back to the individual is one of the most important steps towards extending healthy productive longevity of the global population. It is also a very altruistic cause, which may help reduce the gap between the rich and the poor and allow the people from all walks of life and geographies to equally profit from their own data", said Alex Zhavoronkov, the founder of Insilico Medicine, Inc. 

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For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD

zhu@pharma.ai

Website: http://www.Insilico.com

About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company located at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D resources in Belgium, Russia, and the UK sourced through hackathons and competitions.

The company utilizes advances in genomics, big-data analysis, and deep learning for in silico drug discovery and drug repurposing for aging and age-related diseases. The company is pursuing internal drug discovery programs in cancer, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and aging.

Through its Pharma.AI division, Insilico provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies, foundations and national governments globally. In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. http://www.insilico.com