First molecules discovered using artificial intelligence head to development

Jan.6, 2018, Baltimore, Maryland- Insilico Medicine, Inc. ("Insilico"), a Baltimore-based next-generation artificial intelligence (AI) company specializing in the application of deep learning for drug discovery, announces that Juvenescence.AI, its joint venture with Juvenescence Limited ("Juvenescence"), has licensed its first compound family for clinical development. This is one of five compound families that Juvenescence.AI is able to license each year under its license agreement with Insilico.

"The selection of our first compound family is a landmark event for Juvenescence, and a broader comment on the potential of AI to transform the drug discovery and development industry" commented Jim Mellon, Chairman of Juvenescence.

This deal is a result of a deep collaboration between the senior drug developers at Juvenescence and AI experts at Insilico and signifies a new era in drug discovery where highly sophisticated AI finds viable drug candidates. In less than six months the teams have identified a valuable molecular target for a specific age-associated disease area, and are now working to identify other promising molecules for a variety of targets and perform validation.

Dr Greg Bailey, CEO of Juvenescence said: "This has been a very exciting time for the team of drug developers at Juvenescence as we work with Insilico to change how drug are discovered. This constitutes more validation of Insilico's ability to find novel drugs. It is also speaking to the quality of the relationship between our two companies both focused on changing how mankind ages." 

JAI-001 and its analogues, have demonstrated in vitro activity in assays directly relevant to aging and age-related diseases. 

"The team at Insilico Medicine is very excited to be working with Juvenescence. As a company, it has centuries of drug discovery and development experience, and has provided our team with valuable guidance. We are very happy to see that some of the top pharmaceutical industry executives are now focusing their efforts on aging and artificial intelligence", said Alex Zhavoronkov, PhD, Founder and CEO of Insilico Medicine, Inc.

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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 ageing and age-related diseases. The company is pursuing internal drug discovery programs in cancer, Parkinson's Disease, Alzheimer's Disease, ALS, diabetes, sarcopenia, and ageing. 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 its Top 5 AI companies in its potential for social impact. Website: http://www.insilico.com

About Juvenescence Limited Juvenescence Limited is a biotech company focused on therapies to increase healthy human longevity. It was founded in 2017 by Jim Mellon, Dr. Greg Bailey, Dr. Declan Doogan, Anthony Chow, and Alexander Pickett. The Juvenescence team are highly experienced drug developers, and serial entrepreneurs with a track record of success in life sciences and drug development. Juvenescence is focussed on developing therapeutics that alter ageing or age-related diseases.

Juvenescence believes that recent advances in science have greatly improved our understanding of the biology of ageing and creates the opportunity to develop therapeutics now that can slow, halt or potentially reverse elements of ageing.

For further information, images or interviews, please contact:

Contact:

Qingsong Zhu, PhD
zhu@pharma.ai

Insilico to present the advances in deep-learned multimodal biomarkers of aging at NCI

Tuesday, February 6th, 2018, Baltimore, MD - Insilico Medicine, a Baltimore-based company specializing in artificial intelligence for drug discovery, biomarker development and aging research will present a lecture on deep-learned multimodal biomarkers of aging at the Cancer Biomarkers Data Commons Meeting (CBDC) Think Tank Meeting, February 8th 2018, at the National Cancer Institute. The event is open to the public with prior registration. 

Dr. Zhavoronkov's lecture "Deep-learned multimodal biomarkers of aging" will cover the latest advances in artificial intelligence for development of aging biomarkers. The session will focus on the machine learning approaches used for aging biomarker development and their potential application to the cancer biomarker discovery.

"Assessing the biological age of the patient using multiple data types may significantly contribute to personalization in the many areas of medicine primarily in immuno oncology. People, their organs and systems age at different rates and adjusting the therapy to the biological age of the patient may help improve outcomes in clinical trials and in the real world. The deep neural networks trained to predict the biological age of the patient may be used to discover novel targets and pathways in aging and age-related diseases", said Alex Zhavoronkov, PhD, the founder and CEO of Insilico Medicine, Inc.

The Think Tank Meeting on the Development of a Cancer Biomarkers Data Commons will bring together thought leaders from academia, industry, and government to discuss approaches to the development of cancer biomarkers. The event sets up the objectives to examine clinical and research needs in cancer biomarker discovery, discuss machine learning and statistical approaches to biomarker discovery and explore bioinformatics strategies to transform Big Data into FIT (fit-for-purpose) Data.

"The early diagnosis and prognosis of a cancer have become a necessity in cancer research, as it can facilitate the more effective and accurate decision making in clinical management of patients. The importance of classifying cancer patients into high or low risk groups has led many research teams, from the biomedical and the bioinformatics field, to study the application of integrative high-throughput computational analyzed and machine learning methods. Although it is evident that the use of these methods can improve our understanding of cancer progression, there are still significant challenges and limitations associated with computational modeling human cancer. However, with the dismal success rate seen in clinical trials, and as the current technical limitations deep-learning are overcome, the value of these tools in addressing the continuing challenges in clinical oncology will grow", said Eugene Izumchenko, PhD, Head and Neck Cancer Research, Department of Otolaryngology, Johns Hopkins School of Medicine.

Insilico Medicine is responsible for the many "firsts" and proofs of concept in the application of deep learning to drug discovery and biomarker development. It was the first to apply the 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 demonstrated the application of the deep neural networks to assessing the biological age of the patients. 

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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 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

Advances in deep learning for biomarker development to be presented at the PMWC in Silicon Valley

Thursday, Jan. 18th, 2018, 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 the Precision Medicine World Conference (PMWC) 2018, January 23, 2018, Silicon Valley.

The AI panel will focus on the latest advances in artificial intelligence for biomarker development and drug discovery. The session will cover different approaches and AI platforms, and how they impact the pharmaceutical industry and specifically, the drug discovery and development processes. 

"PMWC Silicon Valley is one of the top conferences in biomedicine and we are very happy to be back this year after receiving the Most Promising Company award at the conference in 2015, when deep learning was still an exotic term. This year's conference is heavily focused on AI and the organizers managed to gather pretty much everyone in the field in the Computer History Museum", said Alex Zhavoronkov, PhD, the founder and CEO of Insilico Medicine, Inc.

The Precision Medicine World Conference is an independent and established conference series known as prominent medicine conference gathering recognized leaders, top global researchers, medical professionals and innovators across healthcare and biotechnology to close the gap between different sectors and to catalyze the cross-functional collaborations. The program of PMWC Silicon Valley embaraces innovative technologies, growing initiatives, and clinical case studies converting the advances of precision medicine into direct improvements in health care. The conference agenda highlights more than 70 sessions with 350+ talks covering all facets of precision medicine. The event will transpire January 22-24, 2018. 

Insilico Medicine is regularly publishing research papers in peer reviewed journals. It was 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 Gerontologyexhibited 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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For further information, images or interviews, please contact:

Contact: Qingsong Zhu, PhD 
a href="mailto:zhu@pharma.ai">zhu@pharma.ai

Website: http://www.Insilico.com

Official Conference Website: http://www.pmwcintl.com/2018sv/

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. In 2018, the company was named one of the global top 100 AI companies by CB Insights. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

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