Advances in AI for drug discovery to be presented at the AI Pharma Innovation Summit 2017 in Boston

 Insilico Medicine, a Baltimore-based artificial intelligence company focused on drug discovery, biomarker development and aging research will present new research on applying deep learning approaches to drug discovery at the inaugural AI Pharma Innovation Summit in Boston, July 25-27. The CEO of Insilico Medicine, Alex Zhavoronkov, PhD will present new research and moderate the workshop titled "A Fundamental Guide to the Application of AI in Drug Discovery to Uncover the Next Wave of Successful Future Candidates" 15:00-17.30 on July 25th. The conference website is http://www.ai-pharma.com and early bird registration deadline is June 23rd.

The conference will bring together some of the most prominent thought leaders in artificial intelligence for the pharmaceutical industry, pharmaceutical industry executives, regulators and academics. It will feature speakers from Pfizer, Sanofi and Novartis with the Global CIO of Novartis, Remy Evard and VP and Global Head of Digital Business, Jeremy Sohn leading a session called "Discover: Accelerating the Integration of AI in into Pharmaceutical DNA". 

"Artificial Intelligence is transforming many industries including transportation, finance and security. This will undoubtedly impact the pharmaceutical industry which will experience dramatic change over the next five years. AI will impact every process from early screening and preclinical validation to clinical trials execution, marketing, sales and general management. To adapt to this rapid pace of innovation pharma needs to adapt to the new world order and embrace AI as the source of competitive advantage and shareholder value creation", said Declan Doogan, MD, DSc, former senior vice-president and head of worldwide development at Pfizer and Chairman and co-founder of Biohaven Pharmaceuticals."

In order to facilitate this fundamental shift in the biopharma R&D model, Insilico Medicine will launch in July an executive training program codenamed "the Pharmaceutical Artificial Intelligence Strategy Executive Coach". The program is geared towards the senior company executives and board members of large biopharmaceutical corporations and international government regulatory bodies in partnership with the several prominent hardware vendors and consulting companies. 

"Artificial intelligence holds enormous potential for pharmaceutical R&D. In fact, mastering AI will become a key competitive advantage for pharmaceutical companies, possibly a key survival factor versus more innovative and faster moving new entrants into the biomedical space. However, the hype surrounding AI, unprecedented investments by venture capitalists and lack of industry experts and analysts are creating a bubble reminiscent of the Dot Com era. Many companies are rebranding basic computational approaches as AI to get funding and contracts. Understanding the underlying principles and various flavours of AI and what the various elements of the AI toolbox can do for the various steps of the early R&D, clinical trials and marketing process is essential for every CEO and board member of every major pharmaceutical company", said Ulrich Muehlner, PhD, former director and head of corporate strategy of Novartis, CEO of GrowthCube Partners and advisor to Insilico Medicine. 

The interactive workshop at the AI Pharma Innovation Summit will delve deeper into the multiple applications of AI algorithms in drug design and discovery: with major investments at stake later down the R&D pipeline, it is essential that only the best candidates are identified to progress through the pre-clinical and clinical landscapes. Immerse yourself in discussions on the following topics: 

• Supporting discovery using AI
• Training neural networks to predict molecular structures
• Improving the scaling of drug discovery efforts by utilizing AI technology
• Discussing the application of AI for target and compound selection
• Predictive analytics for drug discovery target validation
• Discussing sophisticated predictive machine learning methods to improve the speed and efficiency of drug discovery process
• Developing computational AI methods for screening
• Harnessing AI platforms to correlate label drug use and medical events to identify suitable molecules for drug repurposing

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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 hiring talent through hackathons and competitions. It 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 pursues internal drug discovery programs in cancer, Parkinson's, Alzheimer's, ALS, diabetes, sarcopenia and geroprotector discovery. Through its Pharma.AI division, the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies. In 2017 NVIDIA selected Insilico as the top 5 AI companies for social impact. 

Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

Results in AI for aging research and personal health data management to be presented at Bio-Taiwan

 Insilico Medicine, a Baltimore-based artificial intelligence company focused on drug discovery, biomarker development and aging research will present new research at Bio-Taiwan in Taipei, Taiwan, June 28-29. The CEO of Insilico Medicine, Alex Zhavoronkov, PhD, will present new research in deep learned multi-modal biomarkers of aging and unveil a new tool for personal health data management. 

"We are getting ready to launch a new set of our biomarkers of aging and need to ensure that they work in many population groups and are biologically relevant. To do this we are looking for partners in many countries with accurate retrospective health records and unique diets, lifestyles and histories. We are very happy to be invited to present our progress in applying the latest advances in deep learning for aging research at the BioBusiness Asia Conference in Taiwan alongside speakers and friends from NVIDIA. During the event we will be looking for local partners for biomarker development", said Alex Zhavoronkov, PhD, founder and CEO of Insilico Medicine, Inc. 

Insilico will present at 14:50 on June 29th in Ballroom A in Session 6; their presentation will be titled "Increasing the Odds: The Promise of the Precision Oncology Revolution." They will also take part in a panel discussion titled "Utilizing ICT for Precision Medicine". The agenda for the conference is available at: https://bio-taiwan.com/en/program/detail/33.

Insilico Medicine was the first company to apply deep generative adversarial networks (GANs) to generating anti-cancer drugs with given parameters and published a seminal paper in Oncotarget. The paper published in Molecular Pharmaceutics, demonstrating the applications 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. 

In March 2017 the company launched its first geroprotector with its exclusive partner, Life Extension: http://www.geroprotector.com . Life Extension offers their customers a broad variety of blood tests that may be used to rapidly validate the effects of geroprotectors using Insilico's Aging.AI system.

Due to their many industry collaborations and a constant stream of research publications, scientists at Insilico Medicine are expected to present at over 30 events and conferences in 2017. In 2016 Insilico Medicine published several seminal proof of concept papers demonstrating the applications of deep learning to drug discovery, biomarker development, and aging research. A study published in Agingproposed a short list of molecules with likely geroprotective effects. In a recently published article at Nature Communications, Insilico Medicine describes a tool that it uses to study the minute changes in gene expression between young and old tissues and tissues afflicted by disease. Another paper demonstrating the ability to predict the chronological age of the patient using a simple blood test, published in Aging, became the second most popular paper in the journal's history.

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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 hiring talent through hackathons and competitions. It 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 pursues internal drug discovery programs in cancer, Parkinson's, Alzheimer's, ALS, diabetes, sarcopenia and geroprotector discovery. Through its Pharma.AI division, the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies. In 2017 NVIDIA selected Insilico as the top 5 AI companies for social impact.

Induced Cell Turnover: A proposed modality for in situ tissue regeneration & repair

Thursday, July 15, 2017, London, UK: Scientists at the Biogerontology Research Foundation, Feinberg School of Medicine at Northwestern University and Swammerdam Institute of Life Sciences at the University of Amsterdam have published a paper on a proposed method of in situ tissue regeneration called Induced Cell Turnover (ICT) in the journal Human Gene Therapy. The proposed therapeutic modality would aim to coordinate the targeted ablation of endogenous cells with the administration of minimally-differentiated, hPSC-derived cells in a gradual and multi-phasic manner so as to extrinsically mediate the turnover and replacement of whole tissues and organs with stem-cell derived cells.

"One of the major hurdles limiting traditional cell therapies is low levels of engraftment and retention, which is caused in part by cells only being able to engraft at locations of existing cell loss, and by the fact that many of those vacancies have already become occupied by ECM and fibroblasts (i.e. scar tissue) by the time the cells are administered, long after the actual occurrence of cell loss. The crux underlying ICT is to coordinate endogenous cell ablation (i.e. induced apoptosis) with replacement cell administration so as to manually vacate niches for new cells to engraft, coordinating these two events in space and time so as to minimize the ability for sites of cell loss to become occupied by ECM and fibroblasts. This would be done in a gradual and multi-phasic manner so as to avoid acute tissue failure resulting from the transient absence of too many cells at any one time. While the notion of endogenous cell clearance prior to replacement cell administration has become routine for bone marrow transplants, it isn't really on the horizon of researchers and clinicians working with solid tissues, and this is something we'd like to change." said Franco Cortese, Deputy Director and Trustee of the Biogerontology Research Foundation, and lead author on the paper.

Cell-type and tissue-specific rates of induced turnover could be achieved using cell-type specific pro-apoptotic small molecule cocktails, peptide mimetics, and/or tissue-tropic AAV-delivered suicide genes driven by cell-type specific promoters. Because these sites of ablation would still be "fresh" when replacement cells are administered, the presumption is that the patterns of ablation will make administered cells more likely to engraft where they should, in freshly vacated niches where the signals promoting cell migration and engraftment are still active. By varying the dose of cell-type targeted ablative agents, cell type and tissue-specific rates of induced turnover could be achieved, allowing for the rate and spatial distribution of turnover to be tuned to the size of the tissue in order to avoid ablating too many cells at once and inadvertently inducing acute tissue failure.

"Cell therapies are limited by low levels of engraftment, and in principal their ability to improve clinical outcomes is limited by the fact that they can only engraft at locations of existing cell loss. Conversely, therapeutic tissue and organ engineering requires surgery, is more likely to introduce biochemical and mechanical abnormalities to tissue ultrastructure through the decellularization process, and is fundamentally incapable of replacing distributed tissues and structures with a high degree of interconnectivity to other tissues in the body. The aim of ICT is to form a bridge between these two main pillars of regenerative medicine, extending the efficacy of cell therapies beyond a patch for existing cell loss and accomplishing the aim of tissue and organ engineering (i.e. the replacement and regeneration of whole tissues and organs) while potentially remaining free of some of their present limitations." said Giovanni Santostasi, co-author on the paper and a researcher at the Feinberg School of Medicine, Northwestern University.

While future iterations of the therapy could use patient-derived cells, such as ESCs derived via somatic cell nuclear transfer (SCNT) or iPSCs derived from nuclear reprogramming, shorter-term applications would likely use existing stem cell lines immunologically matched to the patient via HLA matching. The authors contend that the cloning of adult organisms with normal lifespans from adult somatic cells testifies to the fact that adult cells can be rejuvenated and used to produce a sufficient quantity of daughter cells to replace the sum of cells constituting adult organisms, and that serial cloning experiments (in which this process is done iteratively, using an adult cell of each subsequent generation to derive the next) attests to this fact even more strongly.

"ICT could theoretically enable the controlled turnover and rejuvenation of aged tissues. The technique is particularly applicable to tissues that are not amenable to growth ex vivo and implantation (as with solid organs) -- such as the vascular, lymphatic, and nervous systems. The method relies upon targeted ablation of old, damaged and/or senescent cells, coupled with a titrated replacement with patient-derived semi-differentiated stem and progenitor cells. By gradually replacing the old cells with new cells, entire tissues can be replaced in situ. The body naturally turns over tissues, but not all tissues and perhaps not optimally. I am reminded of the quote attributed to Heraclitus: 'No man ever steps in the same river twice, for it's not the same river and he's not the same man.'" said Sebastian Aguiar, a coauthor on the paper and researcher at the Swammerdam Institute of Life Sciences, University of Amsterdam.

"Reversing aging in humans will require a multi-step approach at multiple levels of the organismal organization. In situ targeted ablation of the senescent cells and regeneration will be an important component of comprehensive anti-aging therapies." said Alex Zhavoronkov, Chief Science Officer of the Biogerontology Research Foundation.

The researchers originally proposed ICT in 2016 in the context of biomedical gerontology as a possible means of preventing and/or negating age-related phenotypic deviation for the purposes of healthspan extension, and in this new paper they refine the methodological underpinnings of the approach, take a closer look at potential complications and strategies for their deterrence, and analyze ICT in the context of regenerative medicine as an intervention for a broader range of conditions based on disease or dysfunction at the cellular and intercellular level, with potential utilities absent from traditional cell therapies and tissue/organ engineering, the two main pillars of regenerative medicine. The intervention is still very much conceptual, and any potential utilities over other therapeutic modalities within regenerative medicine would need to be verified via preclinical studies, but their hope is to stimulate further research at this interface between geroscience and regenerative medicine.

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The paper is available here.

About the Biogerontology Research Foundation:

The Biogerontology Research Foundation is a UK non-profit research foundation and public policy center seeking to fill a gap within the research community, whereby the current scientific understanding of the ageing process is not yet being sufficiently exploited to produce effective medical interventions. The BGRF funds and conducts research which, building on the body of knowledge about how ageing happens, aims to develop biotechnological interventions to remediate the molecular and cellular deficits which accumulate with age and which underlie the ill-health of old age. Addressing ageing damage at this most fundamental level will provide an important opportunity to produce the effective, lasting treatments for the diseases and disabilities of ageing, required to improve quality of life in the elderly. The BGRF seeks to use the entire scope of modern biotechnology to attack the changes that take place in the course of ageing, and to address not just the symptoms of age-related diseases but also the mechanisms of those diseases.

AgeHack@MLBootCamp: The first Eurasian hackathon on AI for longevity to launch

Insilico Medicine, Mail.Ru Group and the Ministry of Health of the Republic of Kazakhstan to organize the first Eurasian Machine Learning hackathon to combat aging and age-related diseases

 Insilico Medicine, Mail.Ru Group in collaboration with the center for electronic health of the Ministry of Health of the Republic of Kazakhstan to organize the first Eurasian hackathon on machine learning on aging and longevity. The contest will run on the ML BootCamp platform from 15th of June to 15th of July and feature valuable prizes and internships that will allow machine learning scientists and programmers interested in contributing to the field of aging and longevity research.

Deep learned predictors of chronological age trained on the various types of biological data available in large volume from retrospective tests especially in healthy people will help us build comprehensive multi-modal biomarkers of human health status and will allow us to evaluate the effects of the various interventions. Insilico Medicine is collaborating with the governments, large healthcare providers and diagnostics labs in North America, Europe and Asia to develop new tools for personalized medicine, drug discovery and aging research. And while we usually work with tens of millions of data sets, it is important to see new ideas and approaches used on a small data set of one hundred thousand records with a small number of features and identify the machine learning champions, who are interested in solving this kind of problems», said Alex Zhavoronkov, the founder and CEO of Insilico Medicine.

AgeHack@MLBootcamp will be organized using the Machine Learning Bootcamp platform and will receive coverage in social networks, Mail.ru, AgeNet.Net and on the website of the Ministry of Health.

AgeHack@MLBootCamp is an online hackathon dedicated to identifying the novel methods for combating aging and extending the healthy productive longevity as well as to popularizing the field of biomedical data science among the IT professionals in the CIS countries. This will be the first hackathon, where data scientists from several Eurasian countries will attempt to develop novel solutions for healthy longevity starting from age predictors and predictors of health status. The basis for the contest will be the large dataset of anonymized health records.

In addition to recognition and internship offers, the winner will receive a MacBook Pro and the second and third places will receive high-end NVIDIA GPUs. Other top-scoring participants will receive valuable prizes.

"The machine learning technologies are at the peak of their popularity attracting more and more attention from experts from various research areas. This ML-hackathon on our platform is an important milestone in the Mail.ru's development of this field. The future of biomedical innovation is closely related with the management of large data sets and synergy between artificial intelligence and medicine. And we are very happy that we can help in the fight against aging by sharing our experience in machine learning and educational initiatives", commented Olga Avgustan, the head of educational initiatives at Mail.Ru Group.

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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 hiring talent through hackathons and competitions. It 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 pursues internal drug discovery programs in cancer, Parkinson's, Alzheimer's, ALS, diabetes, sarcopenia and geroprotector discovery. Through its Pharma.AI division, the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies. In 2017 NVIDIA selected Insilico as the top 5 AI companies for social impact. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8

Insilico Medicine launches a drug discovery platform ALS.AI

Today, Insilico Medicine, Inc., a company applying the latest advances in deep learning to biomarker development, drug discovery and aging research, launched ALS.AI, a personalized drug discovery and biomarker development platform utilizing the latest advances in deep learning. ALS.AI is intended to advance the discovery of new drugs and repurpose existing ones for Amyotrophic Lateral Sclerosis (ALS) and personalized treatment for ALS patients.

ALS is a rare disease that affects the function of nerves and muscles. Approximately 6,000 people in the U.S. are diagnosed each year with ALS. There are currently only two FDA-approved drugs, including Riluzole (Rilutek) and Edaravone (Radicava), for the treatment of ALS. Unfortunately, these drugs do not reverse ALS damage, but can only slow down the progression of the disease. Moreover, not every patient responds to these drugs. The use of advanced bioinformatics techniques and deep learning, which show promising results in many research areas, may address the urgent need to develop new treatments for ALS.

Above and Beyond NB LLC specializes in the development of new treatments for ALS through accelerated translational programs relevant to both the ALS patient population and specific individuals with ALS. Above and Beyond, which has entered into a collaboration agreement with Insilico Medicine, is equipped to provide transcriptomic data from ALS individuals that were analyzed by Insilico Medicine's ALS.AI platform.

Insilico Medicine was the first company to apply deep generative adversarial networks (GANs) to generating anti-cancer new molecules with given parameters and published one of its drug discovery pipelines in Oncotarget. The paper published in Molecular Pharmaceutics, demonstrating the applications 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.

"ALS is one of the rare diseases without a cure or an effective treatment. We are happy to work with Above and Beyond to identify new treatments for ALS using the latest developments in AI", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine.

For its pioneering work in the many areas of deep learning techniques applied to drug discovery, biomarker development and longevity research, Insilico Medicine was nominated as one of the "top 5 companies with most social impact" out of the pool of over 600 companies using NVIDIA, cutting-edge high-performance deep learning equipment, as part of its Inception Program.

"ALS is a progressive neurodegenerative disease that affects nerve cells in the brain and the spinal cord. Patients with ALS lose the ability to initiate and control the muscle movement, which often leads to total paralysis and even death," said Alexandre Bétourné, PhD, Chief Medical Officer of Above and Beyond. "Our business model embraces partnership. With the combination of traditional in-vitro methods and new technologies, such as AI, we are positioned to work with our partners to identify new treatments for the disease"

Insilico Medicine sees opportunities for the applications of deep learned biomarkers for the other rare diseases and seeks new treatments for such diseases. Insilico Medicine also believes the repurposing of existing FDA-approved drugs is one of the most promising approaches for rare diseases.

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About Above & Beyond

Above and Beyond NB LLC manages and funds a portfolio of programs to bring more innovative treatment options to ALS patients. Above and Beyond aims to translate new therapies for ALS at an accelerated pace. For more information, please visit our website: http://www.aboveandbeyondresearch.com.

About Insilico Medicine

Insilico Medicine, Inc. is a bioinformatics 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 hiring talent through hackathons and competitions. It 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 pursues internal drug discovery programs in cancer, Parkinson's, Alzheimer's, ALS, diabetes, sarcopenia and geroprotector discovery. Through its Pharma.AI division, the company provides advanced machine learning services to biotechnology, pharmaceutical, and skin care companies. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8.