News Article | May 8, 2017
Monday, May 8th, London, UK - The Chief Science Officer of the Biogerontology Research Foundation (BGRF) will present new research on artificial intelligence for drug discovery at the NVIDIA Graphics Technology Conference (GTC) at the San Jose Convention Center, on Wednesday, May 10, 1:00 PM - 1:50 PM alongside two AI scientists from the BGRF and Insilico Medicine, where they will deliver a presentation titled "Applications of Generative Adversarial Networks to Drug Discovery in Oncology and Infectious Diseases". NVIDIA is the leader in computational hardware optimized for deep learning-based applications, and they are on the forefront of supporting research companies and institutions applying deep learning to grand unsolved problems, with the application of deep learning to drug discovery and development being no exception, as they described in detail in their article "Creating New Drugs, Faster: How AI Promises to Speed Drug Development". NVIDIA shortlisted the GAN team as the top 5 companies with most Social Impact out of 2000 AI companies using NVIDIA graphics and 600 companies in the NVIDIA Inception Program. "The application of deep learning to ageing research is poised to make rapid progress on many fronts in the years to come. Foremost among these are the application of deep learning to the characterization of quantifiable and practically-measurable biomarkers of ageing (a necessity for the eventual regulatory evaluation and approval of healthspan-extending therapies) and the acceleration of drug discovery and development timelines by using deep learning to characterize drug candidates according to likely efficacy and safety prior to preclinical and clinical trials. AI, machine learning and deep learning have disrupted many industries and areas of activity that were previously the exclusive arena of human cognition, and in the coming years it seems likely that the pharmaceutical industry and the process of drug discovery and development will come to be radically disrupted by AI and deep learning-based approaches as well" said Franco Cortese, Deputy Director & Trustee of the Biogerontology Research Foundation. The Biogerontology Research Foundation scientists were the first to apply deep generative adversarial networks (GANs) to generating anti-cancer drugs with specific target properties which was the subject of a paper they published in Oncotarget. A second paper by Biogerontology Research Foundation published in Molecular Pharmaceutics demonstrated the ability of deep neural networks to predict the therapeutic class various molecules using transcriptional response data, which received the American Chemical Society Editors' Choice Award. Deep learning-based AI have already outperformed humans in many computational tasks including image and voice recognition, medical diagnostics and autonomous driving. Research published by Biogerontology Research Foundation scientists over the past several years have made great strides in demonstrating that the pharmaceutical industry and the field of biogerontology are areas poised to rapid disruption by deep learning-based approaches as well. Several seminal papers by Biogerontology Research Foundation and scientists from the Pharma.AI division of Insilico Medicine have made formidable progress in demonstrating the tractability of the application of deep learning for drug discovery and development. One study published in Aging announced a short-list of promising novel geroprotective compounds, and another article in Nature Communications demonstrated a proof-of-concept application of a novel algorithm that uses deep learning to characterize changes in gene expression between young and old tissues. They have also made substantial progress in demonstrating the tractability of using deep learning for the characterization of actionable and practically-measurable biomarkers of ageing, which was the subject of a paper they published in Aging demonstrating a deep learning-based algorithm capable of predicting the chronological age of patients using simple blood biochemistry markers obtained from simple blood tests, which became the second most popular paper in the journal's history. Disclaimer: At present, there are no financial ties between the BGRF, Insilico Medicine, Inc or NVIDIA. Insilico is the resident of Skolkovo Foundation ecosystem. 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.
News Article | May 9, 2017
Tuesday, May 9th, London, UK: Biogerontology Research Foundation Chief Science Officer Dr. Alex Zhavoronkov will be giving a talk titled "Drug Discovery Revolution Spiked by Pharma AI" at the Korea Future Forum on Wednesday, May 17, 2017. His talk will be focused upon the application of AI in general and deep learning in particular to drug discovery and drug repurposing to combat ageing and age-related disease. "The application of AI to ageing research has the potential to expedite progress on many fronts, foremost among these being the characterization of ageing biomarkers, drug discovery and development and drug repurposing. The Korean government has demonstrated their commitment to support cutting-edge AI projects, and for decades has demonstrated a very long-range view of scientific and technological progress, actively pursuing and supporting pioneering approaches to grand problems because they have long realized that the key to a strong GDP is a strong stake in the science and technologies of tomorrow. It is for that reason that the Biogerontology Research Foundation sees great promise in international research applications with Korean research hubs and institutions" said Franco Cortese, Deputy Director & Trustee of the Biogerontology Research Foundation. The Biogerontology Research Foundation and Insilico Medicine have worked to establish strategic partnerships and collaborations with Korean researchers following a partnership between Insilico Medicine and YMK Photonics to establish a research collaboration and business cooperation to develop photonics quantum computing and accelerated deep learning techniques for drug discovery, biomarker development and aging research in November 2016 and a collaborative research project with one of the largest Korean research and medical networks, Gachon University and Gil Medical Center to develop artificially intelligent multimodal biomarkers of aging and interventions aiming to slow the processes leading to the age-related loss of function in January 2017. "Advances in artificial intelligence and longevity research will be the highlights of the fourth industrial revolution and will re-shape the global economy. Korea is preparing to take the leadership position in these areas and I am happy to invite one of the leaders in the field, the CSO of the Biogerontology Research Foundation, Dr. Alex Zhavoronkov to speak at the Future Korea forum", said professor Youngsook Park, Chair of the Millenium Project Korea and Korea's leading futurist. The Biogerontology Research Foundation has published several seminal papers over the past few years demonstrating the tractability and scalability of deep learning applied to the characterization of actionable and practically-measurable biomarkers of ageing, which was the subject of a paper they published in Aging (which became the second most popular paper in the journal's history) demonstrating a deep learning-based algorithm capable of quantifying patients' chronological age by analyzing the results of routine blood tests. They have also made substantial progress in showing the potential of deep-learning based approaches to accelerate the drug discovery and development process, while simultaneously reducing costs and risks associated with the drug evaluation process, via several seminar studies and articles, including a study published in Aging that announced a short-list of promising novel geroprotective compounds, an article in Nature Communications that demonstrated the proof-of-concept application of a new algorithm capable of quantifying and classifying changes in gene expression between young and old tissues, a study in Oncotarget that was the first to apply deep generative adversarial networks (GANs) to generating anti-cancer drug candidates with specific target properties, an a paper published in Molecular Pharmaceutics demonstrating a deep-learning based method of predicting the therapeutic class molecules using transcriptional response data. "AI is quickly becoming the main driver of progress in so many fields of science, technology and human endeavor that it is easy for one to lose count. From healthcare to finance to governance, AI is galvanizing rapid paradigm shifts all around us. The pioneering work done by Biogerontology Research Foundation scientists in the application of deep learning and Generative Adversarial Networks (GANS) to drug discovery and development proves this to be the case for the pharmaceutical industry as well" said Dmitry Kaminskiy, Managing Trustee of 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. Professor Youngsook Park is the leading futurist in Korea, who serves as Chair of Millennium Project Korea. She also represents several global futures research organizations such as TechCastGlobal, and Davinci Institute. She has been Information Officer of the British Embassy Seoul (1982-2000) and Director of Public Diplomacy of the Australian Embassy Seoul (2000-2010) where she was trained as a futurist by attending World Future Society conferences, and other futurists meetings. She now teaches Futures Studies at Ewha Woman's University Graduate School for Design (2013-present) and lectures Futures Studies at Yonsei University (2006-present). Park is known for bringing global futurists to Korea for the last 30 years, and is a co-organizer of Korea Future Forum along with News1, a Korean news agency, inviting famous futurists to Seoul to speak on futures. She founded the Korea Foster Care Association after learning from the futures studies that Korean population declines drastically and needs to stop exporting Korean orphans to overseas. Professor Park is the official representative of Insilico Medicine, Inc in Korea.
Makarev E.,Atlas Regeneration Inc |
Makarev E.,Johns Hopkins University |
Fortney K.,Atlas Regeneration Inc |
Fortney K.,Stanford University |
And 6 more authors.
Oncotarget | Year: 2015
Many attempts have been made to evaluate the safety and potency of human induced pluripotent stem cells (iPSCs) for clinical applications using transcriptome data, but results so far have been ambiguous or even contradictory. Here, we characterized stem cells at the pathway level, rather than at the gene level as has been the focus of previous work. We meta-analyzed publically-available gene expression data sets and evaluated signaling and metabolic pathway activation profiles for 20 human embryonic stem cell (ESC) lines, 12 human iPSC lines, five embryonic body lines, and six fibroblast cell lines. We demonstrated the close resemblance of iPSCs with ESCs at the pathway level, and provided examples of how pathway activity can be applied to identify iPSC line abnormalities or to predict in vitro differentiation potential. Our results indicate that pathway activation profiling is a promising strategy for evaluating the safety and potency of iPSC lines in translational medicine applications.
Osipov A.N.,Moscow Institute of Physics and Technology |
Grekhova A.,RAS Emanuel Institute of Biochemical Physics |
Pustovalova M.,RAS Semenov Institute of Chemical Physics |
Zhavoronkov A.,Johns Hopkins University |
And 3 more authors.
Oncotarget | Year: 2015
Molecular and cellular responses to protracted ionizing radiation exposures are poorly understood. Using immunof luorescence microscopy, we studied the kinetics of DNA repair foci formation in normal human f ibroblasts exposed to X-rays at a dose rate of 4.5 mGy/min for up to 6 h. We showed that both the number of ?H2AX foci and their integral fluorescence intensity grew linearly with time of irradiation up to 2 h. A plateau was observed between 2 and 6 h of exposure, indicating a state of balance between formation and repair of DNA double-strand breaks. In contrast, the number and intensity of foci formed by homologous recombination protein RAD51 demonstrated a continuous increase during 6 h of irradiation. We further showed that the enhancement of the homologous recombination repair was not due to redistribution of cell cycle phases. Our results indicate that continuous irradiation of normal human cells triggers DNA repair responses that are different from those elicited after acute irradiation. The observed activation of the error-free homologous recombination DNA double-strand break repair pathway suggests compensatory adaptive mechanisms that may help alleviate long-term biological consequences and could potentially be utilized both in radiation protection and medical practices.
Zhavoronkov A.,The Biogerontology Research Foundation |
Zhavoronkov A.,InSilico Medicine |
Frontiers in Genetics | Year: 2015
Aging is a complex continuous multifactorial process leading to loss of function and crystalizing into the many age-related diseases. Here, we explore the arguments for classifying aging as a disease in the context of the upcoming World Health Organization's 11th International Statistical Classification of Diseases and Related Health Problems (ICD-11), expected to be finalized in 2018. We hypothesize that classifying aging as a disease with a "non-garbage" set of codes will result in new approaches and business models for addressing aging as a treatable condition, which will lead to both economic and healthcare benefits for all stakeholders. Actionable classification of aging as a disease may lead to more efficient allocation of resources by enabling funding bodies and other stakeholders to use quality-adjusted life years (QALYs) and healthy-years equivalent (HYE) as metrics when evaluating both research and clinical programs. We propose forming a Task Force to interface the WHO in order to develop a multidisciplinary framework for classifying aging as a disease with multiple disease codes facilitating for therapeutic interventions and preventative strategies. © 2015 Zhavoronkov and Bhullar.
PubMed | Xpansa, RAS Engelhardt Institute of Molecular Biology, The Biogerontology Research Foundation, Johns Hopkins University and 3 more.
Type: Journal Article | Journal: Nucleic acids research | Year: 2016
Aging research is a multi-disciplinary field encompassing knowledge from many areas of basic, applied and clinical research. Age-related processes occur on molecular, cellular, tissue, organ, system, organismal and even psychological levels, trigger the onset of multiple debilitating diseases and lead to a loss of function, and there is a need for a unified knowledge repository designed to track, analyze and visualize the cause and effect relationships and interactions between the many elements and processes on all levels. Aging Chart (http://agingchart.org/) is a new, community-curated collection of aging pathways and knowledge that provides a platform for rapid exploratory analysis. Building on an initial content base constructed by a team of experts from peer-reviewed literature, users can integrate new data into biological pathway diagrams for a visible, intuitive, top-down framework of aging processes that fosters knowledge-building and collaboration. As the body of knowledge in aging research is rapidly increasing, an open visual encyclopedia of aging processes will be useful to both the new entrants and experts in the field.
Makarev E.,Johns Hopkins University |
Cantor C.,Boston University |
Cantor C.,Retrotope |
Zhavoronkov A.,Johns Hopkins University |
And 6 more authors.
Aging | Year: 2014
Age-related macular degeneration (AMD) is a major cause of blindness in older people and is caused by loss of the central region of the retinal pigment epithelium (RPE). Conventional methods of gene expression analysis have yielded important insights into AMD pathogenesis, but the precise molecular pathway alterations are still poorly understood. Therefore we developed a new software program, "AMD Medicine", and discovered differential pathway activation profiles in samples of human RPE/choroid from AMD patients and controls. We identified 29 pathways in RPE-choroid AMD phenotypes: 27 pathways were activated in AMD compared to controls, and 2 pathways were activated in controls compared to AMD. In AMD, we identified a graded activation of pathways related to wound response, complement cascade, and cell survival. Also, there was downregulation of two pathways responsible for apoptosis. Furthermore, significant activation of pro-mitotic pathways is consistent with dedifferentiation and cell proliferation events, which occur early in the pathogenesis of AMD. Significantly, we discovered new global pathway activation signatures of AMD involved in the cell-based inflammatory response: IL-2, STAT3, and ERK. The ultimate aim of our research is to achieve a better understanding of signaling pathways involved in AMD pathology, which will eventually lead to better treatments.
PubMed | Moscow Institute of Physics and Technology, University of Liverpool, Xpansa, The Biogerontology Research Foundation and 4 more.
Type: Journal Article | Journal: Aging | Year: 2015
As the level of interest in aging research increases, there is a growing number of geroprotectors, or therapeutic interventions that aim to extend the healthy lifespan and repair or reduce aging-related damage in model organisms and, eventually, in humans. There is a clear need for a manually-curated database of geroprotectors to compile and index their effects on aging and age-related diseases and link these effects to relevant studies and multiple biochemical and drug databases. Here, we introduce the first such resource, Geroprotectors (http://geroprotectors.org). Geroprotectors is a public, rapidly explorable database that catalogs over 250 experiments involving over 200 known or candidate geroprotectors that extend lifespan in model organisms. Each compound has a comprehensive profile complete with biochemistry, mechanisms, and lifespan effects in various model organisms, along with information ranging from chemical structure, side effects, and toxicity to FDA drug status. These are presented in a visually intuitive, efficient framework fit for casual browsing or in-depth research alike. Data are linked to the source studies or databases, providing quick and convenient access to original data. The Geroprotectors database facilitates cross-study, cross-organism, and cross-discipline analysis and saves countless hours of inefficient literature and web searching. Geroprotectors is a one-stop, knowledge-sharing, time-saving resource for researchers seeking healthy aging solutions.
News Article | November 21, 2016
Monday, November 21, 2016, Oxford, United Kingdom: Today the Biogerontology Research Foundation announced the international collaboration on signaling pathway perturbation-based transcriptomic biomarkers of aging. On November 16th scientists at the Biogerontology Research Foundation alongside collaborators from Insilico Medicine, Inc, the Johns Hopkins University, Albert Einstein College of Medicine, Boston University, Novartis, Nestle and BioTime Inc. announced the publication of their proof of concept experiment demonstrating the utility of a novel approach for analyzing transcriptomic, metabolomic and signalomic data sets, titled iPANDA, in Nature Communications. "Given the high volume of data being generated in the life sciences, there is a huge need for tools that make sense of that data. As such, this new method will have widespread applications in unraveling the molecular basis of age-related diseases and in revealing biomarkers that can be used in research and in clinical settings. In addition, tools that help reduce the complexity of biology and identify important players in disease processes are vital not only to better understand the underlying mechanisms of age-related disease but also to facilitate a personalized medicine approach. The future of medicine is in targeting diseases in a more specific and personalized fashion to improve clinical outcomes, and tools like iPANDA are essential for this emerging paradigm," said João Pedro de Magalhães, PhD, a trustee of the Biogerontology Research Foundation. The algorithm, iPANDA, applies deep learning algorithms to complex gene expression data sets and signal pathway activation data for the purposes of analysis and integration, and their proof of concept article demonstrates that the system is capable of significantly reducing noise and dimensionality of transcriptomic data sets and of identifying patient-specific pathway signatures associated with breast cancer patients that characterize their response to Toxicol-based neoadjuvant therapy. The system represents a substantially new approach to the analysis of microarray data sets, especially as it pertains to data obtained from multiple sources, and appears to be more scalable and robust than other current approaches to the analysis of transcriptomic, metabolomic and signalomic data obtained from different sources. The system also has applications in rapid biomarker development and drug discovery, discrimination between distinct biological and clinical conditions, and the identification of functional pathways relevant to disease diagnosis and treatment, and ultimately in the development of personalized treatments for age-related diseases. "iPANDA represents a significant contribution to the emerging application of deep learning algorithms to transcriptomic and signalomic data analysis, and is a substantial extension of the approach the team put forward previously through their OncoFinder algorithm. The capacity of iPANDA to reduce the dimensionality of transcriptomic and signalomic data sets makes it a very useful tool in rapid biomarker development and accelerated drug discovery, in formulating personalized treatments to promote improved clinical outcomes, in bringing the results of in silico analyses closer to their experimental counterparts, and in the analysis of transcriptomic and signalomic data originating from multiple sources. While the team predicted and compared the response of breast cancer patients to Taxol-based neoadjuvant therapy as their proof of concept, the application of this approach to patient-specific responses to biomedical gerontological interventions (e.g. to geroprotectors, which is a clear focus of the team's past efforts), to the development of both generalized and personalized biomarkers of ageging, and to the characterization and analysis of minute differences in ageging over time, between individuals, and between different organisms would represent a promising and exciting future application" said Franco Cortese, Deputy Director of the Biogerontology Research Foundation. "This latest achievement on the part of Alex Zhavoronkov and his team is yet another step toward greater heights and bolder frontiers in the application of deep learning to personalized medicine, biomarker characterization and accelerated drug discovery. The publication of this proof-of-concept experiment in Nature Communications is a testament to the importance of their latest accomplishment, to the substantial progress that the team has made over the past 2 years, and to the great heights and ground-breaking achievements that they are sure to reach in the years to come. It represents yet another successful validation of the usefulness of their entire approach - namely, the application of deep learning to biomedicine, geroscience and P3 (personalized, precision and preventative) medicine." said Dmitry Kaminskiy, Managing Trustee of the Biogerontology Research Foundation. The Biogerontology Research Foundation is a UK non-profit Think Tank seeking to fill a gap within the research community, whereby the current scientific understanding of the aging process is not yet being sufficiently exploited to produce effective medical interventions. The BGRF will fund research which, building on the body of knowledge about how aging happens, will develop biotechnological interventions to remediate the molecular and cellular deficits which accumulate with age and which underlie the ill-health of old age. Addressing aging damage at this most fundamental level will provide an important opportunity to produce the effective, lasting treatments for the diseases and disabilities of aging, which are 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 aging, and to address not just the symptoms of age-related diseases but also the mechanisms of those diseases.
Zhavoronkov A.,The Biogerontology Research Foundation |
Zhavoronkov A.,Ludwig Maximilians University of Munich |
Litovchenko M.,The Biogerontology Research Foundation |
Litovchenko M.,Ludwig Maximilians University of Munich
International Journal of Environmental Research and Public Health | Year: 2013
While the doubling of life expectancy in developed countries during the 20th century can be attributed mostly to decreases in child mortality, the trillions of dollars spent on biomedical research by governments, foundations and corporations over the past sixty years are also yielding longevity dividends in both working and retired population. Biomedical progress will likely increase the healthy productive lifespan and the number of years of government support in the old age. In this paper we introduce several new parameters that can be applied to established models of economic growth: the biomedical progress rate, the rate of clinical adoption and the rate of change in retirement age. The biomedical progress rate is comprised of the rejuvenation rate (extending the productive lifespan) and the non-rejuvenating rate (extending the lifespan beyond the age at which the net contribution to the economy becomes negative). While staying within the neoclassical economics framework and extending the overlapping generations (OLG) growth model and assumptions from the life cycle theory of saving behavior, we provide an example of the relations between these new parameters in the context of demographics, labor, households and the firm. © 2013 by the authors; licensee MDPI, Basel, Switzerland.