Insilico Medicine CEO Alex Zhavoronkov featured among World’s Top 50 Innovators

    Insilico Medicine founder and CEO Alex Zhavoronkov, PhD will speak as part of the World’s Top 50 Innovators, presented September 26-28 by Codex in London. The event features technology innovators — including scientists, engineers, entrepreneurs, and visionaries — who are addressing the world’s greatest challenges with bold ideas and breakthrough technologies.

The innovators will provide a 15-minute Codex Talk for the event sharing their expertise and predictions for the future. Zhavoronkov will be featured among a group of innovators in artificial intelligence (AI) and share insights into how AI is transforming drug discovery. Other innovators in the space include Caroline Gorski, CEO of R2 Factory at Rolls Royce; Daniel Nathrath, CEO of Ada Health, and Mark Warner, CEO of Faculty. There will also be a number of speakers focused on robotics, discussing its use in surgery, agriculture, and sustainable development.

With an end-to-end AI-driven drug discovery platform called Pharma.AI that will soon be supported by an AI-powered robotics lab, Insilico Medicine is utilizing technology to change the speed, efficiency and cost at which new drugs are produced. Drawing on trillions of data points, Insilico’s multi-part platform can quickly comb through data to discover novel targets for drugs (PandaOmics), design new molecules to fit those targets (Chemistry42), and predict the outcome of Phase 2 clinical trials (InClinico). The company has raised nearly $400 million in venture capital funding since it launched in 2014 and its lead AI-discovered and AI-designed drug for idiopathic pulmonary fibrosis is currently in Phase 1 trials, the first drug of its kind to reach this milestone. The Company has 30 additional drugs developed from its AI platform being advanced through its internal pipeline for indications including cancer, fibrosis, and COVID-19.

“We are shifting the paradigm for how drugs are produced,” says Insilico Medicine founder and CEO Alex Zhavoronkov. “I’m honored to share what we’ve learned in applying artificial intelligence and robotics to drug development and design as one of the World’s Top 50 Innovators. Current advances in technology have allowed us to completely reimagine how we can understand and treat disease and the more we share and collaborate, the faster we can move to improve human health.”

Zhavoronkov will speak on Mon., Sept. 26, 1:15-2:15pm London time, followed by a Q&A. The three-day event will be shown live at the Wellcome Collection museum in London. Swiss watchmaker Blancplain is the event’s Timekeeper and will provide timepieces as prizes for Best Codex Talk, Top Female Innovator, and Most Impactful Innovation.

About Insilico Medicine

Insilico Medicine, a clinical stage end-to-end artificial intelligence (AI)-driven drug discovery company, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques to discover novel targets and to design novel molecular structures with desired properties. Insilico Medicine is delivering breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system (CNS) diseases and aging-related diseases.

For more information, visit www.insilico.com     

For media inquiries, please contact media@insilicomedicine.com

Deep Longevity granted the first microbiomic aging clock patent

The patent describes a technology to create anti-aging diets and probiotic treatments

 The neural network that can estimate the age of a person based on their gut flora aging was originally announced on the bioRxiv preprint server in 2018, and later published in a Cell iScience research piece: “Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning”. The Company's scientists identified bacteria that could slow down or speed up the basic aging processes and thereby affect the lifespan of a person. The article also displayed diabetes as an aging-related disease that promoted the aging of the gut community.

Deep Longevity filed the USPTO application and converted it to an international patent application in 2019. The granted patent (document ID US 11373732 B2, issued on 6/28/2022) includes claims on the method allowing the interpretation of gut metagenomic information in the context of aging. More specific applications of this technology described among the claims include:

altering the gut flora in a way that rejuvenates the host;

AI-generated reports on the pace of aging;

digital apps;

personalized anti-aging diet plans;

and probiotics.

The issued patent strategically guarantees that Deep Longevity holds priority over any anti-aging applications based on gut community profiling and ensures that the company gains the leading role in this field. The company is planning to develop commercial products based on the patent in 2023.

Deep Longevity is a pioneer in the field of biogerontology and develops anti-aging analytic software based on AI algorithms. The company holds several patents on the applications of deep learning in anti-aging research, including the applications of digital aging models for drug design. Deep Longevity has published other peer-reviewed research studies on such digital models based on epigenetic data, clinical blood tests, psychological surveys, facial images, and gene expression data. Earlier this month, Deep Longevity released a new web-service FuturSelf that features a psychological aging clock and a recommendation engine aimed at maximizing users’ mental health and well-being (read on EurekAlert!). Consumers and employers have dramatically increased their demand for virtual mental health programs in recent years. It is the objective of the Company to access this market through the online research resource FuturSelf by providing a much-needed virtual mental health and wellbeing offering to both employers and employees.

Insilico identifies therapeutic targets implicated in aging using AI and hallmarks of aging framework

 Identifying dual-purpose therapeutic targets that are implicated in aging and disease will extend healthspan and delay age-related health issues.

Longevity.Technology: People worldwide are living longer. According to WHO, one in six people in the world will be aged 60 years or over by 2030. However, aging increases vulnerability to a wide range of human disorders, including cancers, diabetes, cardiovascular diseases and neurodegenerative diseases. Roughly two-thirds of the 150,000 people who die each day globally suffer from age-associated diseases.

Recent aging research suggests that targeting the aging process itself could ameliorate many age-related pathologies. The research proposed by Insilico’s scientists aims to leverage AI to identify potential targets that are implicated in multiple age-associated diseases and also play a role in the basic biology of aging, which may have substantial benefits for the discovery and development of therapeutics for both aging and age-associated diseases.

Insilico Medicine, a clinical stage end-to-end artificial intelligence (AI)-driven drug discovery company, today announced that it has successfully established a unique approach to identify potential dual-purpose therapeutic targets of aging and age-associated diseases with PandaOmics, its proprietary AI-enabled biological target discovery platform. The research was published in Aging and moved at a rapid pace – from conceptualisation to paper submission, the whole process was accomplished in two months.

Insilico deployed PandaOmics to perform target identification for 14 age-associated diseases (AADs) and 19 non-age-associated diseases (NAADs) across multiple disease areas to identify targets of age-associated disease. Upon the comprehensive assessment, 145 genes were considered as potential aging-related targets and mapped into corresponding aging hallmark(s), including 69 high confidence targets with high druggability, 48 medium novel targets with high or medium druggability, and 28 highly novel targets with medium druggability.

“Developing interventions that target multiple age-associated diseases and aging itself could result in unprecedented health benefits by not only treating disease but also extending healthspan and providing for more fresh drug repurposing candidates” said Alex Zhavoronkov PhD, CEO of Insilico Medicine. “The current study also demonstrated the power of PandaOmics AI-powered target discovery platform to identify novel dual-purpose targets not only for specific disorders but across multiple types of diseases in a cost-saving and time-efficient manner.”

A list of potential therapeutic dual-purpose aging targets for drug discovery was disclosed in the paper.

The importance of dual-purpose therapeutic target identification

Many diseases are very heterogeneous when it comes to targets, especially in the course of the disease. It is extremely difficult to treat a big population with a single targeted drug or even a combination. The most recent data shows that the aged population (≥50 years old) accounts for 77% of global deaths, of which the majority cause is related to age-associated diseases such as cardiovascular diseases, cancers, diabetes and other neurodegenerative disorders. It suggests that aging plays an important role in different diseases.

A substantial percentage of the human clinical trials, including those evaluating investigational anti-aging drugs, fail in Phase II, a phase where the efficacy of the drug is tested. This poor success is in part due to inadequate target choice and the inability to identify a group of patients who will most likely respond to specific agents. This challenge is further complicated by the differences in the biological age of the patients, as the importance of therapeutic targets varies between the age groups. Unfortunately, most targets are discovered without considering patients’ age and being tested in a relatively younger population (average age in phase I is 24). Hence, identifying potential targets that are implicated in multiple age-associated diseases, and also play a role in the basic biology of aging, may have substantial benefits.

Identifying dual-purpose targets that are implicated in aging and disease at the same time will extend healthspan and delay age-related health issues – even if the target is not the most important in a specific patient, the drug would still benefit that patient.

“When it comes to targets identification in chronic diseases, it is important to prioritize the targets that are implicated in age-associated diseases, implicated in more than one hallmark of aging, and safe,” said Zhavoronkov. “So that in addition to treating a disease, the drug would also treat aging – it is an off-target bonus.”

Ulta Beauty & Haut.AI partner to bring new era of beauty and healthcare with AI-powered hyper-personalization

 

Ulta Beauty and Haut.AI partner to develop disruptive, inclusive, personalized artificial intelligence engine for skin health and beauty

Today, Haut.AI, a leading research and development company specializing in next-generation artificial intelligence for skincare and longevity, announced a strategic partnership with Ulta Beauty, the largest beauty retailer in the United States. 

The Ulta Beauty and Haut.AI partnership is rooted in a shared goal  to co-create innovative digital skincare tools and offer beauty enthusiasts even greater experiences. Together, the two leaders will enhance skin analysis technology with enriched data, skin algorithms, simulations and improved recommendations.

“Our teams are laser focused on imagining – and reimagining – the most engaging guest experiences across every Ulta Beauty touchpoint,” said Prama Bhatt, chief digital officer, Ulta Beauty. “As industry leaders, we are thrilled to bring forward innovative solutions that serve our guests and cannot wait to see how our partnership with Haut.AI will deliver for guests as we marry our passions for personalization, data-driven technology and beautiful possibilities.”

Since its inception in 2018, Haut.AI has focused on developing and applying next-generation artificial intelligence technologies for skincare, beauty and longevity. The innovative leader supports advanced R&D activities of major global skincare brands and manufacturers, particularly in new product development, testing and collection of claims, and consumer studies.

Ulta Beauty and Haut.AI’s highly experienced, technical and product teams share a vision to help beauty enthusiasts achieve short-term skincare goals, in addition to preserving and improving skin long term. Together, the teams will co-create disruptive, exciting ways to hyper-personalize daily skincare routines.

“An AI-based system that can identify skin issues is not a novelty today. We recognize the next big step is how consumers experience these systems,” said Anastasia Georgievskaya, chief executive officer, Haut.AI. “Our solution is highly accurate and with Ulta Beauty, we will create an AI engine to address consumer skin needs early to prevent deterioration, while tailoring recommendations to individual preferences spanning texture, smell, brand values and preferred ways to shop. Who said science-backed, AI-powered skincare can’t be fun?” 

As part of the partnership, Haut.AI’s will build new capabilities and utilize its inclusive skin scan technology which has been rigorously tested and validated on a curated image dataset. . In turn, Ulta Beauty will enrich Haut.AI’s recommendation engine with consumer insights and product preferences to create a next-generation omnichannel shopping experience.

About Haut.AI

Haut.AI is a leading global artificial intelligence company specializing in skincare and longevity. It combines advanced deep learning techniques for machine vision, deep generative models for synthetic data generation, and reinforcement learning with expert human dermatologists, nutritionists, and biogerontologists for the development of advanced hyper-personalized recommendation engines for beauty, skincare, and longevity.

Haut.AI is headquartered in Estonia, the digital hub of the European Union. It prides itself on supporting diversity and inclusion by developing AI that works equally well for different skin types and skin colors, as well as developing novel techniques for recognizing bias. The company’s SaaS solution currently serves global skincare brands, retailers and contract research organizations in 27 different markets.

For further inquiries please contact press@haut.ai and visit our website https://haut.ai.

Insilico Medicine Applauded by Frost & Sullivan for Enabling Rapid and Cost-Effective Drug Discovery and Development with Its Pharma.AI Platform

 The Pharma.AI platform combining deep generative models (GAN), reinforcement learning (RL), transformers, and other modern machine learning techniques enables the identification of novel targets, generation of novel molecules non-existent in the chemical space, and prediction of outcomes for clinical trials.

SAN ANTONIO, Mar. 15, 2022 /PRNewswire/ — Based on its recent analysis of the global artificial intelligence (AI)-enabled drug discovery industry, Frost & Sullivan recognizes Insilico Medicine with the 2021 Entrepreneurial Company of the Year Award in the global AI-enabled drug discovery industry.

Pharma.AI, the end-to-end AI-enabled drug discovery and development platform of Insilico, addresses challenges that touch on chemistry, biology, and digital medicine. The combined AI and drug discovery expertise enable the identification of novel targets, generation of novel molecules non-existent in the chemical space, and prediction of outcomes for clinical trials. The AI solutions and verified automated AI platform streamline research and development (R&D) efforts, remodel therapeutics discovery, and advance precision medicine. In addition, these solutions accelerate research workflow, leading to rapid and cost-effective discovery and development.

According to Supriya Lala Kundu, industry analyst at Frost & Sullivan, “Insilico’s AI platforms integrate GANs, reinforcement learning (RL), and transformer neural networks to automate multi-targeting, polypharmacolocogy, and holistic diseases assessment. The company is working on AI-powered robotics to create driverless drug discovery as it moves towards advanced technologies and 100% automation.”

PandaOmics is one of the AI-enabled engines of Pharma.AI which integrates proteomics, transcriptomics, and other data types with advanced AI algorithms. PandaOmics supports target disease identification and supports research and target identification for different diseases. The AI-powered platform provides complex algorithms that recommend relevant novel drug target hypotheses in a few days rather than several months, significantly reducing drug discovery timelines.

Insilico Medicine also utilizes multiple algorithms that rapidly evaluate the targets for possible binding sites to address the challenge of transitioning from target to small molecules with desired properties. Chemistry42, a small molecule generation engine of Pharma.AI platform with 30 algorithms, identifies the right pockets and designs a range of molecules that do not exist in the chemical space within a few days. In addition, the engine enables the filtering from billions of generated molecules to identify easy-to-synthesize and inexpensive-to-develop molecules with the highest success potential. Chemistry42TM , a cloud and on-premise hardware-agnostic and scalable platform that can be licensed and tested by clients, delivers new actionable drug-like molecules in days.

“Insilico leverages its proprietary AI-driven platforms to effectively address the challenges of identifying accurate targets, developing novel molecular structures with desired parameters, and predicting clinical trial outcomes. Its deep technical expertise facilitates accelerated and cost-efficient novel therapeutic compound design and innovative drug discovery for cancer, fibrosis, infectious diseases, and aging-related diseases. For example, in 2021, Insilico initiated the first-in-human study of a potentially first-in-class drug candidate with a novel target for fibrosis. Notably, the company completed the entire discovery process from target discovery to preclinical candidate nomination within 18 months on a budget of $2.6 million. Furthermore, Insilico nominated two preclinical candidates with a novel molecular structure for anemia of chronic kidney disease and inflammatory bowel disease within 12 months using its AI engine. Such milestones thoroughly validate Insilico’s AI platform as robust and effective,” Kundu explained further.

In addition to the two engine mentioned above that have already been launched as software, InClinicoTM , another AI-powered engine in development by Insilico which could provide prediction of outcomes for clinical trials has exciting prospects as well. With its strong overall performance, growing partnerships, focus on innovation, and expertise in end-to-end drug discovery and development, Insilico Medicine earns Frost & Sullivan’s 2021 Entrepreneurial Company of the Year Award in the global AI-enabled drug discovery industry.

Each year, Frost & Sullivan presents this award to the company that has demonstrated excellence in devising and implementing a strong growth strategy. The recipient has shown strength in terms of innovation in products and technologies, leadership in customer value, and speed in response to market needs. The award looks at the emerging market participants in the industry and recognizes their best practices that are positioned for future growth excellence.

Frost & Sullivan Best Practices Awards recognize companies in various regional and global markets for demonstrating outstanding achievement and superior performance in leadership, technological innovation, customer service, and strategic product development. Industry analysts compare market participants and measure performance through in-depth interviews, analyses, and extensive secondary research to identify best practices in the industry.

About Insilico Medicine

Insilico Medicine, an end-to-end AI-driven drug discovery and development company, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. Insilico Medicine has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques to discover novel targets and to design novel molecular structures with desired properties. Insilico Medicine is delivering breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system (CNS) diseases and aging-related diseases. For more information, visit www.insilico.com.

Insilico Medicine enters research collaboration with the University of Zurich to apply Insilico's generative Artificial Intelligence platform for the discovery of potential therapeutics for Cystinosis

 - Cystinosis is a rare genetic disease affecting 1 in 100,000-200,000 live births and poses a lifelong risk to those affected. Cystinosis slowly destroys the body's organs including the kidneys, eyes, thyroid, muscles, liver, pancreas, gonads, and brain.

- There are currently no curative treatments for cystinosis.

- The Mechanisms of Inherited Kidney Disorders (MIKADO) group at the University of Zurich (UZH) and Insilico Medicine will be working together to identify, rank, and annotate novel drug targets to identify potential therapeutics for cystinosis.

NEW YORK and ZURICH, March 9, 2022 /PRNewswire/ -- The MIKADO group, a translational team at the UZH focused on generating evidence-driven insights to understand and treat rare inherited kidney diseases, and Insilico Medicine, an end-to-end Artificial Intelligence (AI)-driven drug discovery company, today announced a research and development collaboration designed to accelerate the discovery of transformative novel therapeutics for cystinosis. The duration of the initial research collaboration will be one year.

Specifically, the MIKADO group will leverage its multi-omics databank obtained from preclinical models and cystinosis-based cell models by using Insilico's comprehensive novel target discovery AI platform PandaOmics to identify cellular and molecular pathways that drive life-threatening complications in cystinosis patients. The MIKADO group will analyse disease-relevant targetable pathways and utilize Insilico's proprietary algorithms to generate libraries of small molecule compounds that are expected to be validated in preclinical models and cystinosis cell systems using disease-relevant screening technologies developed by the MIKADO group at the UZH.

"I am thrilled by the collaboration between MIKADO and Insilico. With the power of artificial intelligence-driven, systems biology-based drug discovery, we intend to accelerate the analysis and discovery of drug targets, with the goal of bringing novel breakthrough medicines to cystinosis patients while decreasing costs and increasing probabilities of success," said Olivier Devuyst, MD, Ph.D., head of MIKADO group at the UZH.

"Cystinosis is a commonly neglected disease with large unmet need. We are pleased to partner with MIKADO at the UZH combining the best of PandaOmics target discovery AI and human intelligence for the potential benefit of cystinosis patients worldwide," said Alex Zhavoronkov Ph.D., CEO of Insilico Medicine.

Using innovative preclinical models and disease-relevant phenotype screening, we aim to validate novel drug targets for diseases which no cure has been found. Ultimately, we want to improve the quality of life for those affected by the disease and bring tangible hope to thousands of cystinosis patients around the world," said Alessandro Luciani Ph.D., senior scientist and team leader at MIKADO.

For more information, images, or interviews, please contact media@insilicomedicine.com

About Cystinosis

Cystinosis—one of a family of approximately 70 rare inborn diseases of the metabolism known as lysosomal storage diseases that collectively affect 1 in 5,000 live births—is caused by inactivating mutations in the CTNS gene encoding the proton-driven transporter cystinosin, which exports cystine from the lysosome. Its functional loss leads cystine to accumulate within the lysosome of tissues across the body, culminating in severe multiorgan dysfunctions that affect primarily the brain, eyes, liver, muscles, pancreas, and kidneys. Fanconi syndrome is the first manifestation of cystinosis, usually presenting within the first year of life and characterized by the early and severe dysfunction of the kidney proximal tubule, most often complicated by chronic kidney disease and life-threatening manifestations. In their second to third decade of life, patients with cystinosis can also develop hypothyroidism, hypogonadism, diabetes, myopathy, and deterioration of fine vision and decline of the central nervous system. Beyond supportive care, the only available FDA-approved strategy to counteract cystine storage is the oral administration of cysteamine, which allows cystine to exit from the lysosomes. However, cysteamine treatment is hampered by side effects and poor tolerance, and it does not prevent nor treat PT dysfunction and kidney disease. Therefore, there is an urgent need to develop novel therapeutics for this devastating disease.

About Insilico Medicine

Insilico Medicine, an end-to-end artificial intelligence (AI)-driven drug discovery company, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques to discover novel targets and to design novel molecular structures with desired properties. Insilico Medicine is delivering breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system (CNS) diseases and aging-related diseases.

For more information, please visit www.insilico.com. Follow us on LinkedIn

About MIKADO group

The group "Mechanisms of Inherited Kidney Disorders" led by Prof. Dr. med. Olivier Devuyst and Dr. Alessandro Luciani is investigating the fundamental mechanisms that cause inherited kidney disorders affecting the epithelial cells lining the kidney tubule, leading to chronic kidney disease (CKD) ¾ one of the fastest growing disease worldwide and a major public health burden. Combining human genetic studies with innovative model organisms (e.g., rat and zebrafish) and physiologically relevant cellular systems, and integrating them with OMICs technologies and cutting-edge screening assays, we are applying the knowledge gained from fundamental studies of epithelial cell biology to develop disease biomarkers and novel therapeutics that might potentially improve the care for patients with genetic disorders affecting the kidney and other organs. The MIKADO group has established a zebrafish platform to perform high-throughput and high-content screens for kidney disease therapeutics, and a biochemical profiling platform adapted to microsamples (high-throughput screens coupled to clinical studies or metabolic studies in model organisms).

For more information, please visit https://www.physiol.uzh.ch/en/research/institutegroups/grdevuyst.html. Follow us on Twitter

SOURCE Insilico Medicine

Insilico Medicine Initiates First-in-Human Study of ISM001-055, a Novel Drug Discovered Using Insilico's Proprietary End-to-end Artificial Intelligence Platform

NEW YORK and HONG KONG, Nov. 30, 2021 /PRNewswire/ -- Insilico Medicine, an end-to-end artificial intelligence (AI)-driven drug discovery company, today announced that the first healthy volunteer has been dosed in a first-in-human microdose trial of ISM001-055.

ISM001-055 is a potentially first-in-class small molecule inhibitor of a novel biological target discovered by Pharma.AI, Insilico Medicine's end-to-end AI-powered drug discovery platform. It is being developed for the treatment of idiopathic pulmonary fibrosis (IPF), a chronic lung disease which results in progressive and irreversible decline in lung function. After completing IND-enabling studies, Insilico Medicine has initiated the microdose trial to begin characterizing the pharmacokinetic profile in humans. The trial, administering ISM001-055 intravenously in healthy volunteers, is being conducted in Australia.


ISM001-055 demonstrated highly promising results in multiple preclinical studies including in vitro biological studies, pharmacokinetic and safety studies. The compound significantly improved myofibroblast activation which contributes to the development of fibrosis. ISM001-055's novel target is potentially relevant to a broad range of fibrotic indications.

"We are very pleased to see Insilico Medicine's first antifibrotic drug candidate entering into the clinic. We believe this is a significant milestone in the history of AI-powered drug discovery because to our knowledge the drug candidate is the first ever AI-discovered novel molecule based on an AI-discovered novel target. We have leveraged our end-to-end AI-powered drug discovery platform, including the usage of generative biology and generative chemistry, to discover novel biological targets and generate novel molecules with drug-like properties. ISM001-055 is the first such compound to enter the clinic, and we expect more to come in the near future," said Feng Ren, Ph.D., CSO of Insilico Medicine.

Previously, Insilico Medicine demonstrated its ability to generate drug-like hit molecules using AI with the publication of the Generative Tensorial Reinforcement Learning (GENTRL) system for a well-known target in record time. It also demonstrated the target's proof of concept by applying deep learning techniques for the identification of novel biological targets. This novel antifibrotic program combined these target discovery and generative chemistry capabilities. Notably, Insilico Medicine completed the entire discovery process from target discovery to preclinical candidate nomination within 18 months on a budget of $2.6 million.

"Insilico Medicine has achieved this breakthrough milestone which is extremely impressive. Many drugs were discovered accidentally when scientists designed a drug for disease A and then they found out that it actually works for some different disease B. AI is a way to search for information and look for signals for drug discovery. This achievement didn't happen by chance and is a reproducible method and procedure which is revolutionary," said Michael Levitt, 2013 Nobel Laureate in Chemistry and member of Insilico Medicine's Scientific Advisory Board.

"What impresses me the most about this achievement is not only the lower cost or faster speed of development but, also it demonstrated the Pharma AI platform can overcome the low probability of getting to this stage," said Alex Zhavoronkov, Ph.D., Founder and CEO of Insilico Medicine. "There are very few examples of a pharmaceutical company discovering a new target for a broad range of diseases, designing a novel molecule, and initiating human clinical trials. To my knowledge, nobody has achieved this with AI to-date. The failure rates in preclinical target discovery are very high and even after the targets are validated in animal models, over half of Phase 2 clinical trials fail primarily due to the choice of target. Target discovery is the fundamental grand challenge of the pharmaceutical industry. With ISM001-055 we used end-to-end AI connecting biology, chemistry in order to assess activity and safety in multiple preclinical models."

About Insilico Medicine

Insilico Medicine, an end-to-end artificial intelligence (AI)-driven drug discovery company, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques to discover novel targets and to design novel molecular structures with desired properties. Insilico Medicine is delivering breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system (CNS) diseases and aging-related diseases. For more information, visit www.insilico.com.

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