Insilico partners with APRINOIA on AI-powered neurodegenerative drug discovery

Insilico enters into a collaboration with APRINOIA to apply novel generative AI-powered system to discover novel compounds for neurodegenerative diseases

Wednesday, 30th of December, 2020 (9:00AM, Taipei) - Insilico Medicine is pleased to announce that it has entered into a research collaboration with APRINOIA Therapeutics to utilize Insilico's novel generative artificial intelligence (AI) technology to accelerate the discovery of next generation compounds targeting abnormal proteins in brain associated with neurodegenerative diseases.

"We are excited to initiate the collaboration with Insilico to enrich APRINOIA's proprietary collection of compounds for neurodegeneration," said Dr. Ming-Kuei Jang, CEO of APRINOIA.

"Early diagnosis is critical for disease management. Our initial focus is to discover novel imaging PET tracers to quantify and visualize pathologies of abnormal proteins in the brain. With Insilico's AI-powered platform, we are hoping to shorten the time from lab to clinics to benefit patients and in the medical communities."

With a mission to accelerate drug discovery and development, Insilico Medicine has been breaking new grounds with its next-generation AI technologies and expanding international partnerships in the US, Europe and Asia Pacific Region.

"APRINOIA discovers and develops first-in-class diagnostics and therapeutics that can be broadly applied as PET tracers in the field of neurodegenerative diseases. We are glad to collaborate with APRINOIA, where we will apply our Chemistry42 suite to design a new generation of PET tracers with desired properties. Through this collaboration, we will further demonstrate the universality of our AI-powered generative chemistry platform," said Jimmy Yen-Chu Lin, PhD, CEO of Insilico Medicine Taiwan.

By leveraging an integrated AI-driven drug discovery approach, Insilico Medicine provides APRINOIA Therapeutics with an effective, rational, external auxiliary solution for driving programs forward. The partnership between APRINOIA and Insilico will include an upfront fee and performance-based milestones.

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About APRINOIA Therapeutics

APRINOIA Therapeutics is currently advancing a pipeline featuring diagnostic and therapeutic programs, collectively targeting brain disorders associated with abnormal accumulation of pathological proteins, including tau and alpha-synuclein, from its proprietary small molecule and antibody discovery platforms. APRINOIA is committed to building a pipeline of innovative products, as well as developing partnership with global and regional pharmaceutical companies to accelerate its programs. The company currently has operations in Taipei, Suzhou, Shanghai, Tokyo, and Boston.
Website: http://www.aprinoia.com

About Insilico Medicine

Since 2014 Insilico Medicine is focusing on generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with the specified parameters, generation of synthetic biological data, target identification, and prediction of clinical trials outcomes. Recently, Insilico Medicine secured $37 million in series B funding. Since its inception, Insilico Medicine raised over $52 million, published over 100 peer-reviewed papers, applied for over 25 patents, and received multiple industry awards.
Website: http://insilico.com/

Media Contact
For further information, images or interviews, please contact:
ai@insilico.com

Scientists publish the first human psychological aging clock using artificial intelligence

 

Scientists at Deep Longevity published the first set of psychomarkers of aging developed using deep learning to track the changes in human psychology; the new PsychoAge and SubjAge aging clocks were linked to mortality risk

Today, Deep Longevity, a company developing artificial intelligence to track human aging and extend productive longevity, released the first AI-powered psychological aging clocks to analyze and interpret psychosocial factors in the context of aging. Deep Longevity researchers, joined by Dr. Peter Diamandis, the visionary physician, engineer, and entrepreneur, the founder of the XPRIZE Foundation and Singularity University published their study titled "PsychoAge and SubjAge: Development of Deep Markers of Psychological and Subjective Age Using Artificial Intelligence" in Aging.

Like other species following the classical evolutionary paradigm, humans are born, develop, reproduce, take care of their young, and then gradually decline and die. However, humans are conscious intelligent species and change their behavior, priorities, beliefs, and attitude, during life. Prior works on Socioemotional Selectivity Theory (SST) demonstrated that human life horizons can be manipulated and affect their behavior. To better understand the features that affect psychological age, and perceived age, and the mind-body connection in the context of aging, scientists at Deep Longevity decided to apply their skills in the development of deep biomarkers of aging to human psychology.

Biomarkers of aging that can accurately quantify the human aging process using various biological data types, commonly referred to as the "aging clocks", are among the most important recent advances in the field of longevity research. For example, in November, Deep Longevity scientists published one such aging clock based on DNA methylation, which showed superior performance to all other comparable solutions.

Despite massive progress in aging clock technology, the psychological aspect of aging has been severely understudied. However, the new study on deep psychomarkers of aging is expected to substantially accelerate the progress in the psychology of aging. The recently published study aims to fill this gap by demonstrating two AI-based age predictors: PsychoAge (which predicts chronological age) and SubjAge (which describes personal aging rate perception). These models were trained on a collection of >10,000 questionnaires completed by people aged 25-75 years as a part of the MacArthur Foundation's "Midlife in the United States (MIDUS)" study. The models presented in the publication were reworked into 15-question long surveys available at Young.AI to enable people to find out estimates of their psychological and subjective age.

The authors of the study verified the SubjAge on large independent datasets to discover that higher SubjAge is very predictive of all-cause mortality. More specifically, a person whose SubjAge is five years greater than the chronological age he or she reported is twice as likely to die as a person with normal age perception.

The authors also point out how SubjAge can be manipulated therapeutically to make patients feel younger and thus reduce their mortality risk. For example, developing openness to new experiences can reduce SubjAge prediction by seven years. Keeping the bar high, being productive and not backing away from difficult-to-reach goals will take another four years off of a person's psychological aging clock.

"For the first time, AI can predict human psychological and subjective age and help identify the possible interventions that can be applied in order to help people feel and behave younger" said Alex Zhavoronkov, PhD, founder and CLO of Deep Longevity and co-author of the study. "One's mindset may determine the decisions that ultimately affect their overall health. By identifying the psychosocial variables that underpin particular mindsets and behaviors, deep psychological clocks can serve as a powerful tool in promoting personal improvement, mental health, wellness, and a wide range of other health and therapeutic applications."

In follow-up studies of psychological aging, Deep Longevity plans to explore differences in the perception of aging between men and women, examine psychosocial markers connected to mental health, and build an integrated model of mental-physical health crosstalk.

About Young.AI: Young.AI is an AI-powered longevity web platform & iOS app created by the product of Deep Longevity. Young.AI users can access a variety of aging analysis tools, including psychological and subjective age estimation, to reach productive longevity.

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About Deep Longevity: Originally incubated by Insilico Medicine, Deep Longevity was acquired on 14 December 2020 by Regent Pacific Group Limited (SEHK:0575.HK), a specialist healthcare, wellness and life sciences investment group. Deep Longevity is developing explainable artificial intelligence systems to track the rate of aging at the molecular, cellular, tissue, organ, system, physiological, and psychological levels. It is also developing systems for the emerging field of longevity medicine, enabling physicians to make better decisions on the interventions that may slow down or reverse the aging processes. Deep Longevity developed the Longevity as a Service (LaaS) solution to integrate multiple deep biomarkers of aging dubbed "deep aging clocks" to provide a universal multifactorial measure of human biological age. http://longevity.ai

Longenesis announces Curator platform for privacy-preserving data use for COVID-19 research

 Longenesis announces the first deployment of its flagship product Curator for real-time, privacy-preserving biomedical data identification, with National Research Programme in Latvia for COVID-19 research acceleration and Federated Learning pipeline

Longenesis - a digital health startup aiming towards acceleration of the biomedical research pipeline worldwide, announced a release of its product Curator. It is a platform where clinical institutions and patient organizations are connected in consortiums with potential collaboration partners and study sponsors to initiate further cooperation. Main difference between existing solutions - ability to showcase available personalized datasets without compromising privacy.

Curator provides an opportunity to search for specific biomedical data by different combinations of descriptive characteristics without revealing personal data. It means that actual data sets are left within the institution. However, Curator notifies the data custodian that researchers or institutions are interested in contacting patients or using a particular dataset. This approach provides data controlling mechanisms to the data publishing institutions and the patients. Thus, Curator provides an opportunity for clinical investigators, patient organisations, registries, biobanks and other institutions to showcase the scope of data that could be used for research without compromising the privacy of patients and data protection regulations.

"The majority of solutions aimed to address the similar challenges are providing a centralized approach towards data storing and structuring, powered by the ingestion of data from multiple centers. Such approaches limit the ability to utilize the hidden value of personalized data for scientific breakthroughs, while preserving privacy and ethical aspects in the first place. Pandemic just amplified previously described problems and highlighted the necessity to find solutions for fragmented data as well as initiate collaboration. SARS-CoV-2 accelerated the need for data changing pace from monthly to daily. Moreover, to quickly act and find the treatment, data has to be in-sync not only in one institution, but also providing real-time identification among multiple centers in various geographies. Thus, with a centralised approach for metadata curation, Longenesis becomes an essential tool at the forefront of biomedical international research," says Emil Syundyukov, Longenesis Chief Technical Officer.

Currently the company Longenesis has already initiated a collaboration with 20+ clinical institutions, as well as patient organizations, biobanks, genomic sequencers, and digital health startups in the U.S., South Korea, Northern and Central European region and the Middle East, utilizing the platform for COVID-19, metabolic disorder and oncology research.

One of the strategic projects to mention is collaboration with the Latvian Biomedical Research and Study Centre (BMC), University of Latvia, Riga Stradins University and Riga Technical University. The aim of the cooperation is to use a solution to accelerate COVID-19 research and engagement with international scientific groups. Within the framework of National Research program to Mitigate Consequences of COVID-19, National Biobank of Latvia - Genome Database of Latvia maintained by BMC has established cohort of over 500 COVID-19 patients. Latvian COVID-19 cohort includes various types of samples (blood, serum, plasma, oropharyngeal swabs, PBMC, feces, urine, isolated DNA, RNA), molecular data (blood biochemistry, cytokine panel, genome wide genotyping, viral genome data, metagenome, metabolome, and transcriptome data) as well as excessive characterization of each clinical case. Being also engaged in utilization of COVIDomic platform, developed by Insilico Medicine, providing multi-omics analysis and patient stratification and severity prognosis, such approach would dramatically accelerate the process of international collaborations and new discoveries in COVID-19 space.

"The platform will significantly impact infrastructure development and acquire many new competencies in Latvia that reaches far outside the COVID-19 research frame. The COVID-19 data set is the most evaluated and data-rich disease cohort in Latvia. The development of such an integrated platform is a large step towards implementing personalized preventive medicine in the nearest future," says prof. Janis Klovins, director of Latvian Biomedical Research and Study Centre (BMC).

The Curator platform has enabled safe sharing of this significant research resource to wider scientific audience. The platform has opened collaboration across distributed COVID-19 datasets keeping the link to biological samples that is crucial factor for management of world-wide COVID-19 pandemics.

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For press and other inquiries:
+371 20201964
Emil Syundyukov
es@longenesis.com

About Longenesis:

Longenesis, co-founded by Insilico Medicine and other top-tier biotech players, is a medical technology startup company working towards providing a technological bridge between Healthcare institutions and the BioTech industry with an aim to help identify and unlock the hidden value of biomedical data to accelerate the novel drug and treatment discovery and provide better help to those of need. Our team has experience working with the biomedical organizations and unlocking the potential for accelerating the R&D process around the globe, including National level projects in the Middle East, U.S., EU and APAC regions.

About the National Research Programme of Latvia to Mitigate Consequences of COVID-19
(Project No. VPP-COVID-2020/1-0016)

The main goal of this project is to create a well-managed, secure and centralized biobank and data exchange resource to support the activities that would limit the spread of the virus, search for novel biomarkers and treatment strategies, facilitate the establishment of new international collaborations. Project will be an important part of the overarching objective of the National Research Program for mitigation of the impact of COVID-19. The main concept behind this approach is to provide centralized service for scientific groups involved in COVID-19 research limiting the unnecessary overlapping of activities related to patient recruitment, data gathering, analytical tests.

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents.

Imagining perfect molecules using AI - a benchmarking system for generative chemistry

 

 

Insilico Medicine together with collaborators announces the publication of Molecular Sets (MOSES), a benchmarking system for generative chemistry models

November 30, 2020 - Insilico Medicine, a leading company in AI-powered drug discovery, today announced that the paper titled "Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models" was published in Frontiers in Pharmacology. In addition to the authors from Insilico Medicine and Neuromation, the author list includes Simon Johansson and Hongming Chen from AstraZeneca, Benjamin Sanchez Lengeling from Harvard University, and Alan Aspuru-Guzik from Vector Institute, Department of Computer Science, University of Toronto, and Canadian Institute for Advanced Research (CIFAR).

"With the rapid development of new generative chemistry, it is crucial to compare machine learning models in a unified way; with MOSES, we can easily compare new models with existing approaches without reimplementing all the baselines. MOSES is a result of tight collaboration between multiple generative chemistry labs; together we polished the platform over the last two years and made it as simple and intuitive as possible. We are glad to help researchers obtain interpretable, reproducible results with our platform.", said Daniil Polikovskiy, senior author of the paper.

In 2018, Insilico Medicine presented Molecular Sets (MOSES) benchmarking platform that was employed by multiple research groups since then. MOSES contains a carefully curated dataset, a set of metrics, and a wide variety of baselines for comparing generative models for chemistry. Over the last two years, we extended the repository with new baselines, enhanced evaluation protocols, and implemented simple routines for using MOSES out of the box. Today, Insilico Medicine announces that the manuscript describing the platform has been accepted for publication in Frontiers in Pharmacology, "Artificial intelligence for Drug Discovery and Development" special issue. The paper will soon be available here: https://www.frontiersin.org/articles/10.3389/fphar.2020.565644. For more information on MOSES, please visit the GitHub repository https://github.com/molecularsets/moses.

To cite the paper: https://www.frontiersin.org/articles/10.3389/fphar.2020.565644

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Media Contact

For further information, images, or interviews, please contact: ai@insilico.com

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform (http://www.insilico.com/platform/) and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents. Website insilico.com

Deep Longevity Launches The First Longevity Medicine Course For Physicians

Regent Pacific Group Limited ("Regent Pacific" or the "Company" and together with its subsidiaries, the "Group"; SEHK:0575.HK)'s Deep Longevity, Inc, a company subject to a conditional acquisition by the Group which is a pioneer in deep biomarkers of aging and longevity today announced the launch of the first Longevity Medicine course for Physicians on LabXchange Platform. It is the first of several Longevity Medicine chapters, with upcoming courses scaled for scientists and patients.

This course is aimed to fill the educational gap in translation longevity medicine. Deep Longevity, a leader in artificial intelligence for the development of biomarkers of aging and longevity, brought together scientists and physicians engaged in basic and translational research to develop the course: "Longevity Medicine for Physicians". The course covers basics in translational aging research from terminology and demographic aspects, theories and hallmarks of aging, basic aging pathways and mechanisms behind the possibly geroprotective interventions and covers the various types of aging clocks.

The course is intended for medical professionals and students, who have limited time and seek a comprehensive, well-structured, reliable course. It contains three hours of core lectures providing an introduction to the field, lecture slides, lecture notes, quizzes, guest lectures, as well as references to additional reading materials and online resources. Introduction to Longevity Medicine is the first course in a series intended to provide advanced physicians with the latest approaches in longevity technology.

"As we are partnering with the advanced clinical institutions we see the gap between translational research and clinical practice and would like to provide the MDs with the resources they need to get into the rapidly growing field of longevity medicine, learn about the latest advances in artificial intelligence and in the pharmaceutical industry", said Alex Zhavoronkov, PhD, the founder of the Longevity Medicine course and Chief Longevity Officer at Deep Longevity.

"While much-scattered information is available from more or less evidence-based sources, there was a lack of a structured, guided and well organized course that provides physicians with the necessary background information on this rapidly evolving discipline of healthy longevity. This is why we developed this very first course in Longevity Medicine - to close this gap and provide understandable and practicable, credible resources for clinicians", said Evelyne Bischof, MD, co-founder of the course.

Earlier this year, Deep Longevity received investments from expert longevity investment funds related to clinical organizations and is currently subject to a conditional acquisition by Regent Pacific Group Limited (SEHK:0575.HK), a public company whose securities are listed on The Stock Exchange of Hong Kong Limited. It also announced a partnership with Human Longevity Inc, one of the world's most advanced centers for preventative diagnostic medicine. Since then, it has partnered with several other advanced clinics and hospitals.

For details of the course, please visit: longevity-medicine.org  

This press release is distributed by LBS Communications Consulting Limited.

About Deep Longevity

Deep Longevity is subject to a conditional acquisition by Regent Pacific Group Limited (SEHK:0575.HK), a public company whose securities are listed on The Stock Exchange of Hong Kong Limited. Deep Longevity is developing explainable artificial intelligence systems to track the rate of aging at the molecular, cellular, tissue, organ, system, physiological, and psychological levels. It is also developing systems for the emerging field of longevity medicine enabling physicians to make better decisions on the interventions that may slow down, or reverse the aging processes. Deep Longevity developed Longevity as a Service (LaaS)© solution to integrate multiple deep biomarkers of aging dubbed "deep aging clocks" to provide a universal multifactorial measure of human biological age. Originally incubated by Insilico Medicine, Deep Longevity started its independent journey in 2020 after securing a round of funding from the most credible venture capitalists specializing in biotechnology, longevity, and artificial intelligence. ETP Ventures, Human Longevity and Performance Impact Venture Fund, BOLD Capital Partners, Longevity Vision Fund, LongeVC, co-founder of Oculus, Michael Antonov, and other experts AI and biotechnology investors supported the company. Deep Longevity established a research partnership with one of the most prominent longevity organizations, Human Longevity, Inc. to provide a range of aging clocks to the network of advanced physicians and researchers.
http://longevity.ai/

About Regent Pacific (SEHK: 0575.HK)

Regent Pacific is a diversified investment group based in Hong Kong currently holding various corporate and strategic investments focusing on the healthcare, wellness, and life sciences sectors. The Group has a strong track record of investments and has returned approximately US$298 million to shareholders in the 21 years of financial reporting since its initial public offering.
http://www.regentpac.com/

Merck KGaA, Darmstadt, Germany to deploy Insilico Medicine's Chemistry42 AI platform

Insilico Medicine announces the first deployment of its flagship generative chemistry AI platform for de novo molecular design, Chemistry42™ on Merck KGaA, Darmstadt, Germany's high-performance computing infrastructure

November 17, 2020, 9:00AM EST-- Following the release of Chemistry42 to a select group of key experts in the pharmaceutical industry in Q3 2020, Insilico Medicine is proud to announce that Merck KGaA, Darmstadt, Germany will be the first launch partner for its flagship generative chemistry artificial intelligence (AI) platform - Chemistry42. Merck KGaA, Darmstadt, Germany will integrate Chemistry42™ into their discovery pipeline to facilitate rapid and effective drug design. Chemistry42 v1.0 will be customized and deployed on state-of-the-art high-performance computing (HPC) infrastructure at Merck KGaA, Darmstadt, Germany.

"We are very happy to have Merck KGaA, Darmstadt, Germany sign on as our very first launch partner as they have substantial experience in the field of AI-powered drug discovery internally and built a world-class computing infrastructure," said Alex Zhavoronkov, PhD, founder, and CEO, Insilico Medicine.

Since the publication of Ian Goodfellow's original paper on generative adversarial networks (GANs) in 2014, Insilico Medicine has been developing generative chemistry and generative biology algorithms. In 2016, Insilico Medicine published the first peer-reviewed publication describing the application of GANs to small molecule discovery in oncology. Between 2016 and 2020 Insilico Medicine authored over 40 papers and has been granted several patents in this field. Insilico Medicine has conducted several proof of concept validation experiments that demonstrate that generative models can successfully identify novel targets, and design molecules with desired properties that can be synthesized and tested in vitro and in vivo. 

"We're excited to continue to deploy the latest tools in AI," said Joern-Peter Halle, Global Head of Research for the Healthcare business sector of Merck KGaA, Darmstadt, Germany. "AI has the potential to transform the drug discovery process and Insilico Medicine is at the forefront of exciting AI techniques, such as this generative chemistry AI platform."

Chemistry42™ is a core part of Insilico's Pharma.ai drug discovery suite. It is a flexible, user-friendly software platform that bridges artificial intelligence (AI) and machine learning methods with domain expertise in the fields of medicinal and computational chemistry, for the design of novel small molecules with desirable physicochemical properties. The platform is a scalable distributed web application, capable of running multiple tasks in parallel in a matter of hours. Container orchestration and workflow management allow for predictable hardware-agnostic resource allocation, and for the implementation on either cloud or local HPC infrastructures.

"Chemistry42 v1.0 is the result of years of comprehensive research in generative chemistry, close collaboration between computational and medicinal chemistry scientists, and best high-performance computing engineering practices. We are excited to work closely with Merck KGaA, Darmstadt, Germany and look forward to demonstrating the impact of our collaboration on their drug discovery programs," said Alex Zhebrak, PhD, CTO of Insilico Medicine.

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About Merck KGaA, Darmstadt, Germany

Merck KGaA, Darmstadt, Germany, a leading science and technology company, operates across healthcare, life science and performance materials. Around 57,000 employees work to make a positive difference to millions of people's lives every day by creating more joyful and sustainable ways to live. From advancing gene editing technologies and discovering unique ways to treat the most challenging diseases to enabling the intelligence of devices - the company is everywhere. In 2019, Merck KGaA, Darmstadt, Germany, generated sales of € 16.2 billion in 66 countries.

The company holds the global rights to the name and trademark "Merck" internationally. The only exceptions are the United States and Canada, where the business sectors of Merck KGaA, Darmstadt, Germany operate as EMD Serono in healthcare, MilliporeSigma in life science, and EMD Performance Materials. Since its founding in 1668, scientific exploration and responsible entrepreneurship have been key to the company's technological and scientific advances. To this day, the founding family remains the majority owner of the publicly listed company.

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform (http://www.insilico.com/platform/) and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents. Website http://insilico.com/

Media Contact

For further information, images, or interviews, please contact: ai@insilico.com

Insilico Medicine rebrands Pandomics as PandaOmics, releases a new version

Insilico Medicine introduces new features in its new target discovery platform and announces a name change from Pandomics to PandaOmics

 Thursday, November 12, 2020 -- Insilico Medicinetoday announced the release of a new version of its flagship AI-powered biological target discovery system and a name change from Pandomics to PandaOmics. The original name intended to reflect that the system will handle all (pan-) omics data types and integrated the company mascot - Panda (in 2016 the company published its iPANDA algorithm for dimensionality reduction); however, due to the coronavirus pandemic, the Pandomics name got closely associated with pandemics, and the company is in the process of renaming the system. 

The PandaOmics v1.02 has multiple bug fixes and several additional features requested by the customers: 

1. Omics dataset search by therapeutic area name;

2. The ability to create meta-analysis for several Omics datasets.

3. Target ID - a collection of AI based scores that proposes actionable targets based on molecular data (analysed in PandaOmics) and previously published text-based data.

"A lot of effort has been put in the development of PandaOmics therapeutic target discovery platform. Despite the name change, we will preserve our high quality of standards and ensure that the platform will help even larger number of researchers with their drug discovery programs", said Ivan Ozerov, Target Discovery Director at Insilico Medicine, responsible for PandaOmics development from its early onset.

"While the majority of the customers got used to and liked the name Pandomics, due to COVID-19 the popular search engines started autocorrecting the name to pandemics, and we decided to make this change. Panda remains our company's mascot and we are making a minor change to the name - PandaOmics. The system is designed to provide the biomedical community with the ability to identify biological targets using gene and protein expression data as well as other data types, evaluating the novelty, assessing and annotating these targets, and performing virtual validation of these targets using prior knowledge", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine. 

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For further information, images or interviews, please contact: ai@insilico.com

About Insilico Medicine

Since 2014 Insilico Medicine is focusing on generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with the specified parameters, generation of synthetic biological data, target identification, and prediction of clinical trials outcomes. Recently, Insilico Medicine secured $37 million in series B funding. Since its inception, Insilico Medicine raised over $52 million, published over 100 peer-reviewed papers, applied for over 25 patents, and received multiple industry awards. Website http://insilico.com/

Insilico announces a multi-target AI-powered drug discovery collaboration with Janssen

Insilico Medicine, a leader in deep generative reinforcement learning for target discovery, small molecule generation, and prediction of clinical trial outcomes, today announced that it entered into a multi-target drug discovery agreement with Janssen Pharmaceutica N.V. (Janssen), one of the Janssen Pharmaceutical Companies of Johnson & Johnson. The collaboration was facilitated by Johnson & Johnson Innovation LLC. 

Under the terms of the agreement, Insilico Medicine will design small molecule hits with the defined properties for several targets nominated by Janssen and to receive upfront and milestone payments. Insilico Medicine will demonstrate the discovery process and detailed platform capabilities. 

"We are very happy to collaborate with Janssen, one of the leading and most innovative companies in the field of drug discovery. Since 2019 Insilico Medicine has been a resident of Johnson & Johnson Innovation – JLABS which facilitated closer communication with the scientists at Janssen and other companies in the ecosystem and we see this collaboration as a "graduation" from JLABS", said Alex Zhavoronkov, PhD, founder, and CEO of Insilico Medicine.

Since 2015 Insilico Medicine pioneered the field of generative adversarial networks and reinforcement learning for generative chemistry and generative biology and published multiple research publications and patents in the area including proof-of-concept studies with experimental validation. In 2020 it unveiled the Chemistry42 generative chemistry operating system and made first on-site deployments with the big pharmaceutical companies and drug discovery partnerships. 

"We are very happy to collaborate with Janssen, one of the leading and most innovative companies in the field of drug discovery. Since 2019 Insilico Medicine has been a resident of Johnson & Johnson Innovation – JLABS which facilitated closer communication with the scientists at Janssen and other companies in the ecosystem and we see this collaboration as a "graduation" from JLABS", said Alex Zhavoronkov, PhD, founder, and CEO of Insilico Medicine.

About Insilico Medicine

Insilico Medicine develops software that leverages generative models, reinforcement learning (RL), and other modern machine learning techniques for the generation of new molecular structures with specific properties. Insilico Medicine also develops software for the generation of synthetic biological data, target identification, and the prediction of clinical trials outcomes. The company integrates two business models; providing AI-powered drug discovery services and software through its Pharma.AI platform (www.insilico.com/platform/) and developing its own pipeline of preclinical programs. The preclinical program is the result of pursuing novel drug targets and novel molecules discovered through its platforms. Since its inception in 2014, Insilico Medicine has raised over $52 million and received multiple industry awards. Insilico Medicine has also published over 100 peer-reviewed papers and has applied for over 25 patents. Website http://insilico.com/

Contact: ai@insilico.com

Related Links

http://insilico.com/

Deep Longevity and SquareOne Wellness partner on deep biomarkers of aging and longevity

Deep Longevity added SquareOne Wellness to its growing longevity network; SquareOne physicians will get training in longevity medicine and interpret the AgeMetric™ reports incorporating multiple aging clocks

Today, Deep Longevity Inc, a pioneer in deep biomarkers of aging and longevity, and SquareOne Wellness announced a collaboration to deploy an extensive range of AI-powered aging clocks. Deep Longevity is to develop and provide the customized predictors of human biological age to the network of SquareOne Wellness clinicians and to provide a training program in longevity medicine.

Deep Longevity is a fully-owned subsidiary of a public company, Regent Pacific Group Limited (SEHK:0575.HK). Deep Longevity developed and exclusively in-licensed a portfolio of granted and pending patents on aging clocks developed using the latest advances in artificial intelligence.

Deep Longevity aging clocks are supported by a number of academic publications summarized in a recent review titled "BioHorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities"

"The traditional approach to preventative medicine is focused on preventing disease by diagnosing the symptoms early or reducing the risks of disease. The AI-guided longevity medicine goes much further then that and is focusing on tracking the person's rates of aging at many levels, identification of longevity bottlenecks, and utilizing the latest advances in science and technology to slow down or reverse biological and psychological aging. We are very happy to have SquareOne join the rapidly growing network of our research and clinical partners focused on providing customers with extra years of productive and happy life", said Alex Zhavoronkov, Chief Longevity Officer of Deep Longevity Inc. 

SquareOne Wellness has been on the forefront of total wellness in the treatment of addiction. SquareOne has a holistic approach to wellness and addiction whose goal is to help patients live happier, healthier and longer lives. Deep Longevity and SquareOne will partner to see the impact that the utilization of aging clocks has on continued recovery. "We are always looking for new tools to help our patients reach their full potential in their recovery and in their overall health and life. We believe that the addition of deep aging clocks will be an added tool in long term patient success", said Joshua Jones, Director of Patient Interactions of SquareOne Wellness.

In the scope of the partnership SquareOne Wellness physicians will be trained in deep aging clocks and will be able to provide their customers with AgeMetric™ reports and engage in advanced research to assess the performance of aging clocks in the context of continued recovery.

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About Regent Pacific (SEHK:0575.HK)

Regent Pacific is a diversified investment group based in Hong Kong currently holding various corporate and strategic investments focusing on the healthcare, wellness and life sciences sectors. The Group has a strong track record of investments and has returned approximately US$298 million to shareholders in the 21 years of financial reporting since its initial public offering.

http://www.regentpac.com/

About SquareOne Wellness.

SquareOne Wellness is an addiction and wellness clinic that focuses on recovery of opioid addiction and behavioral health. SOW focus is on helping patients look at every aspect of their health utilizing medically assisted treatment, behavioral health therapy and lifestyle changes to help sustain recovery and live healthier and longer lives. For more information, visit Squareonewellness.org.

About Deep Longevity, Inc

Deep Longevity has been acquired by Regent Pacific (SEHK:0575.HK), a publicly-traded company. Deep Longevity is developing explainable artificial intelligence systems to track the rate of aging at the molecular, cellular, tissue, organ, system, physiological, and psychological levels. It is also developing systems for the emerging field of longevity medicine enabling physicians to make better decisions on the interventions that may slow down, or reverse the aging processes. Deep Longevity developed Longevity as a Service (LaaS)© solution to integrate multiple deep biomarkers of aging dubbed "deep aging clocks" to provide a universal multifactorial measure of human biological age. Originally incubated by Insilico Medicine, Deep Longevity started its independent journey in 2020 after securing a round of funding from the most credible venture capitalists specializing in biotechnology, longevity, and artificial intelligence. ETP Ventures, Human Longevity and Performance Impact Venture Fund, BOLD Capital Partners, Longevity Vision Fund, LongeVC, co-founder of Oculus, Michael Antonov, and other experts AI and biotechnology investors supported the company. Deep Longevity established a research partnership with one of

the most prominent longevity organizations, Human Longevity, Inc. to provide a range of aging clocks to the network of advanced physicians and researchers.

http://longevity.ai/