Using AI technology to “rejuvenate”, Insilico's anti-aging research has established more than 250 industry-university cooperation

As the health care industry and the development of data acquisition technology, AI combination of technology and biomedical industries showing great potential, not only in the pharmaceutical sector has made many breakthroughs in biology of aging-related issues have begun to advance deeper the study.

Since ancient times, China has spread the story of immortality and seeking medicine. Insilico Medicine, a medical and bioinformatics company based in Baltimore, USA, is bringing these mythological stories into reality.

In 2014, Insilico Medicine was founded by founder Alexander Zhavoronkov. The company specializes in discovering new drugs using AI technology, extending lifespan, and working on personal health management and ageing issues.

To date, Insilico Medicine has raised $8.26 million from investors such as Deep Knowledge Ventures, JHU A-Level Capital and Juvenescence.

According to Arterial Network, it has been learned from many overseas media that Insilico Medicine is defined as a venture capital market, which is a market for new-type high-tech enterprises in the development period to conduct share financing. The company's main competitors in the US are Atomwise, twoXAR and Qrativ.

As CEO of Insilico Medicine, Zhavoronkov has the largest number of company employees in the same period. In the past two years, they have received a total of $6.8 million in financing, bringing in $5.7 million in revenue for the company.

Efficient team as the core strength

Currently, Insilico Medicine has research teams in Russia, the United Kingdom, Switzerland, Poland and the United States, and research and development cooperation in Canada, Israel, Switzerland and China.

Through the application of AI technology, Insilico Medicine has established more than 250 industry-university cooperation projects, successfully established applications in drug development and biomarker research and development, and has become an innovation driver in the pharmaceutical industry.

Insilico Medicine's experience team includes Chairman Alexander Aliper, Chief Operating Officer Kingsong Zhu and founder Zhavoronkov himself. Prior to joining the company, Qingsong Zhu received postdoctoral training at Johns Hopkins University School of Medicine.

According to the arterial network, Zhavoronkov focused on aging research at the beginning of his career. By collecting a large number of multi-class omics data from a wide range of health and patient populations of different ages, a comprehensive analysis of these data is performed using machines to identify biomarkers associated with aging and disease. At present, Zhavoronkov and his team work together with companies in a variety of related fields to practice and innovate, and strive to discover anti-aging drugs and delay the life of patients.

Zhavoronkov said that medical research and development is a task that cannot be underestimated. The cost of research and development for each drug can reach $2.6 billion, while the cost of developing these drugs globally is $150 billion. This explains why in 2014, only 46 new drugs were introduced. The failure rate of new drug development was 92%. And there are about 60,000 diseases in reality.

It can be seen that the struggle between medical research and development and human aging is not easy. Insilico Medicine promotes everyone's life cycle quality (QALY) with the goal of promoting AI technology. Currently, each additional unit of QALY will cost $60,000. This will be guided by the development of new drugs.

In addition, the professional background of founder Zhavoronkov also supports his research and innovation in the AI ​​technology and biological research industry. He is 39 years old this year. He holds a Ph.D. in biophysics, a master's degree in biotechnology and a bachelor's degree in computer science, and has a rich career in biomatter and regenerative medicine.

As a well-known scholar in the field of aging research in the world, Zhavoronkov published "Across the Aging: How Biomedical Progress Will Change the Global Economy" in December 2015. The perspectives explored in the book deal with the mechanisms of human aging, the reform of the pension system of interest to the government, and the increasing ageing population of social economists. In his view, the social and economic problems caused by the aging of the United States, Japan and other countries have profound implications for China.

By 2020, China's population over 60 years old is expected to reach 250 million. China will become one of the most aging countries in the world, and it will bring many burdens and problems. Anti-aging research in biomedicine will likely change this situation by delaying the standard age of retirement and even redefining the “aged population” in the broadest sense.

Zhavoronkov has always believed that AI technology is an important way to improve the pharmaceutical industry, improve industrial efficiency and reduce the risk of aging. The company uses its expertise in deep neural network machine learning to help them develop drugs to treat aging diseases.

PHARMA. AI, Young. AI and NUTRIOMI are three important products of Insilico Medicine:

PHARMA. AI: After investigation, it was found that there are not many people who can have multiple sets of studies, drugs, clinical experience and deep neural network knowledge. PHARMA. As one of the projects developed by Insilico Medicine, AI is dedicated to alleviating the lack of professionals in the biomedical industry for several years.

By acquiring millions of unified multi-omics data and human data samples, PHARMA. AI helps pharmaceutical, biotechnology companies and academic teams around the world create, train, sell or license a wide range of solutions for deep neural networks. In addition, PHARMA. The tools developed by AI also help to gain insight into biomarkers and discover new drugs that will lead to personalized solutions for cancer and aging-related diseases in the future.

Young. AI Beta 1.0: Insilico Medicine launched Young in September 2017. Beta 1.0 version of AI. Young. As an intelligent platform that predicts the age of users, AI's mission is to optimize users' lives by controlling users' health and aging rates and tracking time changes. The algorithm is characterized by a neural network capable of deeply tracking tens of thousands or even millions of samples.

The project studied 21 commonly used blood parameters such as cholesterol, inflammatory markers (CRP), hemoglobin count and albumin concentration, and 17 other chemical indicators. Contrast by AI analysis combined with blood chemistry, age, ethnicity, and other data, Young. AI has produced the "first truly reliable aging clock" algorithm for humans. According to the arterial network, it is only necessary to analyze an individual drop of blood to determine an individual's life expectancy.

Anyone can visit their official website to learn about their health and future, because the analysis of the entire system is free. During the use of the platform, participants must perform a local test of 18 parameters on his blood, then upload the results to the official site and upload a photo for age assessment on visual factors. After a few seconds, the website can return to the report.

If the user's biological age is greater than his actual age, Young. The report presented by AI will effectively help users take the necessary measures to improve the weakest indicators in the body.

NUTRIOMI: As another important product of Insilico Medicine, NUTRIOMI is committed to promoting dietary health, slowing down and preventing common aging. It is unique in that it tracks the user's aging dynamics by studying individual blood biochemical data. NUTRIOMI encourages people to adopt a proper lifestyle to improve their age, maintain a balanced diet and improve their nutritional status.

What advantages does Insilico Medicine have in the pharmaceutical industry? It is understood that Insilico Medicine is the first company to apply "Generation Against Network (GAN)", which is dedicated to the deep analysis of molecular structures with specific parameters to predict the most effective drug molecules.

GAN, selected by MIT Technology Review as one of the top ten technologies in 2018, is unique in that it can train two networks at the same time. One is to generate a network, also called a generator, and the other is to identify the network. Discriminator.

We have proposed a metaphor for this concept that is easy to understand. GAN's idea is a two-player game. The sum of the interests of the two sides of the game is a constant. For example, two people are arrogant, assuming that the total space is certain, and your strength is greater. Then you will get a little more space, and the corresponding space will be less. On the contrary, I will get a little more strength, but one thing is certain. The total space of my two is certain. This is the two. Game, but the total benefit is certain. Two players in the GAN, one is the generation model and the other is the identification model.

The generated model is randomly sampled from the potential space as an input, and its output needs to mimic the real sample in the training set as much as possible. The input in the discriminant model is the actual sample or the output of the generated network. The purpose is to distinguish the output of the generated network from the real sample as much as possible. The generation of the network is to deceive the network as much as possible. The two networks confront each other and constantly adjust the parameters. The ultimate goal is to make the discriminating network unable to judge whether the output of the generated network is true.

The ultimate goal of using GAN is to train high-quality artificial intelligence by allowing these two networks to compete and compete with each other while learning from each other.

The biggest advantage of GAN comes from the introduction of the discriminator, so that we don't have to worry about designing the objective function for tasks that are difficult to measure directly with mathematical formulas. With GAN, we can let the discriminator learn to judge the style of the image.

In addition, Insilico Medicine is willing to share research results in the academic field and is committed to maintaining a long-term and stable relationship with readers. The company regularly publishes groundbreaking papers on Oncotarget and Molecular Pharmaceutics to summarize their research.

In 2016, Insilico Medicine's paper on Molecular Pharmaceutics demonstrated their research and application of deep neural networks. The article proposes to use the transcription reaction data to predict the category of molecular therapy. The article received the American Chemical Society Editor's Choice Award.

In November 2017, Insilico Medicine published a new paper on the application of next-generation AI and blockchain technology and support to promote user control and management of personal data. A recent paper published in the journal of gerontology also demonstrates the company's rational assessment of the impact of neural networks on the patient's physiological age.

It can be seen that Insilico Medicine contributes to humanity in AI biomedical and scientific pharmaceuticals. Its corporate philosophy, advantages and products will lay a strong foundation for future human health management and control of aging.

To date, Insilico Medicine has partnered with 11 research institutes and pharmaceutical companies in the application of a new generation of artificial intelligence technology. Among them, the cooperation between Insilico Medicine and Juvenescence has greatly helped the company's product development.

As a financial investment company specializing in aging research, Juvenescence prioritizes and develops the combination of AI technology and the pharmaceutical industry to bring the most advanced medical services to customers and patients.

According to the Arterial Network, Juvenescence has brought in molecular diagnostic techniques for deep learning research to Insilico Medicine and introduced multi-modal biomarkers for human aging.

Its chairman, James Mellon, is a billionaire businessman from the UK who is committed to supporting and contributing to human life research. His expertise, biotechnology and pharmaceutical management have enabled the company to increase industry efficiency and focus on commercialization potential. Mellon graduated from the University of Oxford with a master's degree in 1978.

In 2015, Insilico Medicine won the title of “Most Potential Company” at the Palo Alto Personalized Medicine World Congress.

In 2016, Insilico Medicine and Singapore-based Asia Genomics signed an agreement to develop advanced anti-aging biomarkers and personalized longevity technologies for the Asian population to extend the life span of Asians.

In 2017, Insilico Medicine was listed as the five most influential global artificial intelligence companies by NVIDIA founder Huang Renxun. In 2018, it was also named as the 2018 Global AI Artificial Intelligence Top 100 by CB Insights, a well-known venture capital research institution.

In March of the same year, Insilico Medicine established the first artificial intelligence R&D center in Asia as an artificial intelligence pioneer in Taiwan, and announced that its subsidiary “Taiwan Inco Intelligence” was established in Taiwan.

Taiwan's Inco Smart Future will focus on the development and verification services of “Generation Against Network (GAN)”, using Taiwan's rich medical biotechnology talents to strengthen the application and learning of medicinal chemistry, and continue to work closely with Asian biotechnology, pharmaceuticals and skin care. Cooperation.

Innovation in the medical industry is based on cooperation and communication. Just like Insilico Medicine, whether it is artificial intelligence technology or big data-related research and development, discussions and discussions with companies in various fields will make ideas come to action and avoid paper talk.

Of course, sharing the company's research results in words or multimedia on a regular basis is also the best way to interact with readers. It not only promotes the accumulation and development of knowledge in the medical field, but also increases the visibility of the company and attracts potential investors.

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