Insilico Medicine to present its research in AI Drug Discovery at the AI World Conference

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Credit: Insilico Medicine


Thursday, November 28th, 2018 – Insilico Medicine, a Rockville-based company developing the end-to-end drug discovery pipeline utilizing the next generation artificial intelligence, will present its latest results in modern and next-generation AI for Drug Discovery at the AI World Conference in Boston on December 4th.

Artificial Intelligence (AI) techniques, such as deep learning (DL) and reinforcement learning (RL) play a pivotal role in making the hunt for new pharmaceuticals quicker and more effective. The panel discussion will focus on how Artificial Intelligence is changing Drug Discovery and how to tackle the major challenges in the industry.

“We are happy to present our work at the AI World Conference, which gathers the key industry leaders. The topic of AI for drug discovery is rapidly gaining popularity, and we are happy to be at the leading edge of research and one of the innovation drivers in the area”, says Alex Zhavoronkov, Ph.D., Founder, and CEO of Insilico Medicine, Inc.

AI World Conference brings together all the enterprise executives, decision makers, and business leaders from across the entire artificial intelligence and machine learning ecosystem. The Conference is held on December 3-5.

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Insilico Medicine is regularly publishing research papers in peer-reviewed journals. The company was first to apply the generative adversarial networks (GANs) to the generation of the new molecular structures with the specified parameters and published a seminal peer-reviewed paper submitted in June 2016. The concept was further extended and augmented with advanced memory and reinforcement learning. One of the latest papers published in the Journals of Gerontology demonstrated the application of the deep neural networks to assessing the biological age of the patients. The latest special issue in Molecular Pharmaceutics featured several research papers by Insilico Medicine. Recently the company published an overview of its work in artificial intelligence for aging and longevity research in Aging Research Reviews.

For further information, images or interviews, please contact:

Contact: Polina Firsanova

[email protected]

Website: http://insilico.com/

Official website of the conference:

https://aiworld.com/

About Insilico Medicine, Inc

Insilico Medicine is an artificial intelligence company headquartered in Rockville, with R&D and management resources in Belgium, Russia, UK, Taiwan, and Korea sourced through hackathons and competitions. The company and its scientists are dedicated to extending human productive longevity and transforming every step of the drug discovery and drug development process through excellence in biomarker discovery, drug development, digital medicine, and aging research.

Insilico pioneered the applications of the generative adversarial networks (GANs) and reinforcement learning for generation of novel molecular structures for the diseases with a known target and with no known targets. In addition to working collaborations with the large pharmaceutical companies, the company is pursuing internal drug discovery programs in cancer, dermatological diseases, fibrosis, Parkinson’s Disease, Alzheimer’s Disease, ALS, diabetes, sarcopenia, and aging. Through a partnership with LifeExtension.com, the company launched a range of nutraceutical products compounded using the advanced bioinformatics techniques and deep learning approaches. It also provides a range of consumer-facing applications including Young.AI.

In 2017, NVIDIA selected Insilico Medicine as one of the Top 5 AI companies in its potential for social impact. In 2018, the company was named one of the global top 100 AI companies by CB Insights. In 2018 it received the Frost & Sullivan 2018 North American Artificial Intelligence for Aging Research and Drug Development Award accompanied with the industry brief. Brief company video: https://www.youtube.com/watch?v=l62jlwgL3v8. http://www.insilico.com

Media Contact
Qingsong Zhu
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