News Release 

Insilico Medicine announces the spin-off of Deep Longevity

InSilico Medicine


IMAGE: Insilico Medicine announces the spin-off of Deep Longevity view more 

Credit: Insilico

14th of July, 2020, Hong Kong -- Today, Insilico Medicine announced a spin-off of its aging biomarker and deep aging clock business. On the 4th of July, the new company called Deep Longevity, Inc successfully completed a round of funding led by the reputable biotechnology and longevity investors. The company will focus on the development and commercialization of novel artificial intelligence methods and tools to track the rate of aging using a broad range of biological, medical, and behavioral data types.

In 2016 Insilico Medicine published its first peer-reviewed paper demonstrating the utility of deep neural networks trained on anonymized clinical blood tests for prediction of human biological age. Since then the company published a broad range of deep aging clocks trained on laboratory tests, transcriptomic, microbiome, imaging, and other data types.

"In 2014 Insilico Medicine started as an innovation hub for the applications of artificial intelligence to a broad range of biology and chemistry problems to accelerate every aspect of drug discovery. We also actively engaged in aging research. However, as the company matured, we decided to focus our efforts on AI for novel target discovery, generative chemistry, prediction of clinical trials, and development of our own therapeutic programs. This spin-off demonstrates our commitment to becoming a leading AI-powered biotechnology company", said Alex Zhavoronkov, PhD, CEO of Insilico Medicine


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. 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

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