San Diego (CA) – Insilico Medicine, in collaboration with ChemDiv, Inc., launched a drug discovery initiative that aims to use the power of artificial intelligence for screening chemistry space with newly designed compounds. The initiative is expected to identify a massive of drug candidates in the early stages. That became possible because AI can scan a vast number of compounds at higher speeds and with improved accuracy compared to traditional screening projects. The new project is aimed at rapidly screening targets in various therapeutic areas, including oncology, metabolism, immunology, urology, and others.
“We have successfully identified early drug candidates by screening a limited number of compounds with our AI virtual screening platform,” said Alex Zhavoronkov, Ph.D., Founder and CEO of Insilico Medicine. “ChemDiv significantly increases our capabilities by opening a great lead-like and drug-like novel chemical space with reliable support. Our joint effort to evaluate these diverse compounds increases the likelihood of developing new drugs for existing targets with less adverse effects.”
“We are connecting AI technology with ChemDiv’s efforts and investments in the design and validation of novel chemistry,” said Sergey Bugrov, Executive Director, ChemDiv. “The feasible chemical space of 3 billion molecules partitioned in validated unique scaffolds and available for modeling is represented by 1.7 million physical compounds. This new approach, will immediately provide researchers with many more starting points for drug discovery and significantly improve their process”.
ChemDiv is a recognized global leader in drug discovery solutions. Over the past 29 years, ChemDiv has delivered hundreds of leads, drug candidates and new drugs in the area of CNS, oncology, virology, inflammation, cardiometabolic and immunology, to pharma, biotech and academic partners around the globe. [
About Insilico Medicine
Insilico Medicine is an artificial intelligence company headquartered in Hong Kong, with offices in six countries and regions. The Company was the first to apply the generative adversarial networks (GANs) and reinforcement learning (RL) to generate new molecular structures with the specified parameters in 2015. In addition to collaborating with large pharmaceutical companies, Insilico Medicine is also pursuing internal drug discovery programs in different disease areas and anti-aging fields. Recently, Insilico Medicine published some of the results in Nature Biotechnology and secured $37 million in series B funding. Website
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Insilico Medicine: Klug Gehilfe
ChemDiv: Ron Demuth,
This part of information is sourced from https://www.eurekalert.org/pub_releases/2019-10/im-aga101519.php