News Release

Combining GANs and reinforcement learning for drug discovery

Peer-Reviewed Publication

InSilico Medicine

Graphical Representation of GANs Making New Molecules

video: Insilico Medicine combines the Generative Adversarial Networks with the Reinforcement Learning to design the effective drug candidates. view more 

Credit: Insilico Medicine, Inc.

Thursday, May 10, 2018, Baltimore, MD - Insilico Medicine, a Baltimore-based next-generation artificial intelligence company specializing in the application of deep learning for target identification, drug discovery and aging research announces the publication of a new research paper in Molecular Pharmaceutics journal titled "Adversarial Threshold Neural Computer for Molecular De Novo Design". The described Adversarial Threshold Neural Computer (ATNC) model based on the combination of Generative Adversarial Networks (GANs) with Reinforcement Learning (RL) is intended for the design of novel small organic molecules with the desired set of pharmacological properties.

"This is a proof of concept scratching the surface of what we have in house. Stay tuned for the cool experimental validation results to be announced this Summer. I hope that part of this work integrated into our pipeline will help make the world a better and healthier place and help make perfect molecules for specific targets and multiple targets that will have a much higher chance of becoming great drugs", said Evgeny Putin, the deep learning lead at Insilico Medicine.

The architecture of GANs was initially proposed by Ian Goodfellow in 2015, and since the inception, the GAN-based models have achieved the unprecedented accuracy in image, video and text generation. The fundamental principle of GANs is adversarial training based on the competition between the Generative and Discriminative networks that leads to joint evolution and highly accurate results with the desired properties. Insilico Medicine scientists pioneered the application of GANs and their conjunction with RL for drug discovery process and published the proof of concept.

"The GAN-RL architecture proposed by Putin in this paper demonstrated the ability to generate a substantial percentage of valid and unique molecular structures. This study is a proof of concept using string representations of molecular structure and internally we are using multiple integrated generators with reinforcement learning and the proprietary representation of molecular structure, which allows us to synthesize the exact molecules and link chemistry and biology", said Alex Zhavoronkov, the founder and CEO of Insilico Medicine.


Insilico Medicine is regularly publishing research papers in peer-reviewed journals. The company was first who applied deep generative adversarial networks (GANs) to the generation of new molecular structures with specified parameters and published seminal proof of concept papers in the field. The paper published in Molecular Pharmaceutics in 2016 demonstrated the proof of concept of the application of deep neural networks for predicting the therapeutic class of the molecule using the transcriptional response data, received the American Chemical Society Editors' Choice Award. A recent paper published in November 2017 described the application of the next-generation AI and blockchain technologies to return the control over personal data back to the individual. 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.

For further information, images or interviews, please contact:
Contact: Qingsong Zhu, PhD

About Insilico Medicine, Inc

Insilico Medicine, Inc. is an artificial intelligence company headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, with R&D and management resources in Belgium, Russia, UK, Taiwan and Korea sourced through hackathons and competitions. The company and its scientists is 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 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. Brief company video:

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.